Changes in Athletes' Anxiety, Anger, and Impulsiveness followingChanges in Athletes' Anxiety, Anger, and Impulsiveness following Concussion Megan Byrd Follow this and additional works at: https://researchrepository.wvu.edu/etd Recommended Citation Byrd, Megan, "Changes in Athletes' Anxiety, Anger, and Impulsiveness following Concussion" (2017). Graduate Theses, Dissertations, and Problem Reports. 5294. https://researchrepository.wvu.edu/etd/5294 This Dissertation is protected by copyright and/or related rights. It has been brought to you by the The Research Repository @ WVU with permission from the rights-holder(s). You are free to use this Dissertation in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you must obtain permission from the rights-holder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/ or on the work itself. This Dissertation has been accepted for inclusion in WVU Graduate Theses, Dissertations, and Problem Reports collection by an authorized administrator of The Research Repository @ WVU. For more information, please contact researchrepository@mail.wvu.edu. Changes in Athletes’ Anxiety, Anger, and Impulsiveness following Concussion Megan Byrd, M.S. Dissertation submitted to the College of Physical Activity and Sport Sciences at West Virginia University in partial fulfillment of the requirements for the degree of Doctor of Philosophy In Kinesiology With an emphasis in Sport and Exercise Psychology Sam Zizzi, Ed.D, Chair. Anthony Kontos, Ph.D. Edward Etzel, Ed.D Damien Clement, Ph.D., ATC College of Physical Activity and Sport Sciences Morgantown, West Virginia 2017 Keywords: Concussion, Sport, Anger, Anxiety, Impulsivity, Mental Health, Athletes Copyright 2017 Megan Byrd ABSTRACT Changes in Athletes’ Anxiety, Anger, and Impulsiveness Following Concussion Megan Byrd The impacts and effects of sport-related concussion have been considered a major health concern as early as 1999 (Kelly, 1999) and have continued to be a prominent topic of controversy among all levels of sport. Amidst this concern and controversy, the emotional impacts of sport-related concussion, particularly anxiety, anger, and impulsivity are still relatively unknown. The primary purpose of this study was to examine the relationship between sport concussions and anger, anxiety, and impulsivity in collegiate athletes. The secondary purpose of this study was to determine if there is a subset of athletes who are more likely to exhibit certain emotions based on pre-existing risk factors, or the manner in which the concussion was sustained. The study utilized a multi-method, longitudinal design and was sequential in nature. Participants were male and female collegiate athletes and completed the study during three time points: (a) 1 to 10 days post diagnosis (n = 30) (b) 11 to 21 days post-concussion (n = 12), and (c) 30 days post-concussion (n = 10). Slightly more than half (n =16) of athletes reported self or others noticing a difference in their behavior or mood since sustaining a concussion and the mean on all measures were above norms for college aged men and women during time point a. Most notably, 11 out of 30 athletes scored above a 10 on the clinical anxiety measure, indicating a diagnosable level of anxiety for Generalized Anxiety Disorder. Overall, the results indicated that the athletes were experiencing anxiety, anger, and impulsivity following concussion and anxiety seemed to be the mediating factor. The more anxious athletes felt regarding their symptoms and symptomology, the more it seemed to influence their frustration and behavior. Results indicated that the athletes believed they would benefit from education regarding the affective symptoms of concussions and that rehabilitation of concussions should be tailored to each athletes’ symptomology. iii Acknowledgments To say completing a dissertation takes a village would be a vast understatement. Luckily, I have found myself among incredible people who didn’t give up on me, even when I was ready to give up on myself. This dissertation journey began five years ago during my PhD interview with Dr. Sam Zizzi when he asked me what it meant to lose the forest among the trees. So, it’s only fitting that it ends (or starts a new beginning) in a similar fashion. The magnitude of guidance and support provided by Dr. Zizzi is unmeasurable and difficult to convey in words. Thank you for trekking through the literature forest with me and serving as a beacon of light when I found myself traveling too far. You lead by an example I can only hope to follow and are the type of advisor I strive to be. You remind me not to take myself too seriously and to always engage in karmic cleansing. Thank you. I would like to thank Dr. Anthony Kontos for agreeing to meet me in a coffee shop two years ago, and even more so for listening to what I assumed were grandiose ideas for a dissertation. Without your willingness to share your breadth of knowledge and resources, this dissertation does not happen. Thank you for your honest and genuine feedback and suggestions during this process. Your work in concussions is inspiring and I’m grateful to play a small part in improving recovery and rehabilitation for athletes. Thank you. Dr. Etzel is the source of big picture thinking. Thank you for reminding my why the work we do is important and how small gestures can make a huge difference. From sending articles about concussions or baseball to allowing me to sit in your office in the comfy blue chairs when I needed a minute to myself, thank you for showing me what reaching out looks like. Thank you. I’m grateful to Dr. Damien Clement for agreeing to be involved in this project even after the self proclamation, “I don’t mess with concussions.” Thank you for being a stable voice among the instability that has been this project. You provided information in an area I knew very little about and did so with patience. Thank you. To all the help along the way: thank you Trevor Jones, Danielle Funk, Adam Hansell, Brandon Lucke-Wold, Cindy Holland, Valerie Reeves, Jake Manumalo, Alison Pope-Rhodius, and rest the staff, faculty, and students at John F. Kennedy University. When you join a PhD program, you join a family. At WVU, we have a great one. Thank you to all the SPAFers who came before me, who experienced it with me, and who will come after me. Ashley, Chelsea, Pete, and Jesse; thank you for always answering my texts and showing me the way. MegHan, Stefanee, and Tammy; thank you for being my tribe and a source of unwavering love and support. Sharing in the highs and lows along the way makes everything worth it. Thank you to all of my friends near and far, and Drew for keeping me sane during an inconceivably insane situation. Thank you to my exceptional family. Dad, Mom, Adam, Stephen, and everyone else I’m lucky to call part of me. You have provided me the opportunity to grow through and never doubted my abilities. Love you. v Table of Contents Introduction . . . . . . . . . . 01 Concussion Symptoms. . . . . . . . 04 Emotional and Behavioral Responses Following Concussion. . . 04 A New Approach: Concussion Profiles. . . . . . 08 Methods . . . . . . . . . . 09 Research Design . . . . . . . . 09 Participants . . . . . . . . . 10 Instrumentation. . . . . . . . . 12 Procedure . . . . . . . . . 15 Data Analysis: Quantitative Phase. . . . . . . 16 Data Analysis: Qualitative Phase. . . . . . . 17 Results . . . . . . . . . . 18 Quantitative Phase . . . . . . . . 18 Qualitative Phase . . . . . . . . 23 Discussion . . . . . . . . . . 33 Conclusion . . . . . . . . . 53 References . . . . . . . . . . 54 Appendix A – Extended Literature Review . . . . . . 72 Appendix B – Tables and Figures . . . . . . . 148 Appendix C – Consent Form . . . . . . . 150 Appendix D – Assessments . . . . . . . 153 Appendix E – Interview Guide . . . . . . 160 vi List of Tables and Figures Figure 1 – Using Concussions Clinical Trajectories .. . . Table 1 – Athlete Pseudonyms and Demographics Phase 3 Participants. Table 2- Mean Differences on Paried Samples T-Test Table 3- Descriptive Data Time Point 1 and 2. . . . Table 4 – Bivariate Correlations of Significant Symptoms . . Table 5- Demographics for Phase 1 and 2 Participants . . . . . . . . . . 66 . . . . . 67 67 68 69 72 1 Introduction In the 10-year period from 2000 to 2010, emergency room visits for sports- and recreation-related head injuries among adults and adolescents have increased by 60% (Centers for Disease Control, 2010). In sport, incidence rates per athletic exposure (number of practices and competitions in which an individual actively participates) of all high school sports is 4.9 per 10,000 athletic exposures and collegiate sports is 3.4 per 10,000 athletic exposures (Gessel et al., 2007; Hootman, Dick, & Agel, 2007; Lincoln et al., 2011). A concussion, as defined in the Zurich consensus statement, is a pathophysiological process resulting in functional neurological impairments, as a consequence of forceful biomechanical impacts directly on or transmitted to the head, neck, or face (McCroy et al., 2013). In a retrospective study of 328 collegiate football and soccer players using self-reported symptoms of concussion, Delaney and colleagues (2002) found that 62.7% of soccer players and 70.4% of football players experienced symptoms of a concussion during their previous athletic season. Headache was the most commonly experienced symptom (71%) followed by confusion and disorientation (56%). A history of concussions have been shown to be a significant risk factor for repeat concussions (McCrory et al., 2013) and other neurological conditions, including early-onset Alzheimer’s disease (Graves et al., 1990; Rasmusson, Brandt, Martin, & Folstein, 1995), chronic depression (Holsinger et al., 2002), epilepsy (Langlois, Rultand-Brown, & Wald, 2006) and chronic traumatic encephalopathy (CTE; McCrory, Zazryn, & Cameron, 2007; Omalu et al., 2005). Unfortunately, stories of athletes who have taken their lives are becoming increasingly more common. Many of these athletes who have taken their lives have shown signs of brain injury sustained from concussions in post-mortem brain scans in the form of CTE, a degenerative 2 disease typically caused by multiple hits to the head. CTE can only be diagnosed after death, but patients with CTE often display symptoms such as impulsivity, forgetfulness, depression, and sometimes suicidal ideation (Omalu et al., 2005). While the link between CTE and sport concussion is still being investigated and there are conflicting views on the relationship, it is clear that athletes are experiencing emotional symptoms following concussion. For example, qualitative studies with former professional hockey players detailed suicidal ideations in those who sustained repeated concussions during their career (Caron, Bloom, Johnston, & Sabiston, 2013; Gulli, 2011). In 2014, 22-year-old Kosta Karageorge, an Ohio State football player, and former collegiate wrestler, was found dead from a self-inflicted gunshot wound. He sustained numerous concussions throughout his playing career and in a text to his mother prior to his death Kosta referenced his concussions saying they had his head “all messed up” (Thamel, 2014). While the link between CTE and sport concussion is still being investigated, and there are conflicting views on the relationship, tragedies such as this can be prevented with proper medical attention following concussion. Concussions are a type of traumatic brain injury (TBI) and while the phrases “concussion” and “mild TBI” are often used interchangeably this paper will use the term concussion as a subset of TBI. Concussions may occur from a direct hit to the head, face, neck or elsewhere that results in a force to the head. Rapid functional neurological impairments are often a consequence of concussion that may be short-lived or protracted. Concussion severity ranges from “mild” (i.e., a brief change in mental status or consciousness) to “severe” (i.e., an extended period of unconsciousness or memory loss after the injury), however all brain injuries are serious and may occur without loss of consciousness. 3 Due to the nature and the mechanism of concussion, combined with the physical and psychological symptoms, athletes may be more vulnerable to negative mood states such as depression, isolation, and anxiety, as compared to athletes suffering from musculoskeletal injuries (Chen, Johnston, Petfies, & Pitio, 2008; Hutchison et al., 2009). Therefore, the emotional sequelae following concussion is an area for continued research as a preventative measure against suicide and other mental health issues. By better understanding the manifestation of symptoms following concussion, more specific individualized treatment plans can be developed to aid athletes in their recovery and future health. Collegiate and professional leagues have reformed rules regarding legality of plays, equipment, and return to play protocols to enhance athlete safety. However, even with better detection and stricter rules it has been estimated that as high as 50% of concussions go undiagnosed (McCrea et al., 2004) due to athletes’ unwillingness to report symptoms, and delayed symptom onset (Beckwith et al., 2013; Delaney et al., 2002; Duhaime, et al., 2012). These incident rates do not account for subconcussive impacts, which are characterized as hits to the head that do not cause a concussion to occur, but repeated exposure has been found to be as detrimental as concussions (McKee et al., 2009). Following concussion, and during symptom recovery, an athlete is more susceptible to future head injury, so return to play decisions should be made carefully and with proper testing and screening (Baugh, 2014; McCrory et al., 2013). The American Academy of Neurology has recommended the use of neurological assessment to measure severity and assess treatment, specifically return to play guidelines (Giza et al., 2013). Neuropsychological assessments, such as the Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT 2.0; Lovell, 4 Collins, Podell, Powell, & Maroon, 2000), test memory function, reaction time, and speed of cognitive processing. Concussion Symptoms Signs and symptoms following concussion are often characterized into four discrete system clusters: somatic, cognitive, emotional, and sleep-related (Pardini et al., 2004). In 80% of athletes, these symptoms typically resolve in less than three weeks (Iverson, Brooks, Collins, & Lovell, 2006) with 20% of athletes experiencing lingering symptoms. Little is known about how a concussion changes the brain on either a structural or a neurochemical level (Henry, Tremblay, Boulanger, Ellemberg, & Lassonde, 2010) and so it is difficult to determine if athletes’ psychological symptoms are purely emotional, or if they are caused by change within the brain. This unknown factor can lead to difficulties in studying athletes with concussions, specifically the cluster of emotional responses. There is research to suggest that neurobiological and pathophysiological changes associated with brain injury, regardless of severity level, may be directly related to the onset of psychological symptoms (Chen et al., 2008; Hudak et al., 2011; Reger et al., 2012). Concussions and head injuries often damage the prefrontal cortex, ventral frontal lobe and the anterior temporal lobe, which are implicated in recognizing, regulating, and reacting to emotionally relevant stimuli (Etkin, 2010; Etkin, 2012; Kennedy et al., 2007). Emotional and Behavioral Responses Following Concussion There is substantial research documenting the emotional and behavioral responses following injury that include depression, tension, anger, anxiety, frustration, and boredom (e.g., Brewer, Van Raalte, & Linder, 1991; Leddy, Lambert, & Ogles, 1994). With the combination of physical and psychological symptoms of concussions, athletes who sustain concussions may 5 experience different emotional responses to injury compared to athletes who have sustained musculoskeletal injuries (Hutchison et al., 2009). Furthermore, concussions have no outward visibility, so concussed athletes may present different responses during rehabilitation and recovery than an athlete who has a visible injury with specific physical limitations. The most frequently cited and studied emotional symptom following concussion is depression (Guskiewicz et al., 2007; Rutherford, 1977). Given the high degree of comorbidity between depression and anxiety (Stavrakaki & Vargo, 1986) and non-concussed injured athletes’ endorsement of anxiety during the rehabilitation process (e.g., Mainwaring et al., 2010; Tracey, 2003) athletes with concussion may be prone to both anxiety and depression after injury. General anxiety disorder (GAD) in persons following a TBI has been reported at rates that are double those found in the general population (Hiott & Labbate, 2002). A retired professional hockey player once described his experience with anxiety following a concussion as, “Anxiety. Absolutely. That year was the worst I’ve ever felt…use the comparison of having your foot on a gas pedal and everything is going too fast. Everything was going too fast for me” (Caron, Bloom, Johnston, & Sabiston, 2013, p. 172). In a prospective cohort study by Yang, Peek-Asa, Covassin, & Tomer (2015), the authors found that among 67 male and female Division I collegiate athletes who sustained a concussion within the 2007-2008 to 2011-2012 seasons, one-fifth of concussed athletes (n = 14, 19.8%) reported experiencing symptoms of depression, and one-third of concussed athletes (n = 24; 33.8%) reported symptoms of anxiety. Post-concussion symptoms of depression significantly co occurred with post-concussion state anxiety (OR = 8.35; 95% CI = 2.09, 33.34). Similarly, Bailey et al. (2010) found that in 47 concussed college football players, 13% of the athletes had 6 elevated anxiety levels as compared to their baseline scores. Additionally, 4% of the athletes had clinically significant levels of anxiety compared to their baseline scores and met the diagnostic criteria for an anxiety disorder. These studies demonstrate that athletes do experience feelings of anxiety following concussion and the findings should be replicated to further understand when in the recovery process athletes feel anxious and how long the feelings linger. Athletes with head injury history who have taken their lives may have done so due to depressive feelings they cannot seem to overcome, although another reason may be due to increased impulsive behavior while feeling anxious or depressed. Impulsivity is a construct that encompasses a multitude of behaviors or responses that frequently result in unwanted or damaging outcomes (Daruna & Barnes, 1993). Impulsivity is a common consequence following head injury (Rochat, Ammann, Mayer, Annoni, & van der Liden, 2009; Starkstein & Robinson, 1997), and is also related to difficulties with emotional regulation, such as irritability and poor temper control (Cattran, Oddy, & Wood, 2011). The prefrontal cortex, a commonly injured region, plays an important role in emotional and behavioral regulation, as well as social awareness. Grafman and colleagues (1996) suggested that the inability to control one’s behavior may result from a loss of frontal lobe inhibition due to damage to the subcortical limbic structures in the brain that are involved in the facilitation of aggression and impulses to act. In athletes, these impulses may lead to risk-taking behaviors after concussion. Research shows that male athletes are more likely to engage in risk-taking behaviors, such as substance abuse, alcohol use, and injurious behavior, than males who are non-athletes (Kokoatlio, Henry, Koscik, Fleming, & Landry, 1996). Thus, impulse control problems and poor emotion regulation after concussion could put athletes at greater risk for additional problems such as re-injury (i.e., 7 returning to sport too soon), self-injury (i.e., suicidal ideation), or dysfunctional behaviors outside of sport. This risk may be greater given the prevalence of irritability following concussion. Eames and Wood (2003) have described a cluster of symptoms characterized by intermittent states of altered affect or behavior called temporolimbic disorders in patients with TBI. They have noted that the change in often sudden, unpredictable, and typically “out of character” for that individual. This type of behavior has been termed an intermittent form of anger following head trauma, and that is closely related to impulse control disorders. Anger has been recognized as a prevalent emotion in sport (Brunelle, Janelle, & Tennant, 1999) and has been endorsed by athletes following sports injury (e.g., Brewer et al., 1991; Leddy et al., 1994). There are theories as to why anger is experienced after sport injury, many centered on frustration that accompanies sport injury. Compared to athletes with musculoskeletal injuries, athletes with concussions have higher reported levels of anger one and two weeks post injury (Hutchison et al., 2009), but this research is limited because it did not follow athletes through return to play. Research has yet to determine if the change in anger was due to removal from play or the concussion itself. Using the State-Trait Anger Expression Inventory-2 (STAXI-2; Spielberger, 1999), Bailie and colleagues (2015) examined the impact of TBI on the experience and expression of anger in a military population. Compared to participants without history of TBI, participants with TBI were four times more likely to have three or more atypical STAXI-2 scale scores than the control group, with the largest difference on the state anger scale (η2 = 0.10). This effect indicates that TBI does 8 have a moderate influence on a person’s anger levels, but these findings have not been replicated in an athlete population. As a way to illustrate the differences in emotions between athletes with concussion and other injuries, Mainwaring (2008) presented the concussion crevice profile using data the short form Profile of Mood States Assessment (Morgan, 1980). It was found that athletes with concussion had elevated levels of fatigue, low vigor, elevated depression, and confusion scores. Likewise, as compared to athletes with other types of injury (Hutchison et al., 2009) and non injured athletes (Mainwaring et al., 2004) concussed athletes had greater mood disturbance, decreased energy, and increased levels of fatigue and confusion. Based on their research of the emotional sequelae of concussion, Mainwaring and colleagues (2012) have advocated for more comprehensive concussion management approaches that include the assessment and management for emotional symptoms. A New Approach: Concussion Profiles As a way for research to unite practice and inform rehabilitation programs, Collins, Kontos, Reynolds, Murawski, and Fu (2014) have developed a conceptual approach to developing clinical profiles to inform the treatment of sport-related concussion (Figure 1). The model suggests using assessment information including a clinical interview and neuropsychological data from athletes to gauge the trajectory of the concussion and to inform the treatment plan. Based on empirical data and clinical experience, the model postulates that symptoms are indicative of the treatment and rehabilitation pathway that would be most beneficial to an athlete’s recovery. For instance, if an athlete presents with cognitive symptoms such as confusion and emotional symptoms, such as sadness, the athlete would likely be on the 9 mood and anxiety profile. To determine the concussion profile, athletes would be assessed within the first seven days of injury when they experience the highest manifestation of symptoms, then reassessed one to two weeks later. If clinicians can better gauge the trajectory the concussion may take, the rehabilitation and treatment can be geared toward those specific symptoms. Based on the existing literature on the emotional sequelae of concussions, particularly the gaps in understanding of athletes’ experiences over time, the purpose of this study was to explore the relationship between sport concussions and impulsivity, anger, and anxiety in collegiate athletes. The study also seeks to determine if there is a subset of athletes who are more likely to exhibit certain emotions based on pre-existing risk factors, or the manner in which the concussion was sustained. The study’s repeated measures, multi-method design with multiple dependent variables will allow the researcher to track emotional responses over time in an athlete population. Research Design Methods A multi-method, longitudinal design was used to explore the emotional sequelae post concussion in collegiate athletes. The study was sequential in nature as first the participants were given the quantitative assessments, which informed the follow-up interviews. The study was conducted over three time points: (a) 1 to 10 days post-diagnosis, (b) 11 to 21 days post concussion, and (c) 30 days post-concussion. Time points “a” and “b” reflected the quantitative portion of the study and the qualitative interviews took place 30 days post-concussion. In additional to demographic and injury-related items, the participants filled out measures of concussion symptoms, anxiety, anger, and impulsiveness. 10 The benefit of conducting a multi-method study is the opportunity to follow up on quantitative scores, or capture differences that are not represented by the measures (Greene & McClintock, 1985). Furthermore, researchers (e.g., Brewer, 1993; Johnston & Carroll, 1998; Udry et al., 1997) have recommended the need for using qualitative methods early in the injury process and collecting several data points in injury recovery. The data from both sources was used in combination to create a more holistic and detailed description of the experiences of the participants. The data was not combined for analysis, but to aid in making sense of both sets of data. As Denzin and Lincoln (2000) stated, triangulation in this perspective, “is best understood as a strategy that adds rigor, breadth, complexity, richness, and depth to any inquiry’ (p. 5). By simultaneously tracking multiple emotions in one study over time, this study improves upon previous research designs regarding the emotional sequelae of concussions. Participants Participants were recruited through multiple NCAA institutions, a sports medicine center and snowball sampling. Thirty-seven athletes were recruited during the course of two years to participate. Of those 37, a total of 30 collegiate athletes completed the quantitative surveys (81% response rate) 1 to 10 days post-concussion and 12 of 30 athletes completed surveys (40% response rate) 11-21 days post-concussion. Ten of 12 volunteered to complete the qualitative portion of the study 30 days post-concussion (83% response rate). There are two potential reasons as to why the response rate of athletes declined between 1 to days post-concussion and 11 to 21 days post-concussion. First, athletes may have been cleared to play and no longer experiencing concussion symptoms, thus no longer interested in completing a survey on their concussion symptoms. Secondly, participation in all three phases of this study were time 11 consuming and athletes were not compensated for their time. Demographics for athletes who completed Phase 1 or Phase 2, including scores on the Post-Concussion Symptom Scale, can be found in Table 5. Athletes met the inclusion criteria if they were at least 18 years of age and diagnosed with a sport-related concussion by a medical professional. According to the National Collegiate Athletic Association (NCAA) concussion policy (NCAA, 2013) the concussion must be diagnosed by a “physician or physician’s designee.” Concussion diagnosis was based on the following criteria: (1) observed or reported acceleration/deceleration of the head (2) any observable alteration in mental status; and/or (3) observable signs such as confusion, vacant stare, poor coordination, difficulty concentrating, poor balance; and/or (4) any self-reported symptoms such as headache, loss of consciousness, nausea, balance problems, or difficulty reading or concentrating. Participants were male (n = 23) and female (n = 7) collegiate athletes from soccer (n = 3), volleyball (n = 2), football (n = 22), lacrosse (n = 1), diving (n=1), and basketball (n = 1) who sustained a sport-related concussion during the fall 2015 through fall 2016 athletic seasons. Athletes ranged in year in school from freshman to graduate student, with the highest number of participants in their senior year (n = 19). The mean age of participants was 20.47 (SD = 2.01). One fifth (n = 6) of athletes had been diagnosed with more than one concussion during the year. The range of number of concussions sustained during their collegiate careers thus far was 1 to 4, with a mean of 1.6 (SD = .95). Slightly more than half (n =16) of athletes reported self or others noticing a difference in their behavior or mood since sustaining a concussion. Four athletes disclosed being previously diagnosed with a mental illness. Two athletes indicated they had been previously diagnosed with anxiety, one athlete reported having a learning disability, and the 12 fourth athlete did not disclose their mental illness. Only 1 athlete who completed all three phases of the study disclosed previously having a mental illness (anxiety). De Demographic data for the 10 athletes who participated in all three data collections periods differed slightly from the athletes who participated in solely the quantitative portion. Participants mean years of age was similar (M = 20.10, SD = 2.92) to the larger sample. Athletes were male (n = 4) and female (n = 6) collegiate athletes from football (n = 4), soccer (n = 2), volleyball (n = 2), lacrosse (n = 1), and basketball (n =1). The biggest difference in the samples were the number of concussions in their college careers (M = 2.3, SD = 1.16) and 80% of the athletes reported self or others noticing a difference in mood or behavior since their concussion, and one athlete reported having previously been diagnosed with a mental illness (anxiety disorder). The athletes’ pseudonyms and demographics, including scores on the Post-Concussion Symptom Checklist can be found in Table 1. Instrumentation During time periods 1 (1–10 days post-concussion) and 2 (11-21 days post-concussion), athletes were given the following quantitative assessments to assess reported levels of anxiety, anger, and impulse during their recovery period. (1) Demographic questionnaire (time point 1 only) assessing athletic sport history, age, sport type, concussion history, how the concussion occurred, and mental health history. (2) Post-concussion Symptom Scale. Concussion symptoms were measured using the Post-Concussion Symptom Scale (PCSS; Lovell & Collins, 1998) of the Immediate Post Concussion Assessment and Cognitive Test (ImPACT Version 2.0; Lovell, Collins, Podell, Powell, & Maroon, 2000). It is a 21-symptom checklist to document and track concussion 13 symptoms on a 7-point Likert scale (0 = no experience of a symptom to 6 = severe symptom). The items on the scale were developed to represent player report symptoms as opposed to medical verbiage (i.e., feeling “slow”). Iverson, Lovell, and Collins (2003) found evidence of moderate test-retest reliability (r = .65) and pre-to post-season intraclass correlation (r = .55). Internal consistency reliability on the PCSS in samples of non-concussed high school and college students has ranged from .88 to .94 (Lovell et al., 2006). In high school and college athletes with concussions, Cronbach alphas for men and women were .93 and .92, respectively (Lovell et al., 2006). Symptoms are classified into five categories based on normative data for healthy men and women and categorized by severity (low-normal, broadly normal, borderline, very high, and extremely high). (3) Barratt Impulsiveness Scale-version II. Impulsivity was measured using the Barratt Impulsiveness Scale–II (BIS-II; Patton, Stanford, & Barratt, 1995). The original scale was developed to relate impulsiveness, along with anxiety, to psychomotor efficiency (Barratt, 1959). Through several factor analytic studies (e.g., Barratt, 1965; Barratt, 1985) it was concluded that impulsiveness was not unidimensional and three sub-trait factors were identified, motor impulsiveness, non-planning, and attentional impulsiveness. However, the majority of studies using this scale have reported only the total score, ignoring both the first-and second-factor subscales (Stanford et al., 2009). The scale has 30 questions that are ranked on a 4-point Likert scale (1 = rarely/never to 4 = almost always/always), with 4 indicating the most impulsive response. The higher the summed score for all items, the higher level of impulsiveness. Example items from the questionnaire are “I plan tasks carefully; I say things without thinking; I am restless at lectures or talks.” This 14 questionnaire has shown good internal consistency in college undergraduates (α = .84, Hatfield & Dula, 2014) and test-retest reliability (Stanford, et al., 2009). Total score means for men and women in an adult sample (N = 1577; n = 1178 college students) are 62.8 (SD = 9.2) for men, and 62.1 (SD = 10.6) for women. Previous studies (e.g., Patton et al., 1995) have used a BIS-11 score of one standard deviation above the mean to designate high impulsiveness. (4) State-Trait Anger Inventory-2. Perceptions of anger were assessed using the State Trait Anger Inventory (STAXI-2; Spielberger, 1999). The inventory consists of six major scales and five subscales measuring the experience, expression, and control of anger. The STAXI-2 is comprised of 57-items measured on a 4-point Likert type scale (1 = not at all/almost never, 4 = very much so/almost always). For the purpose of this study, only the State-Anger subscale will be used. State-Anger (S-Anger; 15 items) refers to an emotional state consisting of subjective feelings that vary in intensity from mild annoyance to intense fury, accompanied by muscular tension and arousal of the automatic nervous system. This subscale was chosen for two reasons. First trait anger, as a personality measure, would not likely be effected in a short period of time. Second, research by Bailie et al. (2015) found the largest statistically significant effect on the State Anger subscale when comparing military personnel who had a history of at least one TBI as compared to a control group of persons with no TBI history (η2 = 0.10). Internal consistency reliability has a Cronbach alpha value ranging from .73 to .95 for the total scale and .91 for the S-Anger subscale (Spielberger, 1999). (5) Generalized Anxiety Disorder 7-item. Anxiety was assessed on the generalized anxiety disorder 7-item screening measure (GAD-7; Spitzer, Kroenke, Williams, & Lowe, 2006). It has 7 items answered on a 4-point Likert Scale (0 = not at all sure; 3 = nearly every day). The 15 GAD-7 is a clinical anxiety assessment, with a score above 10 indicating a probable diagnosis of anxiety, and a score above 15 indicating severe anxiety. This measure was developed based on the anxiety disorder diagnosing criteria in the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV). In the construction of the assessment, patients who were diagnosed with GAD had a mean score of 14.8 (M = 14.8; SD = 4.7), compared to a mean score of 4.9 (M = 4.9; SD = 4.8) of people without GAD. Participants are prompted with “Over the last 2 weeks, how often have you been bothered by the following problems?” Example problems are “feeling nervous, anxious, or on edge” and “trouble relaxing.” Internal consistency was reported as Cronbach alpha α = .92, and test-retest reliability has shown good intraclass correlation of .83. This measure was chosen because it is brief and can be used as a screening tool for athletes. All participants were provided with information to counseling services, in addition athletes who scored above 10 on this measure were followed up with by the PI and encouraged to seek counseling services. Procedure Institutional Review Board approval was obtained at two institutions, a large Mid Atlantic Division I university and a Regional Medical Center. Participants were recruited for voluntary participation via team doctors, head athletic trainers, or through snowball sampling from other participants. Once recruited, athletes gave informed consent via signature or online acceptance prior to taking part in the study (Appendix C). All athletes were assigned a code number and identifier kept separately from the data to protect confidentiality. Athletes completed the surveys in-person or using Qualtrics online software. All data was stored in a password 16 protected computer inside a locked office and on a secure online database (Qualtrics Research Suite, 2014). After athletes completed the questionnaires at time point 2, an interview time was scheduled. At time point 3, the athletes participated in a semi-structured interview with the head researcher via synchronous computer-mediated interviewing on Skype (n = 1), face-to-face (n = 1), or telephone (n = 8). The purpose of the interviews were to capture the athletes’ experiences with their emotional changes that could not be assessed via the quantitative measures. Semi structured interviews were used to provide participants “flexibility to express their opinions, ideas, feelings, and attitudes” (Smith & Sparkes, 2016, p. 103). The majority of interviews lasted approximately 35-40 minutes, were audio recorded and then transcribed verbatim. The interview modality was chosen by the participant depending on travel and their convenience. Non-verbal communication from the two athletes who participated in the Skype and face-to-face interviews were noted. Although phone interviews can lose the physical information provided by face-to face interviews, Hanna (2012) argues that telephone interviews provide safety for participants that may lead to the disclosure of sensitive information they might be hesitant to share in face-to face interviews. The interview guide asked athletes to explain their experiences with the emotional impacts of concussion, by prompting them with their survey scores (e.g., “You scored X on the anxiety measure. Can you tell me more about the anxiety you were feeling regarding your sport concussion?; Where do you think these emotional changes come from?”). Data Analysis: Quantitative Phase Descriptive statistics. Descriptive statistics were used to determine the characteristics of the sample based on (a) gender; (b) age; (c) sport (e) concussion (g) range of scores on 17 instruments, including means, medians, modes, and standard deviation per item and overall scores at 1 to 10 days post-concussion and 11 to 21 days post-concussion. Descriptive data for each time point can be found in Table 3. Inferential Statistics. Three, one way repeated measures ANOVAs were calculated used to answer the first research question: “Do athletes’ measured levels of impulsivity, anger, and anxiety change after sustaining a concussion during their sport season?” It was hypothesized that the athletes will score highest out of the three time points on impulsivity, anger, and anxiety after an athlete has been cleared to play. To determine if there is a subset of athletes who are more likely to exhibit certain emotions based on pre-existing risk factors, Pearson correlation coefficients were calculated to show the bivariate relationship between each of the symptoms assessed (i.e., headache, dizziness, fatigue, balance problems, sadness, nervousness) and emotional responses (i.e., anger, anxiety, and impulsiveness). Data Analysis: Qualitative Phase Qualitative data was analyzed using thematic analysis (Grbich, 1999; Braun & Clarke, 2006). Thematic analysis allows for patterns to emerge and be described across an entire data set (Braun, Clarke, & Weate, 2016). First, the researcher familiarized self with the qualitative data by transcribing or reviewing the transcriptions of the interview and then generated initial codes throughout the data set. Initial codes were generated using abductive coding to establish three higher themes based on pre-determined dependent variables of (1) anxiety, (2) anger, and (3) impulsivity. Next, themes were searched for and organized in lower order themes that were coded using InVivo Coding (Strauss, 1987). This type of coding is used to ensure that themes 18 and concepts are as representative of the participants’ words as possible. Themes were then reviewed in relation to the dataset and checked for examples that did not fit within the themes. The code of impulsivity required extensive example checking as the athletes talked about a range of items within this topic. Lastly, themes were refined and links between the themes were created. Reliability of the interviews was established by audio-recording all interviews and transcribing the interviews verbatim. Additionally, quotes have been presented in length with the question that prompted the response included where applicable. Data trustworthiness was established through using specific questions to capture significant experiences related to concussion (Denzin & Lincoln, 2015). Another way to ensure the trustworthiness of findings is through methodological integrity (Levitt, Motulsky, Wertz, Morrow, & Ponterotto, 2017). Levitt and colleagues (2017) describe methodological integrity as a context-driven approach where the research design and procedures support the research goals. As the purpose of this study was to understand how athletes experience emotional effects after concussion, using a sequential design of quantitative assessments to influence qualitative interviews fits this approach. Results Quantitative Phase Descriptive Data. Assessment means were higher during 1 to 10 days post-concussion than 11 to 21 days post-concussion, with the exception of the BIS-II. The athletes mean score on the STAXI-2 was 22.9 (SD = 10). The mean on the STAXI-2 decreased to 19.33 (SD = 6.7) 11 to 21 days post-concussion. The mean score on the BIS-II 1 to 10 days post-concussion was 66.53 (SD = 10.8) and 67.5 (SD = 10) 11 to 21 days post-concussion. On the GAD-7, the mean score 19 was 7.4 (SD = 5.6) 1 to 10 days post-concussion and decreased to 6.25 (SD = 6.6). Eleven athletes scored above a 10 on the GAD-7 1 to 10 days post-concussion, indicating a probable diagnosis of anxiety. Athletes scored a mean of 47.7 (SD = 30.2) on the PCSS 1 to 10 days post concussion and substantially lower 11 to 21 days post-concussion with a mean of 16.0 (SD = 16.3). By gender, women average symptoms were 45.14 (SD = 35) and men scored an average of 16.3 (SD = 19.6) at 1 to 10 days post-concussion. At 11 to 21 days post-concussion, women had an average of 16.3 (SD = 19.6) and men had an average of 15.2 (SD = 15.9). Mean scores and standard deviations for all variables can be found in Table 3. Effect of Time on Outcome Measures. Mean differences in scores on the assessments were only significant on the Post-Concussion Symptom Checklist (PCSS). On the PCSS, athletes selected significantly more concussion symptoms (M = 53.7, SE = 8.26) t(11) = 5.55 p < .05, r= .83 1 to 10 days post-concussion that 11 to 21 days post-concussion. The range of scores 1 to 10 days post-concussion was 1 to 92 (M = 47, SD = 30.1), and the range of scores 11 to 21 days post-concussion was 0 to 42 (M = 16, SD = 16.3). At 1 to 10 days post-concussion, headache was the symptom selected the most often (n = 28) and with the highest intensity (M = 3.2, SD = 1.8). The next most frequently endorsed symptoms were fatigue (n = 23), feeling fogging (n = 23), and difficulty remembering (n = 23) and irritability (n = 21). At 11 to 21 days post-concussion, fatigue (M = 1.3, SD = 2.2, n = 4), excessive sleep (M = 1.8, SD = 2.3, n = 5), irritability (M = 1.8, SD = 2, n = 6), feeling foggy (M = 1.3, SD = 1.8, n = 5), and difficultly concentrating (M = 1.5, SD = 2.1, n = 6), and difficulty remembering (M = 1.2, SD = 1.9, n = 4) were the only symptoms with means above 1.0. 20 When only including the 10 participants who completed all three phases, significant differences were found on the GAD-7. All participants indicated some feelings of anxiety (M = 10, SD = 3.68) 1 to 10 days post-concussion with five of the ten participants scored above a 10 on the GAD-7, a screening tool for anxiety. A score above 10 on this tool is indicates a probable diagnosis of anxiety and of those, one scored 17, indicating severe anxiety. All athletes who scored above a 10 were referred to counseling services. AT 11 to 21 days post-concussion athletes scored an average of 5.5 (SD = 5.7). Athletes endorsed significantly higher feelings of anxiety (M = .2, SD = 3.12) t(9) = 2.32, p < .05, , r = .57 during 1 to 10 days than 11 to 21 days post-concussion. Nine of 10 athletes scored lower at the second point (M = 5.5, SD = 5.68), with the exception being the athlete who indicated previously being diagnosed with an anxiety disorder. Mean differences between 1 to 10 days and 11-21 days post-concussion on the anger and impulsivity measures were not significant with all participants who completed both quantitative phases (n = 12) or with the athletes who completed all three phases (n = 10). All mean differences can be found in Table 3. Correlational Analyses. To determine if there was a relationship between reported symptoms, concussion history, and scores on the three assessments, several point-biserial and bivariate correlations were conducted. Point-biserial correlations were conducted on the dichotomous variables where a response of no was equal to zero, and yes was equal to 1. There was a significant relationship between the variable “Have you or others noticed a difference in your behavior or mood since sustaining a concussion?” and the variable “How many concussions have you been diagnosed with in your college career?”, rpb (28) = .52, (all p<.05. The 21 concussion history variable “Have you been diagnosed with more than one concussion during this year?” was positively correlated with scores on the BIS-II during 11 to 21 days post concussion, rpb (10) = .66 The only other demographic variable with significant correlations was “Have friends or family noticed a difference in your mood or behavior since sustaining a concussion.” This variable was negatively correlated with scores on the STAXI-2 1 to 10 days post-concussion, r pb (28)= -.46 and negatively correlated with scores on the GAD-7 during 1 to 10 days post concussion rpb (28)= -.42. Bivariate correlations supported a significant relationship (all p<.05) between scores on the PCSS and scores on the STAXI-2 r (28) = .72, and GAD-7 r(28) = 64 at 1 to 10 days post concussion. At the 11-21 days post-concussion, scores on the PCSS were significantly correlated to scores on the GAD-7, r (10) = .72. Symptom scores on the PCSS were not correlated with the BIS-II at either time point. To determine which symptoms on the PCSS were related to scores on the GAD-7 and the STAXI-2, follow up analyses were conducted. All significant correlation coefficients are reported in Table 4. The highest correlated symptom with the STAXI-2 was balance problems, r (28) = .7, and loss of sleep, r. = .76. At 1 to 10 days post=concussion, the highest correlated symptoms with the GAD-7 were feeling “foggy,” r (28) = .63 and balance problems, r (28)= .6. During 11 to 21 days post- concussion, there was a significant relationship (all p<.05) between scores on the GAD-7 and most symptoms on the PCSS and the four with the highest correlation were visual problems r (10) = .8, sadness r (10)= .76, excessive sleep r (10) = .75, and irritability, r (10)= .7. 22 Qualitative Phase Codes were developed based on a thematic analysis and an abductive approach (a combination of inductive and deductive coding). The semi-structured interview guide was influenced by the quantitative results, such as asking about their reported concussion history and athletes were provided scores on the quantitative assessments when applicable (i.e. “You scored x on this anxiety measure, which decreased between time points”). Theme 1: Anxiety “The unknown.” A theme emerged around the notion that each athlete was experiencing something unique and different from other athletes and how many facets of concussions are still unknown. They talked about how they tried to make sense of their anxious feelings surrounding the unknown factors of being able to complete school work, their recovery, and most concerning was not being able to regulate their own emotions. Snow White talked extensively about feeling alone and wondering how other athletes felt after their concussions, “Was I different? Did everyone else feel this weird? Why couldn’t I stop crying and just…chill out.” Ariel had a similar experience and discussed being alone on campus as her concussion occurred shortly before holiday break and also wondering how others with similar injuries dealt with their feelings: Knowing how other people can relate is always helpful because um, like now it’s winter break at (school) and only the basketball teams and uh hockey teams are here…I’m always alone it feels like and sometimes I have those nights where I just feel I don’t want to say almost depressed, but almost lonely and emotional and like, why is this going on? So it would be nice to have an outlet to go to someone and be like hey, have you had this 23 feeling before? I don’t know how to get out of this, can you suggest anything? Do you have any recommendations or advice? Many athletes talked about the anxiety associated with not knowing when they would feel “normal” again or the severity of their injury. Belle commented on the interplay of her injury, her school work, and the process of returning to sport, “I was pretty anxious because it was also exam period and didn’t really know, um, the severity of it either, and then additional to that, you know, just the daily symptom check reminder like, ‘Oh, do I really feel better?’ or ‘Is it just the same?” you know, like trying to identify with the numbers as well as possible.” Naveen expressed his anxiety surrounding the severity of his concussion: Now when you hear concussion you think about all your friends who have trouble remembering things and the stories on ESPN or whatever on CTE. I just wanted to know when I could play again and it seemed like no one could tell me. I thought that meant I was bad off, but I guess it just meant they didn’t know. Cinderella shared, “Who’s going to say I’m not going to have headaches for the rest of my life?” Jasmine had a similar thought as Naveen and Cinderella, “One night before I went to bed I was begging my headache to go away so I could sleep. I just wanted it to go away and I was so anxious that I would have a headache for the rest of my life.” She was emotional when recalling this memory, specifically how scared she was about lingering symptoms. Like Naveen, Jasmine mentioned previous teammates and their battles with post-concussion symptoms. Belle had a comparable experience, “you’re getting anxiety in the middle of the night and it’s like, “Oh 24 my god,” and “I can’t sleep” and I have, you know, to be at training in the morning. Stuff like that, and going on just an emotional roller coaster, to say the least.” Mulan seemed to have the most difficulty understanding her spike in anxiety scores during her first 20 days of concussions recovery. For her, it led to frustration with her mental health provider as well as her athletic training staff: I am already an anxious person. I know that about myself and take medication regularly because I have anxiety. But, when I talked to my doctor he didn’t say anything about how my concussion may have made it worse. It felt way worse. Like, I remember, I remember when I filled out the survey the second time, I think, I felt really bad so that makes sense it was higher. I couldn’t concentrate on anything because I felt so anxious all day. My headaches didn’t really go away for a while so maybe that’s why I was anxious? That kinda makes me mad, why wouldn’t my doctor think to ask me about my concussion when I complained my anxiety was worse? Or maybe it was my fault for not bringing it up. In Mulan’s case, she had a pre-existing anxiety disorder that may have been exacerbated by her concussion symptoms, particularly her headaches. In terms of her medical staff, Cinderella introduced the idea of lasting impacts and her fear surrounding her length of recovery that led her to feel anxious: I was pretty concerned that I was taking a long time to recover...I was concerned that there might be something that might show up on the CT. I was concerned about going to see a neurologist. I was concerned about what the doctors would say about my head and what I’m always concerned about: doctor’s telling me I couldn’t play sports anymore but 25 I kinda make that decision for myself...I was concerned about my cognitive functioning for, for a long time like not being able to remember things, not being able to keep up in conversations, um yeah, and then that was definitely very noticeable after this last concussion and I started to notice it after the previous one as well so that was very scary for me. For some athletes this unknown factor was so intense that it resulted in the lack of sleep or other negative mental health outcomes. They expressed how having more education on both the emotional symptoms and recovery of concussion would likely help lessen the feelings of anxiety they experienced. “Fear of not being able to play again.” The second theme to emerge under anxious feeling was directly related to their sport. This was the only theme in which all ten athletes had something to discuss regarding their fears around not being able to return to their sport for the remainder of the season and two participants discussed not being able to play their sport again. Eric was a senior when he sustained two concussions, with the second one occurring eight days after he was cleared to return. He stated: After that second one there was a lot more emotion and knowing that I wasn’t sure that I’d play again like my senior year or more in terms of the concussion itself, but like definitely felt more emotional after that second one…I guess I was just clouded by that kind of thought like it was just at the end, you know. If I could have the opportunity to like do what I wanted you know and sat on the bench for a couple of years and it’s finally my turn and it’s just the fear of not being to play again. 26 Three athletes discussed their conversations with coaches and trainers about their ability to return to sport. Aladdin sustained his concussion during his sophomore year and questioned if he should red shirt his junior year in order to fully recover, but a position coach said that he would “have to fight really hard” for his spot back, so ultimately decided not to sit out. Jasmine had a different experience, and explained, “my assistant coach told me my health was more important than the season and to take a break, but I was too anxious to take off the rest of the season. I know we are bringing in a good freshman who also plays keeper and so I needed to play as soon as I could.” Mulan feared that her captain status could be taken away if she stayed out of the lineup for too long, “I knew I needed to come back, my team needed me whether my head was ready or not!” Simba talked about his realization with concussions when it impacted his playing time: I felt fine. I was ready to go, and then (athletic trainer) told me I probably wasn’t going to play. If I felt fine, but my scores on that test weren’t good enough, when was I going to get to play? It didn’t seem fair. I also didn’t think concussions were a big deal until I couldn’t play. It really just wasn’t fair that I missed two games for something I couldn’t even feel… I was worried that I would be out even longer and there wasn’t nothing I could do about it. There was a general theme surrounding losing their position but also how their health could impact their future and so the athletes were left in a place of dissonance between their recovery and their future. The unknown aspect of when they could return seemed to lead to anxiety, which often stirred feelings of anger or frustration. 27 Theme 2: Anger “Frustration towards myself and irritability towards others.” Feelings of anger were described mostly through frustration with self and others and irritability. Athletes discussed their frustrations in explaining their symptoms and recovery to peers, professors, coaches, and teammates. They felt like most of their support system generally wanted to help, but the athletes did not know how to explain how they were feeling or what help they needed. This inability to explain led to frustration and a halt to asking for help from others. Jasmine explains: My friends would ask if I was okay, but I don’t think they really understood, you know? I would say that I felt weird, cause I didn’t know how else to explain it, and they would just nod. I kinda wanted them to stop asking… I felt frustrated because I know I needed help. I would get irritated with little things, but just couldn’t explain it. So them asking to help frustrated me, and then I got frustrated with myself and how I felt. It was like, never ending. Although concussions have received more attention in the last five years in terms of medical advancements and the seriousness of the injury, some athletes still felt as if they had to justify their injury to others which led to frustration. Eric states, “I’m not like limping around and stuff and I’d say that was the hardest part, trying to get people to understand.” Cinderella had a similar experience. Her concussion happened with such force that she was left with a visible mark on her face: It was swollen a little bit and there was a little bit of um bruising but I think the next day I was kinda like happy. Kinda like showing off my war wound… once the bruising and the 28 swelling kinda went down, the way people usually view concussions kinda took over I guess like people kinda forgot cause it wasn’t visible. Belle also spoke about her frustrating encounters with teammates and other athletes who did not seem to understand her recovery, “People are like, ‘oh, you’re just babying it.’ But they’ll be like, ‘it’s been already so long,’ like, ‘you should be fine.” So I mean there was just a lot of questioning, or and a lot of, you know, and, ‘you’re just trying to get out of it,’ and so that was kind of hard to hear.” Attempting to complete school work and explain to professors that they may need extra time to for assignments and exams was another source of frustration for the athletes. Many athletes talked about the difficulty balancing their recovery with keeping up with school demands. Additionally, they spoke about the added obstacle of completing homework while experiencing symptoms such as headache, dizziness, or nausea. Cinderella stated, “I was having trouble just like reading a paragraph in a text book. I got really, like I said, angry, upset, frustrated, irritated. I got really nervous like, if I can’t do this, then like what’s going to happen to my school.” Similarly, Belle discussed her difficulties with school and how to navigate exams period, “It was more difficult because I was entering exam period, so trying to get my professors to understand the situation was frustrating.” When asked how this injury differed from other injuries sustained in sport, Simba discussed his difficulty going to class based on his restriction: [Team doctor] told me not to be in front of screens for at least 5 days. I was taking a computer class. How was I supposed to do that? (Professor) said I could miss, but I don’t think he believed me. They always think athletes are trying to get out of class for like this thing or the other. But I couldn’t sit in front of a screen. So I couldn’t do the assignment 29 and missed class. It just isn’t like that with other injuries, you know? If my leg was broke I could go to class. Some athletes had experienced injuries previously in sport that kept them out of playing or practicing with their team, but discussed how the concussion was different. It was explained that the concussion was not only different in terms of recovery, but also in how others treated them as their injuries were not visible. In the above quote Simba highlights the difference between his concussion and if he had a musculoskeletal injury. Other injuries experienced by the athletes were hip, knee, and back injuries and no athlete recalled being as frustrated or irritable with those injuries. All seven athletes who sustained more than one concussion in their college careers discussed their anger with the injury itself. This led to anger over the recovery period, not being able to play, and their future health problems. Naveen discussed his anger about sustaining his second concussion of his career: I knew as soon as stood up that I had a concussion. And all I could think was [expletive] not again. I was mad that it was happening again. I was mad that I got hit from a helmet. I was mad that he wasn’t ejected for hitting me. I was just mad. I stayed mad, too. I told [head coach] as I walked off the field, ‘it’s a concussion. I won’t be back’ and didn’t even bother with [athletic trainer]. His anger was related to the injury as well as knowing what the recovery process would look like. He appeared to be agitated as he relived the experience and thinking about what it meant moving forward. He was a sophomore, but discussed how taking time out of sport or being labeled as “concussion prone” could impact his future playing time at his position. Mulan mentioned that she “at least felt better prepared” for this concussion since she had one during her senior year of high school, but also felt like this one was worse even though the hit seemed “way 30 less severe than the last time. That was annoying, if I’m going to get a concussion at least let it happen on a big play.” Cinderella also mentioned her anger with sustaining another concussion, particularly because this was her 4th concussion. She stated, “I was just really angry that I got a concussion again…I think I was partially sad and angry about the fact that I probably won’t be playing soccer for a very long time if ever again and I mean I’ve been playing soccer my entire life.” The second part of this theme that emerged under anger was the endorsement of feeling irritable. Participants discussed being irritated by stimuli that normally would not have bothered them as well as feeling a general sense of irritability. When asked where her irritability may have stemmed from Belle said, “I think just not feeling myself because of the head injury, so, you know, waking up with a hea

Examining the Impact of a Short-Term Psychological Skills Examining the Impact of a Short-Term Psychological Skills Training Program on Dancers' Coping Skills, Pain Appraisals, and Training Program on Dancers' Coping Skills, Pain Appraisals, and InjurFollow this and additional works at: https://researchrepository.wvu.edu/etd Recommended Citation Bryant, Leigh A., "Examining the Impact of a Short-Term Psychological Skills Training Program on Dancers' Coping Skills, Pain Appraisals, and Injuries" (2017). Graduate Theses, Dissertations, and Problem Reports. 5277. https://researchrepository.wvu.edu/etd/5277 This Dissertation is protected by copyright and/or related rights. It has been brought to you by the The Research Repository @ WVU with permission from the rights-holder(s). You are free to use this Dissertation in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you must obtain permission from the rights-holder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/ or on the work itself. This Dissertation has been accepted for inclusion in WVU Graduate Theses, Dissertations, and Problem Reports collection by an authorized administrator of The Research Repository @ WVU. For more information, please contact researchrepository@mail.wvu.edu. Examining the Impact of a Short-Term Psychological Skills Training Program on Dancers’ Coping Skills, Pain Appraisals, and Injuries Leigh A. Bryant, MS, MA Dissertation submitted to the College of Physical Activity and Sport Sciences at West Virginia University in partial fulfillment of the requirements for the degree of Doctorate of Philosophy in Sport and Exercise Psychology Damien Clement, PhD, ATC, Chair Edward F. Etzel, EdD Kelly Knox, MFA Monica Leppma, PhD Sam Zizzi, EdD College of Physical Activity and Sport Sciences Morgantown, West Virginia 2017 Keywords: intervention, injury, psychological skills training, dance, pain appraisal, coping Copyright 2017 Leigh A. Bryant ABSTRACT Examining the Impact of a Short-Term Psychological Skills Training Program on Dancers’ Coping Skills, Pain Appraisals, and Injuries Leigh A. Bryant Psychological skills interventions are often conducted with individual athletes and sports teams in an effort to build mental toughness, prevent injury, or enhance performance. Dancers remain an underserved population in the delivery of sport/performance psychology services, with extremely limited literature addressing college dance students. The dance community has several inherent physical and psychosocial demands, which can promote resilience. However, dancers may also strive to meet these demands by employing unhealthy coping strategies that could be linked to maladaptive appraisals and increased injury risk. The present study examined the impact of a psychological skills intervention program on college dance students’ (N = 30) coping skills, pain appraisals, and injuries over a six-week period. A two-group pre-test/post-test quasi experimental methodology was used to capture the potential influence of the intervention program. At the end of the six-week period, there were no significant differences observed between the treatment and control groups on the three major constructs. In particular, the results demonstrated the need for a single, operational definition of injury within the dance context. A focus group discussion led to several recommendations for future research and improvements for mental skills and life skills intervention programs. Best practices for scholars, applied practitioners, and dance educators are also discussed. IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM iii ACKNOWLEDGEMENTS I would like to thank my Committee Chair, Dr. Damien Clement, for your thorough feedback and encouragement throughout the dissertation process. I would also like to thank the other members of my committee—Dr. Ed Etzel, Dr. Monica Leppma, Professor Kelly Knox, and Dr. Sam Zizzi—for the time and energy that you put into helping me complete this project. A big “thanks” to all of the faculty, staff, and students in the Sport & Exercise Psychology and Counseling programs at West Virginia University. Another big “thanks” to the dancers who took part in this study, and the instructors and administrators who supported their participation. Special thanks to Alison Coates, Jana Fogaça, Stefanee Maurice, and Anna Onderik for your interest in and contributions to this project. Finally, thank you to my parents—Neil and Jennifer Bryant—and to my husband—Kurt Skvarla—for your love and support. IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM iv TABLE OF CONTENTS Page Introduction …………………………………………………………...……………….……….. 1 Methodology ………………………………………………………………...……………......... 8 Research Design ………………………………………………………...……….……... 8 Participants ………………………………………………………...……………..…...... 8 Dance Program Characteristics and Setting ……………………………………...…….. 9 Instrumentation …………………………………………………….……………...…... 12 Basic Demographics Survey …...………………………….…………………….…...... 12 Athletic Coping Skills Inventory-28 ……………………….…………...…….….…..... 12 Pain Appraisal Inventory .……...………………………….………………....……....... 15 Injury Tracking Survey ……………………………………………………...……..….. 17 Dance Experiences Survey ……………………………………………..….………….. 18 Intervention Program …………………………………………………..…….………... 19 Adherence Journal ……………………………………………………..….………...… 21 Procedure …………………………………………………….……………..…………. 21 Data Analyses ……………………………….…………………………..…………...... 25 Results …………………………………………………….……………………..…………..... 27 Descriptive Statistics ………………………………….……………………..……...… 27 Quantitative Results ..……………………………………………………..………..…. 28 Qualitative Results ……...…………………………………………….…..…...……… 29 Exploratory Findings ….…………………………………………………..………..… 33 IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM v Discussion ……………………………………………………………………….……..……... 36 Limitations ……………………………………………………………….…….…..…. 53 Future Recommendations …………………………………………….….…...….…… 57 Implications for Practice ……………………………………………………….…..… 62 Concluding Thoughts ……………………..……………………………….……….… 66 References ……………………………………………………………………….………..….. 67 Tables ………………………………………………………………………………....……… 77 Appendices ……….………………………………………………………………….....…...... 88 Appendix A: Extended Review of Literature ….……………………………….…….. 88 Appendix B: Basic Demographics Survey ………………………………………...…138 Appendix C: Athletic Coping Skills Inventory-28 ………………………………….. 141 Appendix D: Pain Appraisal Inventory …………………………………...…..…….. 144 Appendix E: Injury Tracking Survey………………………………………….…….. 146 Appendix F: Dance Experiences Survey …………………………………....………. 149 Appendix G: Intervention Protocol Outline ……………………………...…………. 155 Appendix H: Intervention Program Exercises and Activities …………..……...…… 157 Appendix I: Adherence Journal …………………………………………………….. 167 Appendix J: Participant Contact Information Form………...………………..…...… 168 Appendix K: Semi-Structured Interview Guide for Focus Group Discussion ….….. 169 Appendix L: Stakeholder Interview Findings …………………………………..….. 170 Appendix M: Sample Self-Talk Statements and Associated Bible Verses ……..….. 173 IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 1 Introduction Dancers are considered to be both artists and athletes, given the rigor of their physical training, the necessity of self-expression, and the emphasis on the mind-body connection (Dick et al., 2013). A dancer’s body is trained to move in complex, highly-technical ways and to stand in atypical positions (e.g., on the tips of one’s toes). For this reason, dancers often have time limited careers, with very few individuals performing beyond their thirties (Kelman, 2000; Turner & Wainwright, 2003; Watson, 2013). Additionally, the path to artistic perfection is a never-ending process, because one’s performance cannot be objectively measured by a judge or audience member (Dick et al., 2013; Estanol, Shepherd, & MacDonald, 2013). Many dancers spend the entirety of their careers making technical and aesthetic improvements. They strive to maintain a slim and athletic physique, endure long rehearsal hours, and execute advanced technical requirements (Grove, Main, & Sharp, 2013; Hamilton & Robson, 2006; Shah, 2008). With no final score to use as a measure of success, dancers often need to engage in self-reflection to assess their strengths and areas for growth. As Kelman (2000) has stated, “dancers must be physically strong and have a high tolerance for pain. The performing artist’s instrument is their body” (p. 431). The mentality of “no pain, no gain” that is often used to characterize an intense sport climate may also be an appropriate description of a passionate dancer’s assessment of pain or injury (Anderson & Hanrahan, 2008). When adopted and reinforced, this “push through it” mindset can be one that is self-motivating and temporarily adaptive. Nevertheless, it is also possible that this mindset can contribute to injury risk if the pain is not properly identified and addressed (Anderson & Hanrahan, 2008; Rip, Fortin, & Vallerand, 2006). In other words, dancers who conceal or ignore physical pain in order to keep training and performing (Krasnow, 2005; Noh & Morris, 2004) IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 2 may be doing more damage to their body, and negatively influencing the environment in which they want to thrive (Anderson & Hanrahan, 2008). The physical demands and the socio-cultural climate of many schools and studios (Dick et al., 2013; Grove, Main, & Sharp, 2013) may lead dancers to a metaphorical tipping point. In some cases, dancers demonstrate resilience in the face of such pressures and engage in strategies that can enhance performance and well-being (e.g., Rivers, 2014). However, a lack of coping skills can lead to disruptions in dancers’ ambitions, or the adoption of destructive behaviors (Kelman, 2000; van Staden, Myburgh, & Poggenpoel, 2009). For instance, obsessive passion can lead to inattentiveness to pain and injury (Rip, Fortin, & Vallerand, 2006). Similarly, low levels of self-awareness about how to properly manage pain or recognize injuries that require medical attention might put dancers’ short- and long-term health at risk (Nordin-Bates et al., 2011). Therefore, it is critical to understand dancers’ appraisals of pain, how these appraisals relate to the desire to keep improving, and what factors influence dancers who engage in positive or adaptive coping strategies, such as those that might be introduced in a prevention or intervention program. As stated by Noh, Morris, and Andersen (2007), “the focus on enhancing coping skills…[may] help dancers cope more effectively with the demands of the dance environment and reduce injury incidence” (p. 28). To date, very little research has examined the delivery of psychological skills training programs to dancers (Noh, Morris, & Andersen, 2007). Historically, these programs have focused on repairing—rather than preventing—dysfunctional coping strategies, unhelpful cognitive habits, and injuries (Hays, 2002). The literature shows that in an eight-month period, up to 97% of university dance majors may experience an injury (Kerr, Krasnow, & Mainwaring, 1992). Other researchers have also reported high rates of injury, with one sample of pre-professional dancers sustaining an average IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 3 of 1.42 injuries per dancer over the course of a year (Ekegren et al., 2013). Dancers deal with both acute and chronic injuries such as ankle sprains, anterior cruciate ligament tears, tendonitis, and stress fractures (Bauman, Gallagher, & Hamilton, 1996; Dick et al., 2013). As such, they are likely to cope with injury related pain in addition to generalized pain that may stem from training and performing. Sustaining an injury may have several consequences for a dancer (Mainwaring, Krasnow, & Kerr, 2001). More specifically, being injured may necessitate taking time off from dancing, which may equate to missed opportunities to advance one’s development. Dancers who have a strong athletic identity (Brewer, Van Raalte, & Linder, 1993) and/or contingent self-worth (Hall & Hill, 2012) may experience decreases in self-esteem should they become injured or have to manage chronic pain. Moreover, for dancers who are employed or seeking employment, the inability to work can result in financial strain (Kelman, 2000; Wainwright, Williams, & Turner, 2005). Financial pressures could lead to additional stress, and possibly the need to pursue a different career. These potential consequences may serve as motivation for dancers to keep injuries hidden. Dancers may self-medicate in an effort to treat or cover-up injuries and/or pain without interfering with regular training and performances (e.g., Wozny, 2016). While researchers have noted that some dancers do inform a teacher or director that something is bothering them, they will nevertheless continue to dance (Nordin-Bates et al., 2011). Nordin-Bates and colleagues (2011) have further suggested that dancers may view rest as a form of “non-constructive passivity” that could have consequences for their fitness, technical training, and/or status, as previously described (p. 82). Therefore, although missteps or improper technique can lead to physical injury in dance, sometimes injuries may occur due to one or more psychological and/or IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 4 psychosocial factors (e.g., Noh & Morris, 2004; Noh, Morris, & Andersen, 2005; Nordin-Bates, Quested, Walker, & Redding, 2012; Smith, Ptacek, & Patterson, 2000). Coping skills, pain appraisals, and injury status may be important to a dancer’s mental well-being and performance-related outcomes. To characterize dancers’ perceived stressors, Noh, Morris, and Andersen (2002) conducted a qualitative investigation with a sample of professional ballet dancers. The researchers found that fear of injury, dance directors’ criticism, and competition for roles were prevalent. Additionally, over 60% of the dancers in their sample reported engaging in dysfunctional coping behaviors (e.g., drinking alcohol) as a means of dealing with perceived stress. Consistent with literature focused on stress and coping, researchers have identified several factors that may make individuals more susceptible to injury in a stressful situation. These factors include low levels of coping skills, high state-trait anxiety, and a history of several negative life events (e.g., Yatabe et al., 2014). Consequently, it is important for dancers, and those who work with them, to be equipped with accurate, evidence-based knowledge about healthy coping skills, adaptive pain appraisals, and injury risk. Andersen and Williams (1988) have developed and revised a model that explores the relationship between stress and injury in sport (Williams & Andersen, 1998). The model emphasizes personality, coping skills, and history of stressors as antecedents to injury risk (Andersen & Williams, 1988; Noh, Morris, & Andersen, 2005). Researchers have previously used this model with dancers to target coping skills as a protective factor for injury (e.g., Noh, Morris, & Andersen, 2007). In the present study, Williams and Andersen’s model (1998) was used as a lens through which to view the role of interventions focused on coping skills, cognitive appraisals of pain, and injury risk in a collegiate environment. In particular, the impact that intervention content may IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 5 have on cognitive appraisal was of interest to the primary researcher. While the model is often said to be linked to acute injury prediction, it was used in the present study to understand the relationship between intervention programming and cognitive appraisal of situations that could lead to or include dance-related pain and/or injury. The model also highlights the potentially meaningful role of coping skills when managing perceived stress. Thus, learning skills to identify and manage stress has implications not only for dancers’ performance-related outcomes, but also for their other life pursuits. A life skills approach to the intervention content may help dancers to better recognize the applicability of psychological skills training to their academics, social situations, and/or personal development (e.g., Danish, Petitpas, & Hale, 1993). Accordingly, the primary researcher developed and selected instruments and program content tailored to a dance population, and, more specifically, for university-level dance students. The psychological skills training program was ultimately aimed at dancers’ coping skills, appraisals of physical pain, and self-reported injuries over a six week time frame. The present study sought to contribute to the current applied research literature in the field of sport/performance psychology. Noh and Morris (2004) previously used Williams and Andersen’s (1998) model to design injury prevention programs with a sample of Korean dancers (N = 105). The authors examined the predictive power of coping skills, stress, social support, and anxiety on injury frequency and duration, further testing the veracity of the stress-injury model to the dance population. Building on this work, Noh, Morris, and Andersen (2007) published the findings of two intervention programs used with a sample of dancers (N = 35) for the purpose of injury prevention across a 24-week period. The first 12 weeks of the intervention program consisted of the delivery of coping skills content, and the subsequent 12 weeks were used to IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 6 collect follow-up data as dancers practiced these skills. Their results suggested that teaching broad-based coping skills could in fact influence the duration of dancers’ injuries. Noh and colleagues (2007) reported that dancers who were assigned to a treatment group spent less time injured than dancers who were assigned to a control group. While some research focused on coping skills and injury has been conducted within the dance population, the current literature contains few intervention programs delivered to dancers in a group context. Consequently, the present study’s methodology is rooted in literature from psychology, counseling, and family systems, which all, to some extent, utilize group sessions, cognitive-behavioral approaches, and brief interventions. Researchers have suggested that, in just a few sessions, individuals have the capacity to learn new material and make long-term behavioral changes (e.g., Bell, Skinner, & Fisher, 2009; Meichenbaum, 1993). In this way, the present study allowed dancers to learn and then apply psychological skills into their training and performances. It was hoped that these skills and strategies might positively influence dancers’ stress management and injury susceptibility, and also translate to other life pursuits such as social situations or academics. Hamilton and Robson (2006) have stated that consultants who work with performing artists have the opportunity to teach “constructive strategies that enhance performance” while helping dancers to recognize and change self-destructive behaviors or coping methods (p. 257). The constructive strategies that they discussed included diaphragmatic breathing, relaxation exercises, positive self-talk, and imagery (Hamilton & Robson, 2006). These strategies have previously been taught to non-elite and collegiate athletes across a variety of sports, including gymnastics and rowing. For instance, over the course of a competition season, Kerr and Goss (1996) conducted individualized sessions with young adult IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 7 gymnasts (N = 24) that focused on thought control, imagery, and self-talk. While no statistically significant findings were reported, the researchers found that the gymnasts who had participated in the intervention program had lower levels of negative athletic stress at the end of the season. Furthermore, Perna, Antoni, Baum, Gordon, and Schneiderman (2003) conducted a three week intervention program that focused on stress management for college rowers (N = 34). Two practitioners taught athletes assigned to a treatment group a variety of skills for performance enhancement and personal development. These skills included deep breathing, progressive muscle relaxation, and imagery. At the conclusion of the intervention program, the researchers found that athletes who had been assigned to the treatment group had fewer reported injuries and illnesses compared to the athletes who were assigned to a control group. The results of these studies, in combination with their limitations and future recommendations, suggest that interventions focused on psychological skills and life skills development can have an important impact on young adult athletes with respect to performance and overall well-being. Therefore, the purpose of the present study was to examine the impact of a short-term psychological skills training program on college dancers’ self-reported coping skills, pain appraisal, and injuries. This psychological skills training program was rooted in the stress management and performance enhancement literature, and adopted a cognitive-behavioral approach. In accordance with the study’s purpose, the four main research questions were: (1) Is there a difference in self-reported coping skills between dancers who participate in the intervention program and those who do not? (2) Is there a difference in self-reported pain appraisals between dancers who participate in the intervention program and those who do not? (3) Is the rate and severity of injuries affected by the intervention program? (4) What are the IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 8 dancers’ reactions to this intervention program, and, more specifically, what aspects of the program were useful and not useful, and why? Methodology Research Design The present study utilized a two-group pre-test/post-test quasi-experimental design (Gay & Airasian, 2003). Participants were assigned to a condition, as a group, based on the dance course in which they were enrolled for the spring 2016 semester. One class was assigned to be the treatment group; this group completed study-related instruments and received a short-term psychological skills intervention program on a weekly basis. The other class was assigned to be the control group; this group also completed study-related instruments without participating in the intervention program. This type of research design is commonly utilized in educational settings, where purely random assignment of participants to groups is not feasible or practical (Gay & Airasian, 2003). The treatment group participants were currently enrolled in a modern dance course, and the control group participants were currently taking a dance conditioning course. These classes were part of the dance program curriculum and led by full-time faculty members at the institution. Participants Participants were male (n = 4) and female (n = 26) dance students (N = 30) studying at the same institution in the Mid-Atlantic region of the United States. Students were encouraged to participate by their instructors, but ultimately the decision to participate was their own. One student was deemed ineligible to participate due to age (less than 18 years), and one student in the control group asked to be removed from the study. IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 9 Participants’ ages ranged from 18 to 22 years (M = 19.77, SD = 1.45). On average, dancers reported a range of 3 to 19 years of dance training (M = 13.30, SD = 4.50). Participants represented all four class years, namely freshman or first year (n = 13), sophomore (n = 2), junior (n = 12), and senior (n = 3). Prior to their participation in this study, few dance students had experience working with a sport psychology consultant (n = 3). The remaining students (n = 27) indicated no prior experience with a sport psychology consultant in an individual or group setting. At the start of the study (i.e., during the first week), almost half of the participants (n = 13) indicated that they were currently suffering from one or more injuries; four injured dancers were in the control group, and the other nine were in the treatment group. On average, dancers in the treatment group were 2.4 years older than dancers in the control group. Dancers in the control group were slightly younger (Mage = 18.60, SD = 0.91) than dancers in the treatment group (Mage = 20.93, SD = 0.80). Members of the control group reported a range of 14 to 25 hours of dance training per week. Members of the treatment group reported a range of 11 to 28 hours of dance training (see Table 1 for basic demographic information). The sampling procedure used in this study was both convenient and purposive (Patton, 2002). An appropriate sample size was determined prior to the start of the study. A sample of 28 participants was deemed suitable by the primary researcher in consultation with a statistician and G*power software (Faul, Erdfelder, Lang, & Buchner, 2007) by adopting a moderate effect size of 0.56 (Cohen, 1988) with a desired power of 0.80. Dance Program Characteristics and Setting Based on self-reported data from the participants, their dance program was somewhat rigorous, requiring a number of hours of class, rehearsal, and/or performance that is comparable to the 20 countable hours put forth by the National Collegiate Athletic Association (NCAA) for IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 10 college student-athletes. Of the 30 participants, 29 reported that they had to audition in order to be admitted into the program. When asked to describe the technical focus of their program, 77% of dancers (n = 23) described their program as ballet-based, and the other 23% of dancers (n = 7) described the program as either mixed-repertoire or consisting of more than one technical discipline (e.g., ballet, modern). Dance majors at this liberal arts institution could receive either a Bachelor of Arts degree in Dance or a Bachelor of Fine Arts degree in Dance, with the latter degree traditionally requiring additional studio work to prepare students for a professional career in the dance industry. The program is housed in an on-campus building, which consists of several dance studio spaces, dressing rooms, and faculty/staff offices. There were pianos in the studios for times when live accompaniment was offered for class. The studios were well-lit, clean, and had flooring that was appropriate for dance conditioning and performance. Outside of the studios, there was a lounge where dancers could stretch, eat, socialize, use their phones or iPods, and complete written homework between classes. Based on the primary researcher’s observations, this lounge area encouraged a sense of “community,” such that multiple conversations could be held at once, and people would make the space their own by spreading out textbooks, lunch boxes, or their own bodies when they needed to recover from or prepare for a technique class. The lounge area also housed resources for students, such as exercise DVDs, stretching equipment, and dance program photo albums. When the primary researcher arrived to the site each week to meet with the dancers in the treatment group, the lounge area served as the “home base” for the project. It was here that dancers could seek out the primary researcher for questions and concerns. One dancer used this space for a few brief individual consultations with the primary researcher about managing stress IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 11 and expectations. Another dancer approached the researcher in the studio space to inquire about an approach to stress management that a family member had utilized. A third dancer asked the researcher for more information on health/wellness careers such as performance psychology, and the researcher shared resources in a brief in-person meeting and via email correspondence. It should be noted that many dancers in the treatment and control groups acknowledged the primary researcher’s (and research assistant’s) presence in the lounge, but very few asked for advice or consultation over the six-week period, particularly when in the presence of other dance students. The primary researcher and research assistant observed that classes seemed to consistently begin a few minutes late, either due to students still transitioning from a previous class, or the faculty member needing to take a few minutes to switch focus from a meeting and/or to finalize content. The most commonly observed dance class was the one that the treatment group participants were taking (i.e., modern dance). This class was fairly structured, and it was clear from observing that the students were accustomed to this structure. Sometimes the students faced the front of the studio so that they could pay attention to the instructor and/or see themselves reflected in the wall-length mirror. Other times they faced different directions for individual or small group exercises, or stood in a circle to do community-focused dance work. Despite the program having an emphasis on classical ballet technique, dancers did not look uniform in appearance and dress code. The dance students represented many body types and wore a range of dancewear, including leotards, tights, sauna pants, t-shirts, sweat pants, and leggings. Women’s hair was typically pulled back in a loose or tight bun or ponytail. Both the primary researcher and research assistant noted the presence of coffee, tea, and water bottles placed around the borders of the dance studio, which dancers would visit during short breaks. IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 12 Although a somewhat casual tone was established, there were clear classroom norms as well. For instance, dancers would never re-enter a studio space during an exercise or dance number. They would wait until the music stopped and a combination or section of dancing was complete. Additionally, dancers clapped for the pianist at the end of each class. They also thanked any person of authority, including the primary researcher and research assistant, before leaving. Instrumentation Basic demographics survey. The primary researcher developed a basic demographics survey specifically for this study in an effort to contextualize the sample (see Appendix B). Survey items included participants’ age, gender, year in school, total number of years dancing, total number of hours dancing per week, and current injury status. The demographics survey also asked participants to rate their level of familiarity with the skills to be introduced during the intervention program (i.e., diaphragmatic breathing, progressive muscle relaxation, imagery, self-talk, and mindfulness). Information gathered via this instrument was intended to help describe the sample’s characteristics, rather than to answer a particular research question. Athletic Coping Skills Inventory-28. The Athletic Coping Skills Inventory-28 (ACSI 28; Smith, Schutz, Smoll, & Ptacek, 1995) is a multi-dimensional measure of self-reported psychological skills utilized in sport (see Appendix C). Seven sport-specific subscales make up the full measure, each subscale having four items answered on a 4-point Likert scale from 0 (almost never) to 3 (almost always). A total score, combining all 28 items, is used to assess overall coping skills, with a possible range of 0 to 84. The primary researcher chose to use this survey due to its multi-dimensional measure and the fact that it had previously been used with a dance population. IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 13 Researchers Estanol, Shepherd, and MacDonald (2013) have previously reported a mean total score of 49.34 and a standard deviation of 10.14 on the ACSI-28 for their sample of dancers (N = 205). Their sample consisted of collegiate-level ballet and modern dancers, professional dancers, and contemporary dancers. The researchers’ descriptives are comparable to the present study’s sample for both week one (M = 48.83, SD = 9.79) and week six (M = 48.72, SD = 10.66). The reliability and validity of the ACSI-28 has been tested with multiple samples and has been used to study coping skills and behaviors in the sport context (e.g., Mummery, Schofield, & Perry, 2004; Omar-Fauzee, Daud, Abdullah, & Rashid, 2009; Smith et al., 1995). Researchers have indicated questionable to acceptable reliability for the concentration subscale, with a Cronbach’s alpha of 0.62, and good reliability for the peaking under pressure subscale, with a Cronbach’s alpha of 0.78. These statistics represent the lowest and highest measures of internal consistency across all subscales of the instrument (Noh, Morris, & Andersen, 2007; Smith et al., 1995). Additionally, researchers reported that one-week test-retest coefficients from a sample of 90 college students and athletes had a median of 0.82 (Noh, Morris, & Andersen, 2007; Smith et al., 1995). In the present study, the primary researcher examined five-week test-retest reliability of the ACSI-28. The correlation between ACSI-28 total scores collected during the first and sixth weeks of the study was strong, r = 0.756, p = 0.000. Additionally, the primary researcher observed the relationship between pre- and post-intervention total scores on this instrument by group condition. There was a strong relationship between pre- and post-intervention ACSI-28 total scores for the treatment group, r = 0.870, p = 0.000. There was also a statistically significant correlation between these scores for the control group, r = 0.555, p = 0.039. These IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 14 correlations are relatively consistent with the reliability statistics reported by the instrument’s developers (Smith, Schutz, Smoll, & Ptacek, 1995). As for convergent and discriminant validity, the developers reported moderate correlations between the ACSI-28 and other similar instruments. These instruments included the Self-Control Schedule (Rosenbaum, 1980) (r = 0.44), Sport Anxiety Scale (Smith, Smoll, & Schutz, 1990) (r = -.43), and Self-Efficacy Scale (Coppel, 1980) (r = 0.58). In contrast to other coping questionnaires that are non-specific to sport (e.g., COPE; Carver, Scheier, & Weintraub, 1989), the ACSI-28 was developed specifically for use with athletes. However, it should be noted that the instrument is not grounded in one or more theories of stress and coping (Croker, Kowalski, & Graham, 1998), but may be considered as having originated from a cognitive behavioral approach (Estanol, Shepherd, & MacDonald, 2013). For the purpose of this study, some of the items were modified to reflect a dance-specific context. The words “coach” or “manager” were replaced with “instructor” or “choreographer.” Similar changes have been made to the ACSI-28 by others in their research with dancers (e.g., Estanol, Shepherd, & MacDonald, 2013; Noh, Morris, & Andersen, 2007). Estanol and colleagues (2013) reported a Cronbach’s alpha of 0.84 for the ACSI-28 when modified and used with their sample. Noh and colleagues (2007) reported slightly lower reliability with these modifications. However, the ACSI-28 had been translated into Korean, and so the translation could also have influenced their reliability estimates. In the present study, a Cronbach’s alpha of 0.727 was observed for week one across 30 participants, and a Cronbach’s alpha of 0.741 was observed for week six across 29 participants. As for the subscales, internal consistency coefficients ranged from a low of 0.508 for the confidence and achievement motivation subscale, to a high of 0.861 for the peaking under IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 15 pressure subscale (see Table 2 for internal consistency at week one compared to the developers’ alphas). These numbers are fairly consistent with the findings of Estanol, Shepherd, and MacDonald (2013). They reported low internal consistency for one subscale (i.e., coachability), with all other subscales having a Cronbach’s alpha greater than 0.65. This was also the case in the present study, although the subscale below this 0.65 cut-off point was confidence and achievement motivation, instead of coachability. Pain Appraisal Inventory. The Pain Appraisal Inventory (PAI; Unruh & Ritchie, 1998) is a self-report instrument comprised of 16 items that quantifies and classifies individuals’ beliefs about physical pain. The PAI also helps to evaluate what respondents think about their pain, and how these thoughts make them feel (see Appendix D). Based on literature in stress and coping research, the developers of the PAI included two scales within this instrument: threat appraisal and challenge appraisal. Threat was defined as “anticipated or actual physical or psychological harm, loss, injury or damage associated with a pain event,” while challenge was defined as “a test of strength, endurance or abilities, with the potential for growth, mastery or gain associated with a pain event” (Unruh & Ritchie, 1998, p. 106). One might expect these two subscales to be negatively related. However, researcher Anderson and Hanrahan (2008) reported the relationship between threat and challenge to be weak to moderate (r = 0.41) in a sample of dancers (N = 51) who represented a variety of styles and training levels. Each subscale contains eight items that are scored on a six-point Likert scale from 1 (strongly disagree) to 6 (strongly agree). A total composite score for pain appraisal can be calculated by summing the 16 items, with a possible range of 16 to 96. The sum of each subscale can also be calculated, with a possible range of 8 to 48. However, it should be noted that the developers stated that they initially considered a rating of “3” or higher to indicate an appraisal IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 16 of pain (Unruh & Ritchie, 1998), and so the total scores and possible ranges for this instrument and its subscales may be highly dependent on the severity and duration of pain that participants are experiencing when this survey is administered. Previously, Anderson and Hanrahan (2008) have reported a range of 8 to 43 for the threat subscale, and a range of 8 to 41 for the challenge subscale. No total scale psychometrics were reported in their study. Compared to Anderson and Hanrahan’s (2008) sample, the present study’s participants reported a similar range of scores on the PAI subscales. The threat subscale had a range of 8 to 37 for week one (M = 18.31, SD = 9.35) and a range of 8 to 32 for week six (M = 18.68, SD = 7.94). Similarly, the challenge subscale had a range of 8 to 42 for week one (M = 20.62, SD = 10.27) and a range of 8 to 43 for week six (M = 21.03, SD = 9.52). The instruments’ developers reported evidence of good validity and reliability. Concurrent criterion validity was determined by comparing the PAI’s properties to other pain instruments, including the McGill Pain Questionnaire (MPQ; Melzachk, 1987) and the Pain Disability Index (PDI; Tait, Chibnall, & Krause, 1990). Using data collected from a sample (N = 46) of college students, health professionals, and community members, the developers reported that the threat subscale yielded a Cronbach’s alpha of 0.86 and the challenge subscale yielded a Cronbach’s alpha of 0.81. In the present study, internal consistency was also strong. Cronbach’s alpha for the PAI at week one was 0.881. At week six, Cronbach’s alpha was 0.886. When observing the two subscales separately, the threat subscale had a Cronbach’s alpha of 0.914, and the challenge subscale had a Cronbach’s alpha of 0.904. The developers of the PAI have discussed some of the instruments’ limitations. Among these limitations is the unexplored relationship between appraisals, and chronic versus acute pain; the developers have suggested that differences in type of pain and their direct or indirect IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 17 effects on appraisal is unknown. The instrument’s developers have also reported a lack of test retest reliability. Given this fact, the primary researcher in the present study decided to run correlations on the PAI total scores as well as both subscales across all participants. The correlation coefficient for the PAI total scores was moderate, r = 0.399, p = 0.035. When observing PAI threat subscale scores, no meaningful relationship was observed between the first and second set of scores, r = 0.111, p = 0.575. In contrast, the PAI challenge subscale scores were strongly correlated, r = 0.527, p = 0.004 (see Table 3). When examining test-retest reliability by group condition, there were slightly different findings. The relationship between pre- and post-intervention PAI total scores in the control group was weak, r = 0.229, p = 0.430. The threat subscale showed no relationship, r = -0.196, p = 0.502, and the challenge subscale showed a moderate relationship, r = 0.497, p = 0.071 (see Table 4). In contrast, the pre- and post-intervention PAI total scores for the treatment group showed a strong relationship, r = 0.702, p = 0.005. The threat subscale data showed a weak relationship, r = 0.336, p = 0.240, and the challenge subscale data showed a moderate relationship, r = 0.664, p = 0.010 (see Table 5). Injury tracking survey. The primary researcher developed an injury tracking survey specifically for this study (see Appendix E). The content of this survey was inspired by several sources, including an injury tracking form developed by members of the Dance/USA Task Force on Dancer Health, and researchers Noh, Morris, and Andersen (2007). Previous research suggests that “dancers may under report injuries on surveys,” and, therefore, multiple questions about injury were presented (Thomas & Tarr, 2009, p. 51). Dancers were asked to report their current injury status; where their injury or injuries occurred on the body; if the injury or injuries caused them to miss or modify any training, rehearsals, or performances; whether they sought IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 18 medical attention; and the presence and severity of pain they may have experienced. Participants in the present study were incentivized to submit their injury reports every week throughout the study in order to be eligible to receive a $100 Visa gift card via a raffle system. The National Collegiate Athletic Association (NCAA) has defined a physical injury by focusing on three specific criteria. First, the injury must occur within the training or competition setting, and not in a different environment. Second, the injury must require the attention of an athletic trainer or physician affiliated with the particular group/team. Third and finally, the injury must restrict or prevent the athlete’s participation in sport for at least one day subsequent to the day in which the injury occurred (Dick, Agel, & Marshall, 2007). Due to the fact that dancers may be inclined to keep their injuries hidden, the primary researcher adopted a modified version of the NCAA’s third criterion. Specifically, any self-reported time lost was considered an instance of injury, rather than having dancers wait until the following day to “start the clock” on minutes or hours of dancing missed. Dance Experiences Survey. The Dance Experiences Survey (Krasnow & Mainwaring, 1990) was used in the present study to capture stressors that individuals may experience as a result of their role as dancers (see Appendix F). The instrument consists of 48 items, and asks participants to use “Yes” or “No” to indicate if each item applies to them at the present time. For those items that do apply, participants indicate the impact that these stressors have on them from -3 (extremely negative) to +3 (extremely positive). The instrument begins with an example so that participants are clear on the instructions and the format of the survey. At the end of the 48 items, participants are provided space to write-in any other stressors that they are experiencing, and to report the perceived impact of these stressors. The developers did not provide psychometric data via personal correspondence with the primary researcher, and there is a lack of psychometric IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 19 data available in the literature that uses this survey. As such, the information gathered via this instrument was intended only to describe the sample. Intervention program. The short-term psychological skills intervention program consisted of six sessions, with one session being conducted each week for the treatment group. This six-week time frame was determined through a search of the literature focused on short term behavior change and psychological skills interventions in sport (e.g., Bell, Skinner, & Fisher, 2009; Johnson, 2000; Meichenbaum, 1993). The primary researcher developed the intervention program content in collaboration with other sport psychology and counseling professionals, and from the content presented in the existing research literature. Face and content validity was confirmed by meeting with a licensed counselor and counselor educator to review all materials (see Appendix G for an overview of the intervention program protocol). Additionally, pilot testing was completed on all activities and handouts with two volunteer undergraduate students who reported a background in dance. During pilot testing, these two students provided verbal and written feedback about the aspects of the program’s content that they liked and did not like, and what they thought could be improved upon before its delivery to treatment group participants. The primary researcher compiled this feedback in written format and used it as a guideline for finalizing all intervention program materials. The primary researcher also asked these two students to complete all self-report surveys so that an estimated time period could be established for the data collection packets to be administered during the first and sixth weeks of the study. All sessions followed a similar outline, with exception of the first and last, which focused on data collection procedures. For the second through fifth weeks, the primary researcher’s routine for each session consisted of: (1) having the participants review what they had learned or IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 20 practiced in the previous week, (2) introducing the new skill to be learned or practiced, and then (3) providing an experiential learning activity focused on the week’s topic. After each skill was introduced and practiced, participants reflected on their experiences. For instance, participants were encouraged to pose questions or concerns about the topic or activity and to share their thoughts on how to use the skills(s) in dance class or other life pursuits. The first skills introduced were diaphragmatic breathing and progressive muscle relaxation. Participants were led through a deep breathing script and then through a progressive muscle relaxation exercise (in either an active or passive manner). The next skill introduced was imagery. Participants were led through a relaxation and coping imagery script based on Jon Kabat Zinn’s Mountain Meditation, and also led through a performance imagery script intended to help them prepare for dance class. The fourth week’s focus was on cognitive reframing and self-talk. Participants were given a handout that contained many negative, maladaptive, or irrational statements related to dancing. In small groups, they came up with more positive, adaptive, and truthful statements to use when they are dancing. The final skill introduced was mindfulness. Participants were led through a mindfulness-based stress management script that asked them to focus on their breath, a small item in their hand (a rock, provided by the primary researcher), and the present moment (see Appendix H for all of the exercises and activities used in the intervention program). Throughout the intervention program, the dancers’ class instructor remained present in the dance studio for all discussion, exercises, and activities. The instructor did not observe the sessions, but rather participated in the same way as the treatment group participants. However, the instructor did not participate in any data collection procedures during weeks one and six, and did not take part in the post-intervention focus group discussion. IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 21 For each week of the intervention program, the primary researcher sent the course instructor the written scripts used for each session, as well as audio-recordings of the respective exercises or activities. The instructor offered to post these files in an online portal, to which the treatment group participants had access throughout the semester. Audio-files were created via QuickTime software and could be downloaded and listened to with an iTunes account. Adherence journal. A weekly adherence journal was developed by the primary researcher and loosely based on the journal that Noh, Morris, and Andersen (2007) used in their study with Korean dancers (see Appendix I). Participants received a link to a secure, online survey so that they could complete the items on their own time following weeks two through five of the program (i.e., dance students were asked to submit an adherence report four times throughout the study). The survey asked participants to indicate which skill(s) they were practicing, and for what amount of time they were practicing them. Participants were also prompted to rate their efforts to practice the skill(s) on a 4-point Likert scale from 1 (no effort) to 4 (excellent effort). This particular item was intended to capture their perceived level of investment in the program. Findings from this instrument are reported as exploratory analyses following the results of the main research questions. Procedure The primary researcher contacted several dance program chairpersons in the Mid-Atlantic region of the United States by email. The email to these chairpersons contained a brief proposal of the research study and its anticipated timeline. Once a dance professor expressed interest in the study, a phone call was scheduled to talk to this professor one-on-one to further explore his/her interest. Then, the primary researcher and the interested professor assessed the feasibility of recruiting another professor from the same department who might also be interested in the IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 22 study. Once this second person was identified, the two professors and the primary researcher developed a schedule that worked for all parties involved. The primary researcher obtained Institutional Review Board (IRB) approval from the primary institution and completed supplemental documents for the approval of the institution at which data collection procedures occurred. These latter documents included an IRB Authorization Agreement and letters of permission from each classroom instructor. The research team—which consisted of the primary researcher, an advisor, and two research assistants—then finalized all instrumentation and the intervention program content. For six consecutive weeks, the primary researcher traveled from her primary institution to the data collection site. During weeks one and six, data collection was the main focus. At the start of the first week, the primary researcher briefly explained the research design to all participants so that they understood how group assignments were made. Participants completed the Athletic Coping Skills Inventory (ACSI-28; Smith, Schutz, Smoll, & Ptacek, 1995), the Pain Appraisal Inventory (PAI; Unruh & Ritchie, 1998), and an injury tracking measure developed specifically for this study for the first and sixth weeks. In addition, two instruments were used to contextualize the sample, and were collected during week one. These included a basic demographics survey and the Dance Experiences Survey (Krasnow & Mainwaring, 1990), the latter of which was intended to capture perceived levels of stress in dance-specific situations. A research assistant accompanied the primary researcher for weeks one and six so that the data collection procedures could be viewed by participants as a somewhat separate process from the delivery of the intervention program itself. To ensure confidentiality throughout the study, participants who volunteered to take part in data collection procedures used code names. These code names were developed during week IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 23 one of the study with both groups, and consisted of two letters and four numbers. The creation of code names was necessary given the repeated measures nature of some of the surveys. The participants’ contact information (i.e., phone numbers and email addresses) was also voluntarily provided during the first week of the study, and these details were stored as a separate file on a password-protected computer throughout the course of the study. Participants’ contact information was necessary in order to collect data for weeks two through five (see Appendix J). Emails were sent through Gmail and text messages were sent using EZ Text, a messaging service that allows recipients to opt-in or opt-out of correspondence at any time. For weeks two through five, the control group did not meet with the primary researcher. Participants in this group were sent the injury tracking survey via email or text message. The treatment group also received the injury tracking survey via email or text message during this same time frame. In contrast to the control group, the treatment group met weekly with the primary researcher to learn and practice the psychological skills previously described. While at the site, the primary researcher took field notes to capture the overall context of the dance program and the setting in which the participants were learning and training. The primary researcher also arrived early to each session to observe other classes and to be available to answer participants’ questions. After each session with the treatment group, the primary researcher remained on-site to address questions and/or comments. In addition to receiving the injury tracking survey on a weekly basis, participants in the treatment group received an email or text message that contained a secure link to the weekly adherence journal. The purpose of the adherence journal was to capture participants’ efforts to practice the skills introduced throughout the intervention program. IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 24 At the end of the intervention program—and once data collection procedures for week six were complete—the research assistant conducted a focus group discussion with participants in the treatment group (see Appendix K for semi-structured interview guide). This discussion was audio-recorded so that all responses could be fully transcribed. Focus group participants were incentivized with the offer of a chance to receive a $50 Visa gift card via a raffle system. Participants were asked to describe: (1) what went well, (2) what didn’t go well, (3) what was surprising or new, (4) how participants could use information provided in the intervention in their lives, and (5) what about the delivery (and/or the deliverer) would they change. Following the focus group discussion, the primary researcher conducted two exploratory interviews (i.e., stakeholder interviews) with each of the course instructors who allowed the researcher access to their classrooms. The instructors were interviewed via phone, and the interviews were audio-recorded so that they could be subsequently transcribed. Both instructors were informed that their names and titles would not be affiliated with the results and that any identifying information would be removed from the transcriptions. These interviews focused on gathering the instructors’ thoughts on their institution, program and teaching philosophies, and investment in the research topics and/or process. Interviews ranged from approximately 30 to 50 minutes and followed a semi-structured interview guide (see Appendix L for a summary of findings from these interviews). Following the conclusion of the study, the primary researcher remained available to participants and their instructors for follow-up questions or concerns. A basic summary of results was also provided. Finally, the primary researcher worked with the instructors to make the intervention program content available to those dancers who were initially assigned to the control group. IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 25 Data Analyses Before any analyses were conducted, the researcher cleaned the data set by looking for impossible values, missing data, and cases of attrition. A few issues were found. The weekly injury reports had the highest response rate at the start of and end of the study, and the lowest response rate for the weeks in between. Two inconsistent or not plausible cases were identified within the injury data. Three participants reported their injury status either twice in the same day or twice in the same week. Given the timing of these submissions, the primary researcher made the decision to interpret the first of the two submissions as the report for the previous week, and the second of the two submissions as the report for the current or upcoming week. No impossible values were discovered within the data, and no other major issues were discovered. Multiple statistical analyses were used to answer the proposed research questions. Basic descriptive and frequency statistics were run to contextualize the sample used in the present study. Then, to answer the first research question, an ANCOVA was run on the post-test data from the ACSI-28, using pre-test ACSI-28 scores as the covariate. This analysis was run on the total scores for the ACSI-28 as well as for the seven subscales of the instrument. The significance level was set to p = 0.05, with the goal of observing a small to moderate effect size. The second research question was answered by running a second ANCOVA on the post test data from the PAI, using pre-test PAI scores as the covariate. This analysis was run on the PAI total scores, as well as for the two subscales of the instrument. The significance level was again set to p = 0.05. The primary researcher chose these statistical analyses based on the fact that ANCOVA may be used to increase statistical power and may potentially help with adjusting pre-test differences between the non-random groups used in the present study (Harlow, 2014). It should be noted that the use of ANCOVA to statistically control for a covariate is a somewhat IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 26 controversial approach, and therefore statisticians recommend that results be interpreted with caution (Harlow, 2014; Miller & Chapman, 2001) The primary researcher planned to run repeated measures analysis of variance (ANOVA) to answer the third research question. This specific test could allow for the examination of the average frequency and duration of self-reported injuries throughout the intervention program. However, this analysis could not be run for two primary reasons. First, the number of dancers who reported their injury status (and injury details) varied by week. Most or all participants reported their injuries for weeks one and six. However, during the weeks in between, the number of reports decreased. Given that repeated measures ANOVA requires information to be observed or collected on the same participants at each time-point, the missing data greatly affected the ability to conduct this analysis. Additionally, there were very few dancers (n = 3) who reported any time lost due to injury. Time lost could have served as the continuous dependent variable in this analysis had more injury reports, and the details within them, been submitted each week. In the absence of this analysis, basic descriptive statistics were run in an effort to report other informative findings. As for the fourth and final research question, the primary researcher utilized qualitative analyses. The primary researcher and two graduate students followed open coding procedures (Creswell, 2007; Patton, 2002), and utilized a typological approach to identify themes and categories from the focus group discussion. This same protocol was used to analyze the two exploratory stakeholder interviews. The coding team also engaged in data triangulation (Patton, 2002) so as to determine similar and different perspectives. IMPACT OF A PSYCHOLOGICAL SKILLS TRAINING PROGRAM BRYANT 27 Results Descriptive Statistics At the start of the research study, participants in the control group had a slightly lower average score (M = 38.47, SD = 15.84) on the Pain Appraisal Inventory (PAI) than did participants in the treatment group (M = 39.42, SD = 14.77). In contrast, control group participants reported slightly higher coping skills (M = 52.00, SD = 8.26) as measured by the Athletic Coping Skills Inventory-28 (ACSI-28) when compared to treatment group participants (M = 45.67, SD = 10.42) at the start of the study. At the conclusion of the study, participants in the control group reported lower scores on the PAI (M = 36.14, SD = 16.27) when compared to treatment group participants (M = 43.07, SD = 11.49). For the ACSI-28, control group participants still had higher scores (M = 50.14, SD = 8.11) compared to treatment group participants (M = 47.40, SD = 12.73). Overall, the control group’s mean scores on the PAI and ACSI-28 slightly decreased over time, and the treatment group’s mean scores on thes

Players' Responses to and Primary Caregivers' Perceptions of Authoritarian and Authoritative Coaching in the Inner-City Players' Responses to and Primary Caregivers' Perceptions of Authoritarian and Authoritative Coaching in the Inner-City Renee Brown Follow this and additional works at: https://researchrepository.wvu.edu/etd Recommended Citation Brown, Renee, "Players' Responses to and Primary Caregivers' Perceptions of Authoritarian and Authoritative Coaching in the Inner-City" (2017). Graduate Theses, Dissertations, and Problem Reports. 5269. https://researchrepository.wvu.edu/etd/5269 This Dissertation is protected by copyright and/or related rights. It has been brought to you by the The Research Repository @ WVU with permission from the rights-holder(s). You are free to use this Dissertation in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you must obtain permission from the rights-holder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/ or on the work itself. This Dissertation has been accepted for inclusion in WVU Graduate Theses, Dissertations, and Problem Reports collection by an authorized administrator of The Research Repository @ WVU. For more information, please contact researchrepository@mail.wvu.edu. Players’ Responses to and Primary Caregivers’ Perceptions of Authoritarian and Authoritative Coaching in the Inner-City Reneé Brown Dissertation submitted to the College of Physical Activity and Sport Sciences at West Virginia University in Partial fulfillment of the requirements for the degree of Doctor of Philosophy in Coaching and Teaching Studies/ Positive Youth Dynamics Ryan Flett, Ph.D., Chair Sean Bulger, Ph.D. Andrea Taliaferro, Ph.D. Suzanne Hartman, Ph.D. Department of Coaching and Teaching Studies Morgantown, West Virginia 2017 Keywords: Positive youth development, inner-city, coaching styles, coaching Copyright 2017 Reneé Brown Abstract Players’ Responses to and Primary Caregivers’ Perceptions of Authoritarian and Authoritative Coaching in the Inner-City Reneé Brown An abundance of research in sport-based positive youth development (PYD) indicates that coaches should be positive, promote autonomy-supportive and authoritative coaching styles, and caution the use of authoritarian leadership, while too often ignoring elements of authoritarian leadership such as discipline and structure. However, most of the studies conducted targeted middle-upper socioeconomic status (SES) suburban, White populations, with little emphasis on the inner-city underserved context. Parenting and teaching literature provides strong support for authoritarian styles in the underserved setting (Hartman & Manfa, 2015; Smetana, 2011). Similarly, the few studies conducted in the underserved sport settings show support of authoritarian styles (Brown et al., in preparation; Cowan et al., 2012; Flett et al., 2012; Flett et al., 2013; Richardson, 2012). The purpose of this study is to extend the previous year’s season-long qualitative study of a single girl’s basketball team (Brown et al., in preparation) to include perspectives from parents of that team and quantitative surveys from players across the league. Participants included five head coaches with 14.2 years of experience and 80 players from the five teams in the league. The study incorporated interviews with six parental/primary caregivers from Team C; and quantitative surveys for players in the league. An abductive approach was used to develop thematic categories from the interview data (Miles, Huberman, & Saldana, 2014). Quantitative results revealed that players are improving life skill development over time. Additionally, in order for coaches to have the biggest impact, they must use authoritative coaching styles and foster a caring and mastery climate. More importantly, results indicated that authoritarian coaching was a unique predictor of life skills development, however, it did not affect life skill development in a negative or positive manner. Qualitative results revealed that parents/primary caregivers relied on the coach as a unique source of support and guidance to supplement, complement or compensate their adolescent’s home life. Additionally, parents/primary caregivers strongly preferred authoritarian coaching combined with authoritative components to instill values and positively influence life skill development. iii Acknowledgements First and foremost, I would like to give the praise, honor and glory to God for allowing me this opportunity to grow as a person, mentally, physically, spiritually, emotionally, and giving me the strength to endure through all odds. I am forever grateful and thankful for my advisor, Dr. Ryan Flett, because without your commitment, intuitive feedback, and immeasurable help, I would not have been able to complete this process without you. Throughout the years, you have been in my corner supporting me with everything whether it was academics, personal life, and exposed me to different opportunities to help develop me into the person that I am today. Dr. Flett, I want you to know that I sincerely appreciate and respect all that you do, because you go above and beyond the traditional role of a chair and I think more professors should strive to be more student-centered like you. To Dr. Hartman, I am so grateful that you were a part of the entire process. Your positive reinforcement, encouragement, and open-door policy helped motivate me through my dark times. I will forever remember the words you said to me, “If it was easy, then everyone would do it.” To Dr. Taliaferro, I am so happy that you were willing to be a part of the committee because the thing I valued most was that you were straight-forward and did not sugar coat anything and it was from a place of love, which reminded me of my mother. To Dr. Bulger, thank you for having a listening ear and reminding me that everyone has breakdowns at one point in time, but the most important thing is that you get back up and little did you know; it was those very words that kept picking me up. I would also like to acknowledge Stephanie McWilliams for her assistance in the qualitative analysis and all participants in the study. I am grateful that you all allowed me your time to help me complete the study, given all the other iv tasks and responsibilities you had going on. Without you all, none of this would be possible. There is an old African proverb which states “it takes a village to raise a child” little did you know, you were all that village and an extension of my family. If I could do everything over again, without changing one thing, I would; because I value each of you and because of your ideas and feedback made this a stronger dissertation. To my parents, Cardell Nino Brown Sr., and Reneé Bernice Drummond-Brown, WVU has made me understand without a shadow of a doubt that none of my accomplishments would have been possible without parents like you. Your patience, trainings and beliefs helped shaped me into the person I am today. I know it has been rough over the years, and we did not always see eye to eye, but you never gave up on me because you both seen something greater in my future. Thank you for making sacrifices that you did and I hope that I have made you proud. To my grandfather, Peter Charles Drummond, thank you pap-pap for loving me unconditionally, and being present at all of my presentations. To my siblings, Cardell Nino Brown Jr. and Raven Chardell Brown, although, you could not be there at times physically, because of jobs and travel; you were always there with me in spirit. To Anthony Antonelli and Family, thank you for the love, support and kindness you have shown me throughout the years. The Antonelli family will forever hold a special place in my heart. v To my late grandmother, Barbara Ann Drummond, this degree is for you. I cannot thank you enough because it was you and mom who both challenged and inspired me to pursue a PhD. While at WVU as you both requested, I held on to this scripture, 2Timothy 2:15 “Study to shew thyself approved unto God, a workman that needeth not to be ashamed rightly dividing the word of truth,” I hope I made you proud! I love you! To all my extended family and supportive friends (too numerous to mention) please know, that I am grateful for your love, support and prayers throughout the education process, you also hold a special place in my heart. To God be the glory for the things He has done in my life. vi Table of Contents Acknowledgements ...............................................................................................................................iii CHAPTER I ................................................................................................................................................. 1 Introduction .............................................................................................................................................. 1 Inner-City Context and Issues ........................................................................................................................ 2 PYD, Sport, and Underserved Inner-City Youth ...................................................................................... 4 The Coach’s Role in Inner-City Underserved Settings ......................................................................... 5 Statement of Purpose...................................................................................................................................... 10 Statement of Significance .............................................................................................................................. 11 Research Questions ......................................................................................................................................... 11 Key Terminology .............................................................................................................................................. 13 CHAPTER II............................................................................................................................................. 16 Extended Literature Review ............................................................................................................ 16 Positive Youth Development ....................................................................................................................... 17 Framing Key Literature in Theory............................................................................................................. 23 Effective Coaching, Mentorship, and Sport Issues .............................................................................. 30 Coaches’ Roles and Responsibilities ......................................................................................................... 39 Underserved Context and Sport ................................................................................................................. 45 Purpose ................................................................................................................................................................. 51 Hypothesis ........................................................................................................................................................... 53 CHAPTER III ........................................................................................................................................... 57 Method ..................................................................................................................................................... 57 vii Design .................................................................................................................................................................... 57 Setting ................................................................................................................................................................... 58 Participants ......................................................................................................................................................... 59 Measures .............................................................................................................................................................. 61 Pilot Testing ........................................................................................................................................................ 66 Procedure ............................................................................................................................................................ 68 Data Analysis ...................................................................................................................................................... 72 CHAPTER IV ........................................................................................................................................... 79 Results ...................................................................................................................................................... 79 Participant Numbers, Measurement Reliabilities, and Assumptions ......................................... 79 Descriptive Data and Correlations ............................................................................................................ 82 Research Question 1: Developmental Outcomes and Related Factors ..................................... 85 Research Questions 2: Common and Comparison of Coaching Style in Context .................. 92 Research Question 3: How Parents View Sport and/or Coaches ................................................ 93 Summary of qualitative findings ............................................................................................................. 106 CHAPTER V ........................................................................................................................................... 108 Discussion ............................................................................................................................................. 108 Summary of Findings ................................................................................................................................... 108 Limitations ....................................................................................................................................................... 113 Recommendations for Future Research .............................................................................................. 115 References ............................................................................................................................................ 117 Appendix A ........................................................................................................................................... 135 viii APPENDIX B ......................................................................................................................................... 139 Appendix C ............................................................................................................................................ 142 Appendix D ........................................................................................................................................... 147 Appendix E............................................................................................................................................ 156 AUTHORITARIAN AND AUTHORITATIVE COACHING 1 CHAPTER I Introduction The current dissertation is grounded in the ecological systems theory (EST) and expands Brown, Hayes, Goodson, Hartman, and Flett’s (in preparation) season-long ethnography and interview study to include parental/primary caregiver perspectives and the other high school girls’ basketball teams within the same city league. The purpose of this study is four-fold. First, it will inform the reader of the coaching styles used in the underserved setting. Second, it will explore the impact of the coaching style and objectively track developmental outcomes throughout the season. Third, it will explore the use of authoritarian strategies in the underserved setting, which is under-represented in the sport literature. Lastly, it will investigate parental/primary caregivers’ perceptions of the coaching style used in the underserved setting, the intentionality of the coach, whether life skills (LS) are transferred from the sport setting to other domains of life, and how the coach supplements or augments parental/primary caregivers’ efforts in this context. In summary, the purpose of this study is to expand the previous year’s season long qualitative study of a single girls’ basketball team to include perspectives from parents of that team and quantitative surveys from players across the league. Positive youth development (PYD) is especially important in underserved communities because youth are less likely to have positive emotional, social, and cognitive developmental experiences (Flett, Gould, & Lauer, 2013; Smetana, 2011). Sport is an avenue for youth to engage in PYD; however, PYD occurs from positive experiences and coaching, not from sport alone (Thomas-Fraser, Côté, & Deakin, 2005). AUTHORITARIAN AND AUTHORITATIVE COACHING 2 The sport-based PYD literature encourages coaches to create autonomy-supportive climates, be “positive” with their players, and cautions the use of authoritarian, controlling coaching styles (Cowan, Taylor, McEwan, & Baker, 2012). PYD research typically focuses primarily on white, middle- to high-class populations with limited research on coaches in underserved urban settings. Based on strong support from parenting literature—and to a lesser extent, the teaching literature—authoritarian styles may be the most developmentally effective approach in underserved settings. This chapter will provide a basic overview of the literature and issues in inner-city contexts, PYD in sport, and the coach’s role in the underserved setting, and will conclude with definitions of key terminology. Inner-City Context and Issues The underserved setting can be defined as those individuals that are provided with low levels of access, inadequate services (i.e. health services, low rates of insurance, etc.) and face a multitude of barriers in everyday life (Walsh, 2008). This context can be characterized by high-risk factors such as poverty, high crime rates, and lack of support. Youth who grow up in this setting are more likely to be at a developmental disadvantage socially, emotionally, and cognitively because they are not afforded the same opportunities as higher socioeconomic (SES) communities (Smetana, 2011). Underserved youth are more likely to face challenges such as broken homes, racism, poverty, lower quality health care, poor education, gang violence, crime, and limited extracurricular activities (Martinek & Hellison, 1997; Martinek & Schilling, 2003; Walsh, 2008). Experts have argued that youth living in the underserved settings are in the greatest need AUTHORITARIAN AND AUTHORITATIVE COACHING 3 of PYD-support because they are more likely to lack developmental experiences and support systems (Flett et al. 2013; Walsh, 2008). Parents and primary caregivers are responsible for socializing and teaching their children the socially desirable behaviors of the culture. However, parenting styles differ from home to home. Furthermore, Coakley (2002) indicated that upper-middle income, predominately White families place emphasis on upward mobility, as compared to an underserved minority family which emphasizes control and discipline. Research in parenting literature shows strong support for Coakley’s claim and revealed that parents in the underserved setting are more likely to use authoritarian parenting styles because they are developmentally effective and serve as a protective factor to underserved youth (Eamon, 2002, Smetana, 2011). For example, Eamon’s two-year longitudinal study with participants living in poverty found that the use of physical punishment prevented anti social behavior. In a similar study, Dearing (2004) found that authoritarian parenting served as a protective factor for youth living in a neighborhood characterized by rape, robbery, burglary, larceny, and aggravated assault. The authors also found that the authoritarian parenting style had a positive effect on academic performance. Research in teaching literature describes that the utilization of an authoritarian approach by staff and teachers toward youth living in poverty is associated with fewer child-behavior concerns (Hartman & Manfra, 2015; Higgins & Moule, 2009). For example, Hartman and Manfra conducted a year-long study to explore the relation between the quality of childcare and behavioral development with low-income underserved Latino children. The findings revealed that a controlling and strict (i.e. authoritarian) approach improved child behavior and decreased behavior concerns. In AUTHORITARIAN AND AUTHORITATIVE COACHING 4 sum, some research indicates that authoritarian styles are developmentally effective for youth living in the underserved settings. PYD, Sport, and Underserved Inner-City Youth PYD is a holistic strength-based approach that focuses on enhancing pro-social norms and optimizing personal development, and engaging youth within their family, school, and community contexts. This leads to involvement in extracurricular activities and develops and refine youth skills (Coakley, 2011). Experts emphasize that organized sport participation could be beneficial and aid in PYD (Deakin, 2005). Sport is considered the most popular and time-consuming activity in high schools (Hansen & Larson, 2007), and is typically available to underserved populations. Many believe that sport is an appropriate activity for enabling PYD because it can serve as a protective factor, enhance personal and interpersonal development, and provide opportunities for youth to build rapport with adults, such as coaches (Cowan et al., 2012; Flett, Gould, Griffes, & Lauer, 2012; Flett et al., 2013; Gould, Flett, & Lauer, 2012; Richardson, 2012). Research shows that sport can have positive outcomes such as physical health (Côté & Fraser-Thomas, 2007), teamwork/cooperation opportunities (Gould et al.), positive relationships with adults (Fry & Gano-Overway, 2010) and positive self-esteem (Smith, Smoll, & Curtis, 1979). However, other researchers found sport to have negative outcomes on youth such as increased stress (Merkel, 2013), emotional abuse (Stirling & Kerr, 2013), poor cooperation, and negative peer influence (Dworking & Larson, 2006). In other words, PYD does not occur from sport participation alone; other social contextual factors (i.e. coaches) contribute to the fostering of PYD (Petipas, Cornelius, Van Raalte & Jones, 2005; Holt, 2008). AUTHORITARIAN AND AUTHORITATIVE COACHING 5 The Coach’s Role in Inner-City Underserved Settings As stated earlier, PYD does not occur from sport alone; coaches play a pivotal role in player development through their coach-athlete relationship (Jowett & Ntoumanis, 2004; Petipas et al., 2005; Smith & Smoll, 2011) motivational climate, coaching style, and coaching behavior, especially in the underserved settings. Coach-Athlete Relationship. In underserved settings, interpersonal relationships within non-familial adults (such as coaches) are important (Levine & Munsch, 2016). The coach-athlete relationship is essential because coaches have the ability to become role models and mentors to their athletes due to the consistency and time spent in games, practices, and off-court activities (Jaime et al., 2015). Furthermore, research shows that athletes’ perceptions of strong coach-athlete relationships are linked to positive developmental experiences (Jowett, 2008). Richardson’s (2010) study in the underserved context of New York City showed that caring and trust was built between players and coaches through consistent interactions during practices and off-court activities. As a result, the coach was able to reduce risk, promote resiliency, and provide safety to players through mentorship. In addition, the coach kept players occupied with various activities and talked to players about their actions and choices. Experts emphasized the importance of the caring element when it comes to working with underserved youth. Motivational Climate and Caring Climate. Another important factor that has a direct impact on player experience is the motivational climate. Coaches are responsible for creating and structuring an environment that is beneficial to PYD. Research strongly supports the idea of using a mastery climate because success is based on personal improvement, effort, helping others, learning through cooperation, and hard work (Cox, AUTHORITARIAN AND AUTHORITATIVE COACHING 6 2002). Furthermore, studies have shown that mastery climates increased positive attitudes towards sport and coach (Fry & Newton, 2003), decreased burnout (Vitali et al., 2015), decreased athlete anxiety (Fry & Newton, 2003), and increased personal and social development. Gould et al. (2012) found that a mastery-oriented climate has the most positive impact on underserved youth. However, Gould et al. (2012) also found that “kids don’t care what you know, unless they know you care,” (p.86) and hypothesized that the caring climate defined by Newton et al. (2007, p.70) as "the extent to which individuals perceive a particular setting to be interpersonally inviting, safe, supportive, and capable of providing the experience of being valued and respected” is more important than a motivational climate and is more likely to influence PYD. The caring climate is an important factor in PYD because if players perceive the feelings of being cared for (feelings of support, safety, value, and respect) then they are more likely to value the perspective of their coach (Gano-Overway et al., 2009). In other words, coaches who create a caring climate can impact their players’ beliefs and foster prosocial behaviors. Similar to Richardson’s (2010) study, Gould et al. found that building rapport, caring, and supporting the athletes allowed the coach to be more effective in their personal and social development (e.g. teamwork, physical skills, initiative, cooperation). Additionally, Fry and Gano-Overway (2010) found that players who perceived a caring climate reported having higher enjoyment and more positive attitudes towards the coach and teammates. Coaching style. Coaches in urban, underserved settings are believed to be more authoritarian, controlling and militaristic towards their athletes because they want to protect and prepare their players for the ways of the world as opposed to creating an AUTHORITARIAN AND AUTHORITATIVE COACHING 7 autonomy-supportive climate (Flett et al., 2013). For example, Flett et al. (2012) conducted a qualitative comparison study in inner-city Detroit with 12 youth coaches from six different sports. The authors used ethnographic methods and interviews to observe the coaches 14 times in practice and game settings before conducting in-depth interviews with each coach. Findings indicated that coaches who utilized an authoritarian, militaristic coaching style were invested in their athletes lives and knew the personal struggles the athletes faced (e.g. gang violence, crime, abuse, uninvolved parents, dangerous neighborhoods, etc.). Furthermore, coaches wanted to prepare players for the ways of the world with “tough-love.” The coaches who utilized this approach disciplined the players out of love and went to the extremes to protect their athletes from negative outcomes. In addition, the authors found that discipline may be effective in the urban underserved settings, which is consistent with the parental literature. However, the same sample of coaches tended to use authoritarian styles in overly harsh, ineffective ways. Discipline and toughness used by these coaches were understandable and justified, but extreme anger, harsh verbal attacks and emotional manipulations were unjustifiable. The study did not investigate the coaches’ behavior over a long period of time, did not interview parents, and this particular study did not incorporate quantitative measures or a more generalizable sample size. Cowan et al. (2012) conducted a case study in the underserved setting of Scotland to explore coaching behaviors and the common assumption that autonomy-supportive coaching is adaptive, versus controlling coaching which is considered to be maladaptive. The sample included two male head coaches and 18 athletes from two teams between the ages of 16 to 19 years. The authors found that the coaches were considered to be AUTHORITARIAN AND AUTHORITATIVE COACHING 8 controlling and militaristic. However, the coach used humor to help buffer the negative outcomes associated with his authoritarian, controlling coaching style. In addition, the authors found that the provision of choice to the players was maladaptive in this setting because players lacked confidence and self-esteem. The study was limited because the authors were not immersed into the culture of the team but instead relied on non participant observations. This underserved setting may also differ from North American high school sport. Although the context may differ, the fact remains that an authoritarian coaching style was effectively used in an underserved setting. Based on the few studies published about underserved sport-based PYD, results suggest that authoritarian coaching styles play a significant role in underserved PYD (Cowan et al., 2012; Flett et al., 2012; Flett et al., 2013; Gould et al., 2012; Richardson, 2012). Brown et al. (in preparation) conducted a season-long in-depth ethnographic study to observe a coach’s style and impact on players in the underserved setting. In addition, the study included interviews to assess the coach and players’ perceptions of the developmental environment, the coach’s perceived role/responsibilities, and the rationale for coaching style/strategies. In an effort to address multiple gaps in the literature, this study focused on a high school girls’ basketball team, was conducted over an entire year, and the primary investigator was embedded within the team as a volunteer coach (and had already coached with that team for a full season before this research study). As such, the data collected in this dissertation represents the author’s third year with the team and second year researching them and the city-league. The results of Brown et al. (in preparation) indicated that the coach was characterized as highly authoritarian and controlling, but also highly caring and sensitive AUTHORITARIAN AND AUTHORITATIVE COACHING 9 to the needs of the players. Together, these attributes are indicative of what the authors term a “tough-love” approach: caring, understanding, and supportive, yet disciplined, demanding, and lacking autonomy support. The coach consumed and controlled much of the player’s time in order to develop academics, life skills, and character while keeping them from threats in the community. Player and coach-interviews revealed that the coach had high expectations for the players and disciplined them out of love. The coach used physical tactics such as Charlie Horsing (light jabs in the arm), “popping” (i.e. slapping players in the head), and “socking” (i.e. punching) to get players back on task, to motivate, and to keep their attention. All players believed the coach used physical contact in a positive and humorous manner, never in a negative manner, because the coach cared for the players. Critical to the literature, results indicated that players generally supported the coach’s use of an authoritarian approach, and expressed a desire for even more disciplinary, controlling, and strict leadership (in order to manage newer and more unruly girls). However, the study was limited in its design because the authors focused on one team in the league and did not make comparisons to other teams. In addition, they did not obtain quantitative assessments of developmental outcomes or perceived coaching style. Parents of the players also expressed an interest in being interviewed so that they could share their perspectives on the coach, context, and their daughter’s development. What works for one context may be maladaptive in another context. Authoritarian styles used in underserved, high-crime/-violence, and disadvantaged settings are more likely to facilitate resilience and positive outcomes in youth (Cowan et al., 2012; Flett et al., 2012; Flett et al., 2013; Gould et al., 2012; Hartman & Manfra, 2015; Richardson, 2012). Additionally, authoritative styles in these settings may be considered harmful and AUTHORITARIAN AND AUTHORITATIVE COACHING 10 maladaptive. Coaching styles should be context-specific and focus on players’ needs (Flett et al., 2016). After reviewing the foundational articles related to coaching in the underserved settings, future research needs to explore parental/caregiver views on the coaching style and how it impacts child development, the transfer of life skills, and the use of authoritarian strategies. The current sport-PYD literature is not representative of the underserved context and the unique challenges they face in everyday life. As stated earlier, parenting literature and to an extent, some teaching literature shows strong support for authoritarian (controlling, monitoring, and strict) styles in the underserved setting. However, coaching literature typically cautions the use of authoritarian styles and supports the use of positive, choice-based, autonomy-supportive (i.e. authoritative) styles for PYD—but may be overgeneralizing their findings. Furthermore, the current sport-PYD literature needs to expand and become more culturally and socioeconomically diverse. Additionally, the literature must progress and change from streamlining and stating that the use of authoritarian coaching and parenting is wrong. More importantly, the most valuable question that needs to be answered is: How can authoritarian styles of coaching be used most effectively, especially in the underserved settings? Statement of Purpose In summary, the purpose of this dissertation will address the lack of underserved PYD research; address the need for more longitudinal mixed-method studies; objectively measure and track developmental outcomes throughout a season; and better understand coaching styles used and how they impact PYD in the underserved setting (Cowan et al. AUTHORITARIAN AND AUTHORITATIVE COACHING 11 2012; Flett et al. 2012 and 2013). In addition, the dissertation will answer the question “what combination of coaching style factors has the strongest influence for PYD in the underserved setting?” Lastly, it will look at parental/caregiver perceptions and preferences of coaching styles, the intentionality of the coach, and transferable life skills. Statement of Significance The following dissertation contributes to the existing sport-based PYD literature by exploring a multitude of coaching styles used in the underserved settings of the inner city. To the knowledge of the primary investigator (PI), this study is the first to objectively measure authoritarian and authoritative coaching in sport (in the underserved or any other setting). Additionally, the current study will assess life skill outcomes at two time periods, which differs from the current sport-based literature utilizing one time of data collection. This study is informed by not only the sport literature but also parental and teaching literature. Research Questions This study will use quantitative measures to survey teams across the city league located in an urban underserved setting in the North East United States, and in-depth interviews with parents/primary caregivers from one team (Team C) within this league. The research questions and sub-questions guiding the study are as follows: 1. Do life skills (LS) improve from participation, and what coaching style factors influence those LS outcomes? 1.1 Do quantitative measures of life skills show improvement for players across the season (Do scores change over time)? AUTHORITARIAN AND AUTHORITATIVE COACHING 12 1.2 Do quantitative measures of coaching style change over the basketball season (between Time 1 and Time 2)? 1.3 Are certain coaching styles greater for LS development (i.e. authoritarian, authoritative, caring, mastery, ego)? 1.4 If you were to combine all coaching style factors, which have the strongest influence on LS? 1.5 What influence does authoritarian coaching have on LS when combined with each of the other three coaching style factors (i.e. caring, mastery, ego), one at a time (i.e. authoritarian + caring; authoritarian + mastery; and authoritarian + ego). 1.6 What influence does authoritative coaching have on LS when combined with each of the other three coaching style factors (i.e. caring, mastery, ego), one at a time (i.e. authoritative + caring; authoritative + mastery; and authoritative + ego). 2. What is the common style of coaching in the city league? 2.1 What is the common coaching style in the city league? 2.2 How does Coach DD’s (Team C) style compare to other coaches’ styles in the city league? 3. Is this coach (Coach DD, Team C) developing LS through basketball, and if so, what skills and how does she develop them? 3.1 What developmental outcomes do parents think occur from participation with this coach and team (i.e. life skills development, intentionality, and transferability)? AUTHORITARIAN AND AUTHORITATIVE COACHING 13 3.2 Does the coach foster youth development intentionally? If so, how does she intentionally develop LS? 3.3 Do parents feel they can provide concrete examples of transferrable LS? If so, how are they being transferred? 3.4 Do parents think the sport or coach supplement psychosocial development in the players’ home lives? If so, how does the coach or sport supplement psychosocial development in the players’ home lives? Key Terminology Adolescents. Youth who are in the transitional stage concerning childhood and adulthood between the ages of 13 to 19 years. Authoritarian. A person who is characterized as highly demanding, less responsive, controlling, and rarely provide rationales (Baumrind, 2013). Authoritarians tend to create a disciplined environment with clear rules, and monitor behaviors, and activities of youth (Holt, Tamminen, Black, Mandigo & Fox, 2009). Authoritative. A person who is characterized as highly demanding, responsive, consistent, and provides rationales (Baumrind, 2013). In addition, authoritative people are assertive, and use supportive rather than disciplinary actions (Holt et al. 2009). Autonomy-supportive. “A style that actively supports self-initiated strivings and creates conditions for athletes to experience a sense of volition, choice, and self endorsement (Bartholomew, Ntoumanis, Thøgersen-Ntoumani 2010).” In addition, an autonomy-supportive style allows youth to feel that they initiate their actions rather than feeling coerced to act in a certain manner (Grolnick, 2003). AUTHORITARIAN AND AUTHORITATIVE COACHING 14 Caring climate. “The extent to which individuals perceive a particular setting to be interpersonally inviting, safe, supportive and capable of providing the experience of being valued and respected” (Newton et al., p.70). Positive youth development. A holistic intentional approach that engages youth in all contexts (i.e. school, home, work, etc.) while enhancing pro-social norms and helping youth reach their full potential (Holt, 2008; U.S. Department of Health and Human Services, 2007). Sport. Structured physical activity governed by a set of rules and facilitated by a coach or instructor that is implemented in an individual or group setting. Tough-love. A formal, established definition for this term is not available from the literature, but because the term is frequently used in this dissertation, it is important to provide clarity it. The term has emerged from research by Flett et al. (2013) and Brown et al. (in preparation). Tough-love is meant to describe a highly caring and respectful approach to authoritarian, or more controlling, coaching. Such an approach would not be “entirely” authoritarian in that there could be elements of autonomy-supportive and authoritative behaviors. Finally, based on Flett et al.’s work, it is important to clarify that a tough-love approach is not angry, unregulated, out of control coaching. A tough-love coach is able to model life skills and positive psychosocial attributes. Underserved. According to the American Journal of Managed Care (2013), underserved populations are defined as vulnerable populations that include the economically disadvantaged, racial and ethnic minorities, the uninsured, low-income children, the elderly, the homeless, those with human immunodeficiency virus (HIV), and those with other chronic health conditions, including severe mental illness. It may also AUTHORITARIAN AND AUTHORITATIVE COACHING 15 include individuals who often encounter barriers to accessing healthcare services. The vulnerability of these individuals is enhanced by race, ethnicity, age, sex, and factors such as income, insurance coverage (or lack thereof), and absence of a usual source of care. Their health and healthcare problems intersect with social factors, including housing, poverty, and inadequate education. For the purpose of the dissertation, underserved will be characterized as those who are socially disadvantaged, living in poverty, and face many unique challenges such as racial discrimination, gang violence, substance abuse, and cultural barriers (see, Flett, Gould, & Lauer, 2013; Richardson, 2012; Walsh, 2008). AUTHORITARIAN AND AUTHORITATIVE COACHING 16 CHAPTER II Extended Literature Review This dissertation addresses the need for research on sport coaches and positive youth development (PYD) in the underserved setting. The study will explore inner-city coaching styles throughout the season and their impact on developmental outcomes. In addition, the study will examine parents’/primary caregivers’ perceptions of the coaching style in the city league, and intentionality and transferability of life skills. While an authoritative style and positive coaching strategies (e.g., autonomy support) are staples of a PYD approach to coaching, authoritarian parenting and teaching styles are more developmentally effective in underserved settings. Bartholomew, Ntoumanis, and Thøgersen-Ntoumani (2010) argued that coaches can use a mixture of both autonomy-supportive and controlling strategies simultaneously and still be considered adaptive. Youth from underserved settings are in the greatest need of PYD because of the unique challenges they face in their everyday life (Walsh, 2008). Researchers believe that underserved youth may also be less likely to have positive developmental experiences in sport (Flett, Gould & Lauer, 2012; Flett, Gould, Griffes, & Lauer 2013; Richardson, 2012). Sport is a popular activity in high school and many perceive it to be an effective activity to enhance personal development and serve as a protective factor for underserved youth (Coakley, 2011). Sport provides underserved youth the opportunity to develop interpersonal relationships and build rapport with peers and non-familial adults, such as coaches. AUTHORITARIAN AND AUTHORITATIVE COACHING 17 The purpose of this chapter is to explain the importance of PYD and how it relates to this study. Additionally, this chapter will discuss the context needed for PYD to occur in sport and explain the importance of girls’ participation in sport. The chapter will then focus on the ecological systems theory (EST), which will help explain the importance of interpersonal relationships throughout different contexts, and how they play an enormous role in player psychosocial development. Furthermore, it will then focus in depth on effective coaches, with specific emphasis on the coaches’ role, style, and the created motivational and caring climate. Lastly, the chapter will review the scant literature in sport and the underserved setting, address gaps, and discuss future directions. Positive Youth Development In the past, traditional youth development was reactive and focused on minimizing and reducing problems such as teen pregnancy, sexual involvement, substance abuse, problem behaviors and delinquency during adolescence in targeted populations (Holt, 2008). This traditional approach provided intervention programming and treated youth as beneficiaries as opposed critical resources and solutions. Pittman et al. (2011) noted that problem-free youth are not fully prepared to be productive members of society. Larson (2000) argued that healthy development involves more than reducing and minimizing problem behaviors. In addition, Holt (2008) and others argued that a comprehensive, holistic approach is more beneficial and would achieve long lasting results for youth. As a result, a shift has been made from a traditional deficit reduction approach to a humanistic positive youth development approach. PYD is a holistic, strength-based approach that engages all youth within their families, school, and community context. PYD has no singular definition. It concentrates AUTHORITARIAN AND AUTHORITATIVE COACHING 18 on enhancing pro-social norms, helping youth reach their full potential (U.S Department of Health and Human Services, 2007), fostering positive relationships (Strachan, Côté, & Deakin, 2009), and viewing youth as contributing members of society and critical resources to be developed as opposed to problems to be solved (Holt, 2008; Roth & Brooks-Gunn, 2003). Within the PYD field, several researchers have outlined key components needed for optimal development. Larson (2000) believed that there needs to be a match between experiences of adolescents and requirements of the adult word. He argued that youth need three important characteristics to function as healthy adults: initiative, empowerment and leadership opportunities. Damon (2009) believed youth need to have a “purpose” in life, which, in turn, helps adolescents cope and allow them to be optimistic no matter the situation. The Five C’s Model of PYD created by Lerner and colleagues (2005) address psychological, behavioral, and social characteristics in youth including: competence, confidence, connection, character and caring. Youth who acquire the Five C’s are considered to be thriving and will develop a sixth C, described as contribution to self, family, and community (Zarrett & Lerner, 2008). Similarly, the Search Institute identified 40 developmental assets, also known as “building blocks” for human development. These assets help youth to become more healthy, caring, and responsible adults. The developmental assets are organized into two components, internal assets and external assets, with eight domains. Internal Assets are sets of skills, links to the personal development, competencies, and values within a person and are grouped into four categories: 1) positive identity, 2) positive values, 3) social competencies, and 4) commitment to learning (Benson et al., 2011). External AUTHORITARIAN AND AUTHORITATIVE COACHING 19 assets describe the environmental, contextual and relational assets (formation of strong bonds and relationships with the developing person), and are likewise grouped into four categories: 1) empowerment, 2) support, 3) constructive use of time, and 4) boundaries and expectations (Benson et al., 2011; Brofenbrenner, 2009). In order to develop these assets, youth must positively and effectively interact within various contexts (family, school, and community) to build important relationships and foster opportunities to enhance their skills (Strachan et al., 2009). Research shows that adolescents who acquire multiple assets have a greater chance of developing in a healthy manner (Benson et al., 2006; Strachan, Fraser-Thomas, & Nelson-Ferguson, 2016). Fraser-Thomas, Côté and Deakin (2005) implied that organized sport participation could benefit youth and help them grow into caring and responsible adults. Sport and PYD. PYD engages youth through multiple contexts (family, school, and community) and provides youth the opportunity to get involved in various extracurricular activities, like sport, to develop and refine their skills. In almost every school, sport is the most popular and time-consuming activity (Hansen & Larson, 2007). In the United States, approximately 21.5 million youth between the ages of 6 to 17 participate in organized team sports annually (Kelley & Carchia, 2013). The late Nelson Mandela stated: Sport has the power to change the world. It has the power to inspire, it has the power to unit people in a way that little else does. It speaks to youth in a language they understand. Sport can create hope, where once there was only despair (Laureus World Sports Awards, Monaco 2000). AUTHORITARIAN AND AUTHORITATIVE COACHING 20 Organized sport enhances personal development more so than informal activities such as hanging out with friends (Mahoney & Stattin, 2000), or hanging out at the mall (Osgood & Anderson, 2004). According to Perkins et al. (2007), “Time spent in youth programs is the most consistent predictor of youth thriving,” and research supports that youth participating in organized sport are more likely to experience positive developmental outcomes in comparison to those who do not participate in organized sport (Larson, 2000). Empirical findings have shown that organized sport can lead to healthy social, psychological, and physical developmental outcomes such as an increase in physical health (Bailey, 2006; Côté & Fraser-Thomas, 2007), self-esteem (Bailey, 2006; Smith, Smoll & Curtis, 1979), decreased stress (Smith, Smoll, & Cumming, 2007), leadership opportunities (Gould & Carson, 2008), teamwork/cooperation opportunities (Gould et al., 2012), increased academic achievement (Bailey), character development (Donnelly & Coakley, 2007; Gould, Collins, Lauer, & Chung, 2007), responsibility (Hellison & Cutforth, 1997) and the establishment of positive relationships with adults (Fry & Gano-Overway, 2010; Strachan et. al, 2009). The cultural and structural context of sport influences personal and social development (Theokas, Danish, Forneris, Hodge, & Heke, 2008). Factors such as personal characteristics of the athletes and coach (Peterson, 2004), actions of the coaches (Smith& Smoll, 2002), and the environmental context (Fry & Gano-Overway, 2010; Holt, Sehn, Spence, Newton & Ball, 2012; Martinek & Hellison, 1997) play a role in developmental outcomes in sport. Larson, Hansen, and Montea (2006) contend that positive outcomes of sport will likely occur when it is intentional, structured, and systematic because sport is more likely to enhance external and internal assets in AUTHORITARIAN AND AUTHORITATIVE COACHING 21 adolescents (Hodge, 1989; Petipas, Cornelius, Van Raalte, & Jones, 2005). However, sport participation alone is not the “magic ingredient” to enhance PYD. Negative outcomes and best-practices. Although many studies show that sport can be beneficial to PYD, negative outcomes can occur if PYD is not intentional. If sport is not conducted in the right manner, it has the potential to deter youth from personal and social development and result in eating disorders (Reel, SooHoo, Petrie, Greenleaf, & Carter, 2010), elevated use of alcohol (Lisha, Crano, & Delucchi, 2014; Veliz, Boyd, & McCable, 2015), sport injuries (Vitali, Bortoli, Bertinato, Robazza, & Schena, 2015), decrease in self-esteem and confidence (Stirling & Kerr, 2013), athlete burnout (Vitali et al.), increased stress (Gould & Carson, 2010), poor sportsmanship (LaVoi, & Stellino, 2008), emotional abuse (Stirling & Kerr), and/or poor cooperation and negative peer influence (Dworkin & Larson, 2006). These negative outcomes are believed to occur because of parents, youth, and coaches placing too much emphasis on sport outcomes (i.e. winning, losing, and playing time), lack of formal education for coaches, and sport susceptibility to adult domination (Gould & Carson, 2008). The research presented shows empirical support for both positive and negative outcomes that may result from sport participation. As stated earlier, sport participation alone is not the “magic ingredient” to enhance PYD. Coakley (2011) argued that, “By itself, the act of sport participation among young people leads to no regularly identifiable developmental outcomes” (p. 309). In an effort to reduce negative experiences, Petipas et al. (2005) created a PYD sport framework grounded in research findings and best practices in the field of youth development (Larson, 2000; Smith & Smoll, 2002). Petipas et al. indicated that PYD will AUTHORITARIAN AND AUTHORITATIVE COACHING 22 occur when youth a) are engaged in a desired activity within the appropriate context, b) are surrounded by positive, caring external assets, and c) have the opportunity to learn and acquire internal assets. In addition, Lerner and Lerner (2006) indicated that structure and physical/psychological safety of athletes are critical factors to instilling PYD. In the teaching personal and social responsibility (TPSR) framework, Martinek and Hellison (1997) suggested that youth development programs should develop a sense of values, purpose, and empowerment; respect diversity; promote safety; and develop resiliency. In other words, youth programs need to create and maintain a physically, psychologically, emotionally, and socially safe setting where coaches provide opportunities to teach youth the necessary skills and instill positive values needed for sport and other domains (i.e. school life, home life, and work life). The current study looks at how coaching styles, sport participation, and intentionality of the coach may promote PYD. Girls in sport. This study will look at PYD in the context of high school girls’ basketball teams. A generation ago, sport literature focused primarily on male involvement because girls participating in sport were not culturally accepted nor acknowledged. Within the past 40 years, there has been an increase in girls participating in sports in America due to Title IX of the Educational Act of 1972, which prohibits gender discrimination in any federally funded education program or activity (Paule-Koba, Harris, & Freysinger, 2013). Title IX states, “No person in the United States shall, on the basis of sex, be excluded from participation in, be denied the benefits of, or be subjected to discrimination under any education program or activity receiving financial assistance” (Title IX and Sex Discrimination, 2015). As a result, Title IX increased athletic opportunities for girls and women. Women participating in sports has become more AUTHORITARIAN AND AUTHORITATIVE COACHING 23 culturally accepted and celebrated (Cooky, 2010). Research shows that sport and physical activity positively impact the physical and psychosocial well-being of girls and women (Staurowksy et al. 2009). Sport can potentially increase girls’ self-confidence, prevent eating disorders, and enhance their physical health (Kane et al., 2007). In addition, sport participation is associated with a positive body image (Hausenblas & Fallon, 2006; Huang et al. 2007), an increase in educational achievement (Coakley, 2011), and a decrease in teen pregnancy and substance abuse (Staurowsky et al.). Allen (2003) implies that a sense of belongingness and enjoyment is the motivator for girls in sport. Furthermore, Allen (2003) also provided support that girls prefer social, “fun” activities, and opportunities to learn concepts and skills as motivators for their participation (Passmore & French, 2001; Perkins et al., 2007). Despite Title IX and increased athletic opportunities, sport participation gaps for underserved African American girls still exist in urban and rural communities (Sabo & Veliz, 2008). Sabo (2009) suggested that the lack of participation in urban and rural communities can be explained by multiple contextual factors that include family income, race and ethnicity, and the type of community. Sport may be helpful to achieve PYD for underserved girls, but as stated earlier it is not the only ingredient (Coakley, 2011; Hartmann & Kwauk 2011). Coakley (2011) argued that other factors within and outside the sport program help to foster developmental benefits. Framing Key Literature in Theory Multiple theories have been used in sport PYD literature to explain the positive and negative outcomes of sport. Due to the pragmatic approach for this dissertation, the theory used for the current study is grounded in the ecological systems theory (EST). The AUTHORITARIAN AND AUTHORITATIVE COACHING 24 current study uses the EST (Brofenbrenner, 2009) to organize the review of literature and as the rationale for including parents and other teams from this league as participants in this study. EST allows the researcher to look at a broader picture of how an inner-city girls’ basketball team functions in relation to the entire league and the parents’/primary caregivers’ point of view. Ecological System Theory. Brofenbrenner’s (1977; 2009) EST suggests that human development and human behavior occur from person to context interactions. EST provides a framework to understand the significance of social interactions within and between various contexts, such as the home, school, and work environments. EST has been used across several research domains (e.g. sport, public health, psychology, child development, sport, etc.) to understand the bidirectional influence between youth and their context (Lerner et al., 2011). Within the EST framework, the ecological systems model is organized into four nested systems that include: microsystem, mesosystem, exosystem and macrosystem. The microsystem represents one’s immediate context that directly impacts development (e.g. home, school, church, team). The mesosystem represents regular social interactions and interconnectedness between the microsystems (i.e. the relationship between a coach and player). The exosystem represents the relation between a social setting and one’s immediate context, which the individual does not have an active role in (i.e. the coach’s relationship with the player’s parents). Lastly, the macrosystem represents the cultural context, such where one lives (e.g., neighborhood), SES, poverty and ethnicity. EST is relevant to the sport domain because it takes into account the bidirectional influence of individual, environmental, and program characteristics, rather than studying the AUTHORITARIAN AND AUTHORITATIVE COACHING 25 individual in isolation. Integrating EST into the design of this study reinforces the PYD perspective, because PYD is grounded in an ecological systems approach to youth development (Holt, 2008). The family, school, and community contexts of PYD are considered below. Family context. Within the family context (microsystem), parenting strategies and techniques are used to socialize and teach their children appropriate behaviors of the culture. Parenting styles differ throughout cultures and vary from home to home. Coakley (2002) emphasized that upper- middle income, predominantly White families have different ideas about PYD and believe that outcomes should emphasize achievement and upward mobility, in comparison to underserved minority families who emphasize control and discipline. Baumrind (2013) created a typology that described four different parenting styles grounded in research findings: authoritarian, authoritative, permissive and disengaged. For the purpose of this paper, authoritarian and authoritative parenting styles will be defined and emphasized as they relate to coaching in the inner-city. Authoritarian parenting styles are described as highly structured with clear stated rules, high control, and militaristic with the use of physical discipline such as spanking (Deater-Deckard, Lansford, Dodge, Pettit & Bates, 2003; McLoyd, Kaplan, Hardaway & Wood, 2007). Parents who utilize this style are considered to be high in demand and low in acceptance and responsiveness to their child. These types of parents often have a large number of rules that they expect their children to obey and rarely provide rationales for their rules and expectations. On the other hand, authoritative parenting styles are described as parents being highly demanding and highly accepting/responsive to their children. Unlike AUTHORITARIAN AND AUTHORITATIVE COACHING 26 authoritarian parenting styles, authoritative parents tend to provide rationales for their rules/expectations and listen to their child more (Baumrind, 2013). Experts suggest that authoritative parenting styles are linked to positive PYD outcomes; however, these findings may not be generalizable to other contexts because the majority of these studies examined white, middle-class populations. Coll and Pachter (2002) advised researchers studying African American or other minority populations to use a historical and cultural lens to try to account for their experiences (i.e. slavery, racism, and poverty). Similar to EST, sociocultural theorist Vygotsky believed “development occurs over time within the context of the culture” (Gardiner & Kosmitzki, 2008, p. 302). In other words, learning and development occurs through context and social events, and cannot be separated from cultural, historical, and social contexts in which they are situated (Wang, Bruce, & Hughes, 2011). This paradigm looks at how social interaction and participation in organized activity play a role in psychological development (Scott & Palinscar, 2009). According to Thompson (2004), “African Americans in urban communities are socialized very differently from Whites from middle-class communities” (p. 72). Research has shown that authoritarian parenting practices used in low-income families correlate with lower levels of child behavior problems. For example, Eamon (2002) conducted a two-year longitudinal study with a sample of 963 participants between the ages 10 to 12 years old. Results showed that poverty was strongly related to neighborhood problems more than parental and peer influences. In addition, Eamon found that authoritarian parenting styles and the use of physical punishment for kids living in poverty buffered anti-social behavior. Similarly, Dearing (2004) conducted a longitudinal study in Massachusetts with three ethnic groups AUTHORITARIAN AND AUTHORITATIVE COACHING 27 (i.e. African American, Latino American, and European American) living in an underserved setting plagued by rape, robbery, burglary, larceny, and aggravated assault. The purpose of the study was to examine how neighborhood characteristics moderated associations between parenting and child outcomes. Results showed that restrictive/controlling (authoritarian) parenting styles were a protective factor and had a positive effect on academic performance for African American and Latino American children, but had a negative effect on European American children. Furthermore, research shows that minority parents living in dangerous and impoverished neighborhoods are typically more controlling and use authoritarian parenting styles because this style protects a

Psychosocial Development of Junior Hockey Players Psychosocial Development of Junior Hockey Players Alexander John Sturges Follow this and additional works at: https://researchrepository.wvu.edu/etd Recommended Citation Sturges, Alexander John, "Psychosocial Development of Junior Hockey Players" (2018). Graduate Theses, Dissertations, and Problem Reports. 7295. https://researchrepository.wvu.edu/etd/7295 This Dissertation is protected by copyright and/or related rights. It has been brought to you by the The Research Repository @ WVU with permission from the rights-holder(s). You are free to use this Dissertation in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you must obtain permission from the rights-holder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/ or on the work itself. This Dissertation has been accepted for inclusion in WVU Graduate Theses, Dissertations, and Problem Reports collection by an authorized administrator of The Research Repository @ WVU. For more information, please contact researchrepository@mail.wvu.edu. Psychosocial Development of Junior Hockey Players Alexander John Sturges Dissertation submitted to the College of Physical Activity and Sport Sciences at West Virginia University in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Sport & Exercise Psychology Edward Etzel, Ed.D., Chair Kristen Dieffenbach, Ph.D. Larry Lauer, Ph.D. Scott Barnicle, Ph.D. Department of Sport & Exercise Psychology Morgantown, West Virginia 2018 Keywords: Psychosocial development; adolescence; elite sport development; athletic identity Copyright 2018 Alexander John Sturges ABSTRACT Psychosocial Development of Junior Hockey Players Alexander John Sturges Junior hockey is an elite sport development model that impacts over twenty thousand adolescent male athletes each year. Participation in junior hockey commonly requires adolescents, 16 to 21 years of age, to move away from home, disrupt academic plans, and participate in an intense elite sport development model during critical developmental years. The influence of junior hockey on long-term psychosocial development is widely unknown. The present research measured developmental outcomes of college-enrolled former junior hockey player utilizing the Student Development Task and Lifestyle Assessment (SDTLA) and the Athlete Identity Measurement Scale (AIMS). Statistical analyses examined the impact of various measures of the junior hockey experience on measures of athletic identity and psychosocial development, with comparisons also being made to a representative population of male college students. Findings indicate junior hockey’s potential contribution to increased measures of athletic identity as well as delays in specific aspects of adolescent psychosocial development when compared to a normative population of male college students. Recommendations are provided for junior hockey shareholders towards improving the developmental outcomes associated with a junior hockey experience. iii Table of Contents Abstract ............................................................................................................................... ii Introduction ..........................................................................................................................1 Statement of Purpose .................................................................................................6 Primary Research Questions ......................................................................................7 Hypotheses .................................................................................................................7 Methods................................................................................................................................8 Introduction ................................................................................................................8 Theoretical Orientation ..............................................................................................8 Previous Research ......................................................................................................9 Research Design.......................................................................................................10 Sample inclusion criteria.....................................................................................10 Sampling procedure ............................................................................................10 Electronic surveys ...............................................................................................12 Data collection procedures ..................................................................................12 Sample size .........................................................................................................13 Statistical Analyses ..................................................................................................13 Research question 1 variables .............................................................................14 Research question 1: Junior hockey and athletic identity ...................................14 Research question 2 variables .............................................................................15 Research question 2: Psychosocial development compared to normative population ................................................................................................................................15 Research question 3 variables .............................................................................15 Research question 3: Athletic identity and psychosocial development ..............15 Summary ..................................................................................................................16 Results ................................................................................................................................17 Data Preparation.......................................................................................................17 Overview of Data Analysis ......................................................................................18 Demographic Characteristics of the Participants .....................................................19 iv Table 1: Number of participants by ethnicity .....................................................19 Table 2: Number of participants by age ..............................................................20 Table 3: Number of participants by class rank ...................................................20 Table 4: Number of participants by international student status ........................20 Table 5: Number of participants by current hockey status .................................21 Table 6: Number of participants by junior hockey years ....................................21 Table 7: Number of participants by number of JH teams played for ..................21 Table 8: Number of participants by school changes due to JH ...........................22 Table 9: Number of participants by residence changes due to JH ......................22 Table 10: Participant rating of “enjoyment” of junior hockey experience .........22 Table 11: Participant rating of “benefit” of junior hockey experience ...............23 Table 12: Descriptive statistics for participant AIMS scores .............................23 Table 13: Frequency distribution of participant AIMS scores............................23 Analysis of Research Question 1 .............................................................................23 Table 14: Bivariate correlation of AIMS and JH experience .............................24 Analysis of Research Question 2 .............................................................................24 Table 15: SDTLA subtask standard T scores by class ........................................25 Table 16: SDTLA task standard T scores by class .............................................26 Analysis: Research Question 3 ................................................................................26 Table 17: Multivariate analysis of the variance (AIMS and SDTLA)................26 Table 18: Test of between-subject effects ..........................................................26 Discussion .....................................................................................................................27 Introduction .........................................................................................................27 Research Question 1 Discussion .........................................................................28 Research Question 2 Discussion .........................................................................31 Academic autonomy subtask ........................................................................32 Instrumental autonomy subtask .....................................................................34 Salubrious lifestyle scale ................................................................................36 v Research Question 3 Discussion .........................................................................39 Summary of findings...........................................................................................40 Recommendations ...............................................................................................41 Limitations ..........................................................................................................43 Future Directions ................................................................................................45 Conclusion ..........................................................................................................47 Appendix A: Extended Review of the Literature ..............................................................48 Junior Hockey ..........................................................................................................49 Introduction to Junior Hockey ............................................................................49 Junior hockey history .....................................................................................49 Fundamental Experiences ........................................................................................53 Athlete relocation ................................................................................................53 Academic disruptions..........................................................................................54 New primary support system ..............................................................................58 Junior hockey structure .......................................................................................58 Junior hockey player rights ............................................................................60 Junior Hockey Culture .............................................................................................62 Deviance .............................................................................................................63 Alcohol and Substance use .................................................................................64 Positive junior hockey outcomes ........................................................................65 Enjoyment ......................................................................................................65 Junior Hockey Development System .......................................................................66 Long-term athlete development ..........................................................................66 Youth sport.....................................................................................................68 Elite sport development .................................................................................69 Sport mastery .................................................................................................70 Relative age effect..........................................................................................71 Perceptions of junior hockey ..............................................................................73 vi Summary of the Junior Hockey Experience ............................................................74 Adolescence .............................................................................................................76 Introduction to adolescence ................................................................................76 Problem behavior theory .....................................................................................78 Adolescent risk behaviors ...................................................................................79 Adolescent development .....................................................................................81 Athletic identity ..................................................................................................83 Adolescent transition ..........................................................................................84 Adolescent mobility ............................................................................................86 Educational mobility ......................................................................................88 Residential mobility .......................................................................................89 Homesickness ...........................................................................................90 Adolescent adjustment ...................................................................................91 Late adolescence .................................................................................................91 Developmental tasks ...........................................................................................93 Adolescent psychosocial development ...............................................................94 Psychosocial development in college .................................................................95 Non-traditional college students .........................................................................96 Student Development Task & Lifestyle Assessment ...............................................99 Uses of the SDTLA ...........................................................................................103 Athletic Identity Measurement Scale .....................................................................104 Uses of the AIMS..............................................................................................105 Research with the SDTLA and AIMS ...................................................................106 Summary ................................................................................................................107 Appendix B: Definition of Key Terms ............................................................................109 Appendix C: Basic Demographic Questions ...................................................................112 Appendix D: Athletic Identity Measurement Scale (AIMS) ...........................................114 Appendix E: Student Development Task and Lifestyle Assessment (SDTLA) ..............116 vii Appendix F: Participant Cover Letter ..............................................................................142 Appendix G: Participant Recruitment Email Templates .................................................144 Appendix H: Participant Follow-up Email Templates.....................................................146 Appendix I: Academic Autonomy Subtask Questions ....................................................149 Appendix J: Instrumental Autonomy Subtask Questions ................................................151 Appendix K: Salubrious Lifestyle Scale Questions ........................................................153 References ........................................................................................................................156 Introduction 1 Junior hockey is an elite sport development system providing athletic opportunities for over 20,000 participants annually. Selection to join a junior hockey team represents a watershed moment in a player’s career, as they are following in the footsteps of the many thousands of great professional players who taken the same path. The junior hockey system is widely celebrated across Canada and the United States as it is viewed as a shaper of men, a molder of professionals, and as a symbol of community prosperity and opportunity. However, despite its prominent role in advancing the careers of talented hockey players, little is known about the influence of this experience on adolescent psychosocial development. Junior hockey is unique compared with other mainstream North American sports in that it systematically challenges traditional academic, family, and social institutions. Furthermore, success in junior hockey is measured primarily through athletic outcomes (e.g. achieving a college scholarship or being drafted into the National Hockey League) and professionalized competitive forces hold substantial influence over the structuring of the system and therefore the experience for participants. Because of this, little attention is paid to the intricate process of adolescent development taking place throughout and after the junior hockey experience. To date, research on junior hockey has focused primarily on team and individual performance variables, and little work has been done to consider the potential impact of junior hockey on athletes moving through the system or transitioning to advanced developmental stages. The modern junior hockey system is rooted in the growth and professionalization of Canadian ice hockey throughout the 20th century (Kidd & MacFarlane, 1972). Junior hockey’s earliest form involved regional sponsors hosting local senior league teams that would compete for distinction across Canada and some Northern sections of the United States. Through the initial years of organized ice hockey, teams were stocked with local talent and embraced the 2 ideology of amateur competition (viewing sport as leisure instead of a legitimate vocational option). However, as the popularity of ice hockey grew, so did opportunities for money to be made by sponsors, promoters, and organizers. The introduction of new revenue streams and financial sponsorship led to private and community investments in larger, more spectator friendly arenas, as well as the recruitment and payment of hockey talent brought in to help teams win (Whitson & Gruneau, 2006). As the sport of ice hockey grew and elite professional leagues began to organize, top franchises needed a system of identifying and developing young talent to eventually play for their elite teams, and therefore began sponsoring junior organizations. Conceived as a stepping stone to the pro ranks, junior hockey embodies characteristics of professionalized sport, emphasizing performance and athletic advancement to serve the interests of professional sport organizers. From small-town beginnings, junior hockey expanded exponentially, evolving to ideally suit the needs of higher level programs making selections from the junior hockey talent pool. Through this growth, junior hockey has become a major financial and social institution, as well as a source of pride for many communities across the United States and Canada. The junior hockey landscape is diverse, involving over 600 registered teams in 60 different leagues. Although most leagues and teams are affiliated with national governing bodies of sport for either Canada or the United States, very little oversight or standardized regulation exists. Most of the operational and cultural norms of junior hockey are guided by traditions that have been passed down through generations of the sport, making junior hockey a unique but unifying experience for those who participate in the system. Despite diversity in locations, competitive levels, and offered resources of junior hockey teams and leagues, four fundamental components can be identified that encapsulate the lived experience for participants within the 3 junior hockey system. For the purposes of this study, these common factors have been established to conceptualize junior hockey and its key developmental influences. The four identified fundamental factors of junior hockey included: 1) athlete relocation, 2) new primary support systems, 3) academic disruption, and 4) the professionalized nature of the junior hockey environment. First, the full-time relocation of junior hockey participants is a long-accepted practice of junior hockey. Junior hockey relocation involves moving adolescents away from their immediate families, established peer groups, and familiar community support systems, and placing them in unfamiliar environments subject to forces of highly competitive sport. Advocates for junior hockey have historically embraced the process of athlete relocation and see it as a benefit to the cultural integration of the athlete to the sport (Mason, Duquette, & Sherer, 2005). However, the impact of youth athlete relocation and the environments participants are being asked to integrate into have not been critically examined. Junior hockey often represents an individual’s first experience living away from home. While relocation has long been viewed as a necessary step towards maturity, junior hockey’s lack of oversight, and inconsistent policy regarding relocation and housing make this fundamental process worthy of further examination. Second, physically relocating for junior hockey introduces personal challenges for participants as they are introduced to new towns and teammates to which they have limited if any social or emotional connection. This period of transition can have a range of behavioral and developmental consequences, including the formation of a strong emotional attachment with teammates, team personnel, and overall junior hockey culture (Finn & McKenna, 2010). Traditionally, the process for relocating junior hockey players involves the assignment of billet, 4 or host families (local families willing to house junior hockey players, often compensated by the team). Players live in their billet’s home, share meals and experiences, and even take responsibility for chores and helping around the house. Familiarizing with a billet’s rules and values can be a very impactful experience for junior hockey participants, especially because this may be their first experience living away from their own families (Dubé & Schinke, 2008). Junior hockey and its relocation practices have the potential to significantly impact an individual’s development by means of exposure to unique social and interpersonal challenges. The third feature of a junior hockey experience is the regular feature of academic disruption. Junior hockey participation typically occurs during the transition between high school and college. While many junior hockey players are required to maintain high school academic progress, players who have completed high school may not be enrolled in any schooling at all. While most current junior hockey teams and leagues encourage the continuation of academic progress, no enforceable guidelines exist, and no public data is available regarding individual or team academic progress. Furthermore, junior hockey requires a commitment to strenuous training and competition schedules, often conflicting with classes and/ or participation in the school environment (Koshan, 2004). Overall, the fundamental structure of junior hockey lacks congruency with the academic goals and interests of participants, and long-term consequences of this process remain widely unknown. The fourth fundamental experience of junior hockey is the professionalized approach in structuring this elite sport development system. Franchises and leagues are privately funded, and their primary purpose is to serve the financial interests of management and ownership groups, who yield substantial power and influence (Whitson & Gruneau, 2006). Teams are not required to make long-term commitments to players, despite holding considerable control over their hockey careers. Players can be cut or traded at any time based on subjective performance 5 standards, and franchises that fail to produce financial viability can fold or relocate, even after a single season. This instability contributes to a competitive, high-pressure environment that is found consistently throughout junior hockey’s varying levels. Overall, junior hockey’s competitive structure, together with required relocation, and social and academic disruptions represent four foundational factors that are found at all levels of junior hockey and have strong developmental implications. Junior hockey occurs during the developmentally dynamic stage of adolescence. Adolescence is a period of intense change and identity exploration in which numerous meaningful developmental challenges must be overcome (Steinberg & Morris, 2001). Along with the challenge of establishing a stable and authentic sense of self-identity, adolescents also must navigate social interactions of ever-increasing complexity and significance. Normative adolescent development also calls for the healthy formation of career ambitions, ability to form proper interpersonal relationships, and to solidify oneself as an autonomous feature of the environment (Demos & Demos, 1969; Eccles et al., 1993). Taking into consideration the timing and potential intrusiveness of the junior hockey experience, an established understanding of the influence of junior hockey on adolescent development is crucial. The transition from high school to college is a well-documented developmental process that has a significant impact on the lifespan trajectory of individuals. Development within the college environment is seen as constant, cumulative, and occurs on a continuum that can provide insight as to potential developmental outcomes (Winston, Miller, & Cooper, 1999). Research in this domain has identified specific developmental tasks associated with proper psychosocial development. Chickering and Reisser’s (1993) seven developmental vectors (which include developing competence, interdependence, mature interpersonal relationships, emotional 6 management, sense of purpose, and integrity) have played a major role in shaping the accepted notion of appropriate college student development. The unique demands placed by junior hockey on academic progress produces many non-traditional college students, a population known to adapt differently to the college environment, and therefore may require specialized programming and accommodations (Macari, 2003). Given the long-term developmental significance of the college and university, factors that influence this experience are worthy of inquiry. Overall, the presence of junior hockey in key transitional periods of adolescence, as well as its potential influence on the transition to the college setting, emphasizes the importance of research on the development of individuals participating in this system. Statement of Purpose The present study explored the psychosocial development of college-enrolled former junior hockey players. The study also examined long-term developmental implications of junior hockey and offers recommendations to improve programming and participant experiences. Junior hockey is unique from other major sport development structures in North America in its scale (over 20,000 annual participants) and its cultural norms, (e.g., expected participant relocation) which actively disrupt sources of adolescent stability and support. Junior hockey’s intense and professionalized system influences participants lives during a developmentally sensitive period in which the formation of a stable and secure identity is a primary feature. Furthermore, the role of junior hockey in normalizing the delay of college enrollment as well as its potential influence on college selection may play a role in altering the college experience and potentially in subsequent development. Overall, the present study examined the influence of junior hockey on identity formation and subsequent psychosocial development in the college 7 setting. Primary research questions The following three research questions were developed to address the primary purpose of the study and to guide the methodology: 1. What is the relationship between measures of junior hockey participation and measures of athletic identity in college-enrolled former junior hockey players? 2. In what ways does junior hockey participation influence measures of psychosocial development when compared to the normative sample population of male college students? 3. Are measures of athletic identity predictive of measures of psychosocial development in a population of college-enrolled former junior hockey players? Hypotheses The following represent the three primary research hypotheses, although methodology tested null hypotheses. 1. Measurements of junior hockey participation are related to measurements of athletic identity in college-enrolled former junior hockey players. 2. Junior hockey participation influences measurements of psychosocial development when compared to a normative sample population of college students. 3. Measurements of athletic identity are predictive of measurements of psychosocial development in college-enrolled former junior hockey players. Methods 8 Introduction The selected methodology examined the relationship between the junior hockey experience and developmental processes in a sample of college-aged, former junior hockey participants utilizing the collection and analysis of data from validated measurements of athletic identity and psychosocial development. Two primary measurement instruments were featured: The Athletic Identity Measurement Scale (Brewer, Van Raalte & Linder, 1993) to measure participant athletic identity, and the Student Development Task and Lifestyle Assessment (Winston, Miller, & Cooper, 1999) to measure aspects of psychosocial development within the college setting. The following chapter outlines the selected research parameters and methods of statistical analysis applied to address the primary research questions pertaining to the developmental impact of junior hockey. Theoretical underpinnings, data collection procedures, and aspects of research integrity are also discussed. Theoretical Orientation The present research adopted a positivist theoretical stance. A positivist perspective aims to test a theory or describe a unique experience through observation and measurement to establish the ability to predict and/ or control a phenomenon (Campbell & Stanley, 1963; Mackenzie & Knipe, 2006). A positivist perspective also assumes that observable phenomena are knowable through empirical and reductionist scientific inquiry, and that methodology should be constructed with precision and detail so that experimental conditions can be replicated by other researchers (O’Leary, 2004). Concepts of psychosocial development and athletic identity have generally agreed upon definitions previously established through the literature. However, concrete understanding of these topics is an ongoing and fluid process, as evidenced by the 9 varied theoretical positions and continued empirical work expanding to new and emerging contexts (Shutte & McNeil, 2015; Gucciardi, 2017; Hardy et al., 2017). The present research contributes to the literature by focusing on a specific realm of elite sport development system (junior hockey) and its potential impact on aspects of adolescent psychosocial development. Previous Research A pilot study utilizing an electronic version of the SDTLA on a sample of college enrolled former junior hockey players was conducted by the principal investigator, testing the appropriateness of this methodology. SDTLA and demographic data was collected from a convenience sample of 45 male college students with varying levels of junior hockey experience. Participant scores were compared to the normative population of male college students on each developmental task. Results showed that standard scores produced by former junior hockey players were significantly lower on tasks of developing mature interpersonal relationships and establishing autonomy. Results were consistent with developmental principles proposed by Chickering and Reisser (1993) that college students display psychosocial development through time spent in college (scores for freshman were typically lower than seniors). Furthermore, the pilot study results suggested that junior hockey has a potential impact on former participants’ ability to successfully transition and display appropriate psychosocial development in the college setting. Results of the pilot study generally supported the need for more research on the topic of psychosocial development on this population. Research Design The present study utilized a descriptive, correlational research design to address the 10 research questions. Descriptive correlational design refers to research in which the size and direction of a relationship between variables is observed, however no direct attempt is made to control for or randomize participant experience (Shadish, Cook & Campbell, 2002). Descriptive correlational research evaluates connections between various behavioral outcomes and illuminates potential paths of inquiry that may provide a deeper understanding of the observed phenomenon (Lappe, 2000). Correlational designs are well-suited for studies that apply validated measures to novel contexts, especially when the observed behaviors are social and exploratory in nature. Furthermore, descriptive data collection can help formulate new research questions or guide future research (Anderson, 1998). Sample inclusion criteria. College-enrolled males with experience playing junior hockey, whether they are still competing in the sport or not, were eligible to participate. The construct of junior hockey experience was defined (for this study) as time spent within any level of junior hockey for any duration of time. Participants were required to be currently enrolled in a college or university continuously for at least four weeks to ensure adequate acclimation to the environment (Winston, Cooper, Miller, 1999). Participants also had to be at least 18 years of age. No additional participant exclusion criteria regarding race, ethnicity, or nationality were featured. Sampling procedure. The present study utilized non-probability purposive sampling. Purposive sampling, the deliberate choice of participants based on inherent characteristics, best meets the goals of the study in understanding a specific population through a theoretical framework (Tongco, 2007). Presently, no collective database of former junior hockey players exists, and therefore purposive sampling allows for data to be collected from the desired population in a timely manner (Battaglia, 2008). Participant contact information was accessed by networking with hockey shareholders 11 willing to provide contact information of potential participants. Current and former junior and collegiate hockey coaches/ organizers were contacted through email and phone to discuss possible inclusion of former junior hockey player contacts. Snowball sampling was also used in limited cases in which participants were willing to connect other individuals within their network to the research study (Goodman, 1961). Electronic correspondence in the form of email was established directly with potential participants, or indirectly through a coach/ organizer. This initial contact was followed by delivery of an anonymous and unique access code for the testing instrument (See Appendix F, G, & H for email correspondence templates). One initial email, and two follow-up emails were distributed individually to all participants to maximize survey completion (McPeake, Batterson & O’Neill, 2014). Limitations to this method of participant recruitment included: a) potential selection bias (Ahern, 2005) towards successful junior hockey players (indicated by actualized opportunities to continue competing after junior hockey), b) surveying of a potentially non-representative sample (Jones, Murphy & Edwards, 2008) through exclusion of junior hockey participants who do not continue on to college, c) non-randomized participant sampling (Reeves, Deeks, Higgins & Wells, 2008) and d) potential for lower response rates (Robson, 2011) due to the format of the survey instrument. To counteract bias and establish trustworthiness, connections were established with as large and diverse a population of former junior hockey participants as possible, and specific inclusion/ exclusion criteria were followed to increase the generalizability of findings (McPeake, Batterson & O’Neill, 2014; Higgins et al., 2013; Hopkins, Marshall, Batterham & Hannin, 2008). 12 Electronic surveys. Electronic surveys were utilized for data collection. Online surveys can be an effective data collection tool that yield meaningful responses regarding a phenomenon within a specific target population with near universal internet access (Crawford, Couper & Lamias, 2001; Aldridge & Levine, 2001; Creswell, 2003). Electronic surveying has been found to be a reliable and efficient way to reach a large proportion of the sample population and is considered a valid form of data collection (Schleyer & Forest, 2000). For the present study, use of electronic surveying allowed for the most convenient data collection procedure, reaching the maximum possible sample population. Both the SDTLA and the AIMS are approved and validated for use in electronic form by their authors (Winston, Milller & Cooper, 1999; Brewer, Van Raalte & Linder, 1993). Furthermore, both the SDTLA and AIMS have been successfully utilized in online versions in research settings with similarly aged populations (Coe-Meade, 2015; Turton, Goodwin, & Mayer, 2017; Wisdom, 2006). Benefits of employing these measures in an online format include ordered presentation of questions, reduction of non-responses, increased convenience for participants, lower cost, and faster data analysis (Aldridge & Levine, 2001; Granello & Wheaton, 2004). Data collection procedures. Prior to data collection, approval was obtained from the West Virginia University Institutional Review Board for the Protection of Human Subjects to ensure ethical protection of all participants. Study procedures, outline of participant rights, and informed consent were presented to participants for approval prior to accessing the survey instrument. The full survey instrument (see Appendices B, C, & D) was administered to participants utilizing the Qualtrics software platform (Qualtrics, Provo, UT). Each participant received a unique and anonymous link to the instrument that was accessed at their convenience. All possible efforts 13 were made to ensure confidentiality and minimize collection of identifying information through the survey instrument, and no identifying information as included in data analysis proceedings. Data was secured and accessible through one password protected account, only accessible to the researcher. Downloaded data sets were stored on a password protected computer. Sample size. Data collection remained open until desired sample size was reached. Estimates utilizing the GPower software suite (Faul, Erdfelder, Lang & Buchner, 2007) indicated that for a low-to-medium effect size, with power set at .95, and a .05 Pearson’s coefficient, that approximately 210 participant responses would be required to obtain significant results. Desired sample size has further been determined through recommendations from similar studies as well as parameters in the literature regarding appropriate sampling procedures (Bartlett, Kotrlik & Higgins, 2001). Statistical Analyses Statistical analysis of the data was conducted in three separate steps and addressed each research question individually. All data analyses were conducted through the SPSS statistical software suite (SPSS Inc.) and Microsoft Excel. First, participant scores on the AIMS and SDTLA were calculated as defined by official assessment manuals and published data calculation procedures. Prior to conducting any statistical analyses, the data set was examined for missing/ incomplete responses, and multicollinearity (Schroeder, Lander & Levine-Silverman, 1990). Cook’s distance measure was conducted to test for and remove unduly influential outliers in the data set. In addition, SDTLA task and subtask data missing more than 12% of responses were not included in the data analysis, as recommended by the authors (Winston, Miller, & Cooper 1999). AIMS measures missing any of the seven question responses were also excluded (Brewer, Van Raalte & Linder, 1993). Participant total scores on the AIMS were reflected by a 14 cumulative score of the seven answered questions, ranging from a minimum of 7 to a maximum of 49. Scores on each of the SDTLA’s five tasks/scales were converted to standard scores, allowing individual scores to be compared to the normative population. Research question 1 variables. Research question one examined the relationship between junior hockey experience and athletic identity. To address this question, two demographic variables and two questions related to perceived enjoyment and benefit of the junior hockey experience were collected through the survey instrument and served as independent variables. The four independent variables included: a) number of years of junior hockey participation, b) number of junior hockey teams played for, c) “I enjoyed my junior hockey experience”, and d) “junior hockey was beneficial to my college experience”. The two questions regarding perceived enjoyment and benefit of the junior hockey experience were scored on five-point Likert scales. The dependent variable was represented by cumulative athletic identity scores assessed by the AIMS, ranging from 7 to 49 (Brewer, Van Raalte & Linder, 1993). Research question 1: Junior hockey experience and athletic identity. Research question one addressed the relationship between measures of junior hockey participation and the athletic identity measurement scale (Brewer, Van Raalte & Linder, 1993). Junior hockey experience was measured by four variables; number of years played, number of teams played for, and rating of perceived enjoyment and benefit. Pearson product correlation coefficient, r, was calculated to determine the relationship between two key demographic variables (i.e., years in junior hockey and number of teams played for) and athletic identity. Bivariate correlations are used to assess the degree of relationship between two continuous variables (Tabachnick & Fidell, 2001). Results of this test are intended to assess the relationship between athletic identity and factors associated with junior hockey experience, including years played, and number of teams played 15 for, and ratings of perceived enjoyment and benefit. Research question 2 variables. Research question two examined the relationship between college-aged former junior hockey players and non-junior hockey playing college students on measures of psychosocial development through the SDTLA (Winston, Cooper, & Miller, 1999). Comparisons were drawn between former junior hockey players and a normative population of male college students categorized by academic class standing. Between each academic class standing (freshman, sophomore, junior, and senior), four developmental measures of psychosocial development were assessed. The four SDTLA tasks/ scales included; a) academic autonomy, b) mature interpersonal relationships, c) clarifying sense of purpose, d) salubrious lifestyle scale. Research question 2: Psychosocial development compared to normative population. Research question two examined the relationship between psychosocial development in former junior hockey players in comparison to normative scores for male college students. Participant SDTLA data was stratified based on academic class standing to allow for comparison to normative data. Comparisons of converted T-scores were conducted between participant SDTLA task and subtask scores with normative sample population scores provided by the authors. This comparison determined if mean score on specific tasks for the research sample were significantly different than established norms for male college students (Tambachnick & Fidell, 2001). Research question 3 variables. Research question three examined the relationship between psychosocial development and levels of athletic identity in former junior hockey players. To address this question, participants were stratified according to their AIMS scores into low, medium, and high athletic identity groups. The middle group was formed based on +/- 0.5 16 standard deviation from the sample mean. High athletic identity was represented by scores more than 0.5 standard deviations above the sample mean, and low athletic identity was represented by scores more than .05 standard deviations below the sample mean. The research question was addressed by comparing the stratified groups of athletic identity (measured through the AIMS), with participant aggregate scores on the Student Development Task & Lifestyle Assessment (SDTLA) for the established primary developmental tasks. Research question 3: Athletic identity and psychosocial development. Participants were stratified according to their AIMS scores into low, medium, and high athletic identity groups. The middle group was formed based on +/- 0.5 standard deviation from the sample mean. High athletic identity was characterized by scores more than 0.5 standard deviations above the sample mean, and low athletic identity was characterized by less than scores more than .05 standard deviations below the sample mean. The stratified groups of AIMS scores were used as independent variables and run in a one-way Multivariate Analysis of Variance (MANOVA), testing mean differences between athletic identity and the four scales/ task measures of the SDTLA (Tabachnick & Fidell, 2001). This test explored the predictive value of athletic identity scores and specific aspects of psychosocial development in college-enrolled former junior hockey players. Summary The present methodology was determined to be the best means to address the primary research questions based on a thorough empirical review of the literature. The methodology addressed the examined relationships between junior hockey experience, athletic identity, and psychosocial development in a college-aged population. The sample population was defined as college enrolled former junior hockey players, having been in college for at least four weeks. The electronic survey instrument for this study included demographic questions, the AIMS, and the 17 SDTLA. Data analyses was conducted to make comparisons between the data sets and to address the three primary research questions outlined previously. Responsible and ethical research practices were observed as defined by the Institutional Review Board, and participant rights to confidentiality were enforced throughout the data collection and analysis process. Results Data Preparation Data collection conducted through the Qualtrics online platform was closed when pre determined sampling thresholds were reached. From a potential audience size of 563 participants, 344 participants accessed the survey and 258 surveys were submitted (75% completion rate for surveys opened by participants). Collected data was converted and downloaded through Qualtrics to SPSS v.25 for analysis. All remaining identifying information was removed from the data set in preparation for analysis. In addition, score adjustments for individual items were entered according to the published SDTLA scoring key before scale, subtask, and task scores were calculated. Following a preliminary review of participant data, specific factors were determined to be grounds for removing cases from the data set. Total sample size progressed through three adjustments based on the requirements of each of the three research questions. For research question one, participants were removed if they did not indicate having any junior hockey experience (based on years played or teams played for). Graduate students (N=10) were also removed from the sample prior to analysis. A final exclusion criterion implemented prior to analysis for research question one involved the SDTLA response bias scale. The SDTLA includes a six-item response bias scale within the instrument, through which the authors recommend removal of participant scores on this scale equal to or exceeding 3 of a possible 6 18 (Winston, Miller, & Cooper, 1999). Although research question one did not involve the SDTLA instrument, the indication of a high participant social desirability rating was determined to be a threat to AIMS and demographic measurements, both administered at the same time as the SDTLA. Analysis for research question one included N=215 participants. The data set from research question one was established then adjusted in preparation for analysis with research question two. Exclusion criteria for this question included participant responses that fell below 75% completion due to their inability to provide complete SDTLA task or subtask scores. Although the authors of the SDTLA provide instructions for customized scoring of assessments with missing data, it was determined that all participants would be scored the same. If a participant’s subtask or subsequent task score was incomplete, that measure was excluded in the final analysis. Surveys with 75%-100% completion were retained for analysis only on task/ subtasks where all required items were completed, and scores were able to be calculated. Analysis for research question two included N=203 participants. One final exclusion criterium was utilized for research question three. Incomplete participant responses (below 100%) were not included in the MANOVA analysis, which reduced the sample to N=199 participants. Overview of Data Analysis The purpose of the study was to investigate the impact of junior hockey participation on identity formation and psychosocial development in a population of college-enrolled former junior hockey players. Research question one was examined by running bivariate correlations between junior hockey experience (as measured by years of junior hockey played, number of junior hockey teams played for, and personal ratings of enjoyment and benefit) and athletic 19 identity (as measured by the seven item AIMS). Research question two was addressed by comparing differences on standardized scores between former junior hockey players and the norm sample population on task and subtask measures of the SDTLA. Research question three was addressed through mean score comparisons of task measures of psychosocial development through the SDTLA and athletic identity scores as measured by the AIMS. The following results are presented in this chapter: (a) description of participants, (b) description of AIMS scores, (c) description of SDTLA task and subtask scores, and (d) the results of a one-way multivariate analysis of variance (MANOVA). Demographic Characteristics of the Participants The utilized sample population was comprised of 215 college-enrolled former junior hockey players. All participants were male and over the age of 18. The average participant was 22 years old. Demographic summaries of ethnicity, age, class rank, and international status are provided in tables 1-4. Table 1 Number of Participants by Ethnicity Ethnicity Label White Black American Indian or Alaskan Native Asian Native Hawaiian or Pacific Islander Hispanic RQ1 207 1 0 5 1 1 RQ2 196 0 0 5 1 1 RQ3 192 0 0 5 1 1 Totals (N) 215 203 199 20 Table 2 Number of Participants by Age Age RQ1 RQ2 RQ3 19 5 4 4 20 29 27 27 21 43 41 39 22 57 55 54 23 41 39 38 24 24 23 23 25 9 8 8 26 1 1 1 27 1 1 1 Totals (N) 215 203 199 Mean age = 22 *Five participants did not register age information Table 3 Number of Participants by Class Rank Class Rank RQ1 RQ2 RQ3 Freshman 42 40 38 Sophomore 57 51 51 Junior 61 59 58 Senior 55 53 52 Totals (N) 215 203 199 Table 4 Number of Participants by International Student Status Classification RQ1 RQ2 RQ3 International Student 36 35 35 Not International Student 179 168 164 Totals (N) 215 203 199 Hockey Experience. Demographic information pertaining to experience within the sport of hockey was measured through self-reported current hockey status (level of participation), number of years spent playing junior hockey, number of junior hockey teams played for, number of school changes due to junior hockey, and number of residence changes due to junior hockey. 21 Two additional questions were included regarding participant perception of enjoyment and benefits of their junior hockey experience (“I enjoyed my junior hockey experience”, and “junior hockey was beneficial to my college experience”). These questions were scored on five-point Likert scales ranging from “strongly disagree” to “strongly agree”. Frequency and mean scores for these questions are provided in Tables 5-11. Table 5 Number of Participants by “Current Hockey Status” Status RQ1 RQ2 RQ3 Competing in college (NCAA/ CCAA level) 114 113 112 Competing in college (Club level) 94 84 82 Participating in college (rec./ intramural) 3 2 1 Not participating in hockey 4 4 4 Totals (N) 215 203 199 Table 6 Number of Participants by “Junior Hockey Years” Years RQ1 RQ2 RQ3 0-1 22 19 19 1-2 74 71 69 2-3 54 49 49 3-4 42 41 39 4-5 23 23 23 Totals (N) 215 203 199 Mean years = 2.9 Table 7 Number of Participants by “Number of JH Teams Played For” Teams RQ1 RQ2 RQ3 1 76 71 70 2 64 60 60 3 38 36 34 4 20 20 20 5 17 16 15 Totals (N) 215 203 199 Mean number of teams = 2 22 Table 8 Number of Participants by “School Changes Due to JH” Changes RQ1 RQ2 RQ3 0 7 6 6 1 97 92 91 2 64 61 60 3 24 23 23 4 18 16 14 5 5 5 5 Totals (N) 215 203 199 Mean school changes = 1.8 Table 9 Number of Participants by “Residence Changes Due to JH” School Changes RQ1 RQ2 RQ3 0 1 1 1 1 51 47 46 2 38 36 36 3 44 42 42 4 37 34 33 5 44 43 41 Totals (N) 215 203 199 Mean residence changes =2.9 Table 10 Participant Rating of “Enjoyment” of Junior Hockey Experience RQ1 RQ2 RQ3 Strongly disagree 2 2 1 Somewhat disagree 5 5 5 Neither agree nor disagree 10 9 9 Somewhat agree 55 49 48 Strongly agree 143 138 136 Totals (N) 215 203 199 Table 11 Participant Rating of “Benefit” of Junior Hockey Experience RQ1 RQ2 RQ3 23 Strongly disagree 2 2 1 Somewhat disagree 5 4 4 Neither agree nor disagree 17 15 15 Somewhat agree 44 43 42 Strongly agree 147 139 137 Totals (N) 215 203 199 Participant frequency scores and descriptive statistics for the AIMS are provided in Tables 12-13. Table 12 Descriptive Statistics for Participant AIMS Scores N Min Max Mean SD RQ1 215 18 49 40 5.4 RQ2 203 18 49 40 5.4 RQ3 199 21 49 40 5.2 Table 13 Frequency Distribution of Participant AIMS Scores AIMS Score RQ1 RQ2 RQ3 18-21 2 2 1 22-25 1 1 1 26-29 8 6 6 30-33 18 13 13 34-37 32 28 27 38-41 76 61 60 42-45 65 60 59 46-49 37 32 32 Totals (N) 215 203 199 Analysis: Research Question One Research question one addressed the relationship between the athletic identify (measured by the AIMS) and junior hockey experience (measured by years spent in junior hockey, number of teams played for, and personal perception of benefit and enjoyment of the experience). Because junior hockey experience was a requirement for participation in this study, the lowest value for participation was one year (i.e., participant years included time spent up to or equaling that number). Significant positive correlations were observed between AIMS score and the 24 variables representing time, perceived enjoyment, and perceived benefit. Bi-variate correlation results are presented in Table 14. Table 14 Bivariate Correlation: AIMS and Junior Hockey Experience Time (years) AIMS .2* Pearson Correlation Sig. (2-tailed) Sum of Squares and Cross products .004* 260.2 # of teams “Enjoyable” .083 .228 117.7 .2* .003* 176.1 “Beneficial” .18* .009* 166 N = 215 Significance marked at the .05 level. Analysis: Research Question Two Data collected for the SDTLA was sorted by current academic standing and then converted into standard scores according to the published scoring instrument provided by the SDTLA authors. Means and standard deviations derived from the normative sample population were used to compute individual standard T scores for each participant for each sub-scale and scale of the SDTLA. The purpose of converting participant raw scores to T scores was for comparison to the normative sample population, represented as 50 for each category. Participant scores .5 standard deviations above or below the published norm (+/- 5) are considered significant findings according to the SDTLA technical manual (Winston, Brewer, & Cooper, 1999). Average scores for each academic class standing are presented below (See Table 15). Analyses revealed significant differences between the sample population and the norm in two subtask categories and on the Salubrious Lifestyle Scale. On the Academic Autonomy subtask, sophomores, juniors, and seniors scored below the published norms. For the 25 Instrumental Autonomy subtask, scores for sophomores also fell below the expected range, while scores for the other three class ranks neared falling significantly below. Both subtasks containing significantly lower participant scores fell within the Developing Autonomy Task. Table 15 SDTLA Subtask Standard T Scores by Class Class Career Purpose Tolerance Peer Relationships Lifestyle Planning Cultural Participation Educational Involvement Academic Autonomy Interdepende nce Instrumental Autonomy Emotional Autonomy FR 48.1 51.4 46.5 49.1 54.8 45.2 46.4 48.8 45.3 50.9 SO 46.3 47.1 46.7 46.4 53.9 46.3 43.9* 48.9 44.3* 48.3 JU 46.5 49.7 46.3 50.0 52.1 45.7 43.4* 49.1 45.1 52.0 SR 46.1 50.6 46.0 47.2 53.4 48.2 44.5* 47.7 45.7 51.7 * Indicates score >.5 +/- standard deviations from the normative sample Significant differences were also found in the Salubrious Lifestyle Scale, one of the instruments primary measurements (See Table 16). Cumulative scores from Freshman and Seniors on this measure fell below the expected range. Table 16 SDTLA Task Standard T Scores by Class Class FR SO JU SR Salubrious Lifestyle Scale 43.1* 48.2 48.3 44.7* Establishing and Clarifying Purpose Task 47.9 47.7 46.9 48.1 Mature Interpersonal Relationships Task 50.1 45.8 49.6 48.2 Developing Autonomy Task 47.3 45.9 47.3 47.1 * Indicates score >.5 +/- standard deviations from the normative sample 26 Analysis: Research Question Three AIMS scores were categorized to “high”, “medium” and “low” according to +/- 0.5 standard deviation from the mean to test variance of the SDTLA model in relation to athletic identity. Table 17 shows the results of the one-way MANOVA conducted. Wilks’ Lambda and F values were not found to be significant. A subsequent between-subjects test of the AIMS categories and the SDTLA tasks did not yield significant values. F scores for the Clarifying Purpose and Salubrious Lifestyle Scale neared significance (See Table 18). However, these findings were not maintained when controlling for differences attributed to class rank within the model. Table 17 Multivariate Analysis of the Variance (AIMS and SDTLA) Value F df Error Sig. Power AIMS Rank Wilks' Lambda .96 1.2 8 386 .39 .5 N=199 Table 18 Test of Between-Subject Effects DV SS df F Sig. Power AIMS AUT 23.9 2 .514 .599 .13 SAL 153.1 2 1.617 .201 .34 PUR 392.9 2 3.25* .041* .62 MIR 10.7 2 .420 .658 .12 N=199 Discussion 27 Introduction Junior hockey is an influential sport development system that impacts thousands of adolescent hockey players prior to their developmental transition to college and early adulthood. Despite the size of this system (approximately 20,000 annual participants in 250 teams in 40 leagues across North America), very little work has been done to understand the effect of a junior hockey experience on participants. Unique from other sport development models, junior hockey embraces a series of non-traditional organizational norms, including the requirement of participants to move away from home, change schools, and alter educational trajectory. Thus, the purpose of the present research was to better understand developmental outcomes of a junior hockey experience through measurements of athletic identity and psychosocial development in a population of college-enrolled former junior hockey players. Research Question One Discussion Research question one hypothesized that the junior hockey experience would influence the amount of athletic identity reported by former junior hockey participants. Junior hockey experience was represented by time spent (in years) within the system, number of teams played for, as well as personal reflection on enjoyment and benefits of the junior hockey experience. The hypothesis was partially supported, as significant positive correlations were found in self reported “time spent” (r = .2), ratings of personal enjoyment (r = .2), and ratings of perceived benefit of junior hockey (r = .18) yielded a significant correlation of at the .01 level. Number of teams played for was not significantly correlated with scoring on the AIMS. These findings indicated that more time spent in junior hockey is associated with the greater athletic identity 28 formation when transitioning

Coaching life skills through sport: An application of the teaching personal and social responsibility model to youth sport in eSwatini Coaching life skills through sport: An application of the teaching personal and social responsibility model to youth sport in eSwatini Zenzi Huysmans zehuysmans@mix.wvu.edu Follow this and additional works at: https://researchrepository.wvu.edu/etd Part of the Other Psychology Commons, and the Sports Studies Commons Recommended Citation Huysmans, Zenzi, "Coaching life skills through sport: An application of the teaching personal and social responsibility model to youth sport in eSwatini" (2018). Graduate Theses, Dissertations, and Problem Reports. 3717. https://researchrepository.wvu.edu/etd/3717 This Dissertation is protected by copyright and/or related rights. It has been brought to you by the The Research Repository @ WVU with permission from the rights-holder(s). You are free to use this Dissertation in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you must obtain permission from the rights-holder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/ or on the work itself. This Dissertation has been accepted for inclusion in WVU Graduate Theses, Dissertations, and Problem Reports collection by an authorized administrator of The Research Repository @ WVU. For more information, please contact researchrepository@mail.wvu.edu. Coaching life skills through sport: An application of the teaching personal and social responsibility model to youth sport in eSwatini Zenzi Huysmans, M.S. Dissertation submitted to the College of Physical Activity and Sport Sciences at West Virginia University in partial fulfillment of the requirements for the degree of Doctorate of Philosophy in Kinesiology with a Major in Sport, Exercise, and Performance Psychology Sport and Exercise Psychology Damien Clement, Ph.D., Chair Sam Zizzi, Ed.D. Christiaan Abildso, Ph.D., MPH Meredith Whitley Ph.D., Adelphi University Department of Sport Sciences Morgantown, West Virginia 2018 Keywords: youth development, life skills, coaching, teaching personal and social responsibility model, eSwatini Copyright 2018 Zenzi Huysmans Abstract Coaching life skills through sport: An application of the teaching personal and social responsibility model to youth sport in eSwatini Zenzi Huysmans Adolescence is a formative developmental period where youth learn the life skills and values needed to become compassionate and civically-engaged young people and navigate increasingly challenging global environments. Youth in eSwatini face major context-specific challenges that impede their healthy development as well as limited engagement with government initiatives intended to support their development. This feasibility study aimed to employ youth sport as a creative and engaging context to facilitate life skills development in underprivileged youth in eSwatini. Specifically, this study explored the youth participation experiences, positive youth outcomes, and implementation successes and challenges of a sport program for underprivileged youth in a community in eSwatini. The sport program was designed using the teaching personal and social responsibility (TPSR) model, which is a well-established instructional model for life skills education through sport. Although this model had been widely applied in Western contexts, the current study explored how the model might operate differently in a non-Western context where youth face different developmental challenges. An intervention design was employed to implement a three-week sport program for youth in a small community in the Lobamba region of eSwatini. Local coaches were the primary implementers of the program and participants were youth (N=33), aged 11-15 years old, who attended the grade six and seven literacy development afternoon club at a community-based children’s organization. Findings from the current feasibility study provided further support for the value of using the TPSR framework in the design and implementation of sport-based life skills education programming in a novel youth context in eSwatini. The focus of the model on building caring coach-youth relationships, creating an enjoyable sport experience, fostering small successes, and providing intentional opportunities for youth to actively practice and engage in their own learning were the most meaningful elements of the model in the current youth context. The developmental outcomes and changes in life skills associated with participation in the current program may also be highly pertinent to helping youth navigate the most salient health and resource challenges in the community. Notably, the current study also identified culture and context-specific considerations that should be made when implementing TPSR-based youth programming in eSwatini. These included, but are not limited to, adaptations to the awareness talk and self reflection time, the use of active learning strategies and behavioral management techniques, and the provision of fruit and food to meet basic survival needs. Continued future explorations of the program design elements and coaching strategies that most meaningfully contribute to a holistic youth development and a positive sport participation experience in eSwatini is warranted. Acknowledgements iii Traveler, the path is your tracks And nothing more Traveler, there is no path The path is made by walking - Antonio Machado – It takes a village to raise a child and I have had so many supporting hands help me get to this point. To the family, friends, and community in eSwatini who believed in me from the very beginning, “I am because we are”. What a beautiful thing to have been shaped by so many kind hearts over the years. Siyabonga kakhulu! To the children of the Moya Center, the staff, and the coaches who helped me bring this dissertation to life. It was an immense privilege to develop this program alongside you all. You are the reason why I do what I do. To the community members, key informants, coaches, and students who participated in the needs assessment that grounded this dissertation, thank you! Your voices are present in every chapter of this dissertation story! To my wonderful SEP colleagues. As the African proverb says, “If you want to go fast, go alone, if you want to go far, go together.” We have journeyed far together…and what an adventure it has been! Over the years we have shared so many moments of laughter and joy, and also experiences of sadness and challenge. In those difficult times, your support and kindness have meant everything to me. I will cherish both; the deep belly laughter and also the compassion you have shown me! Thank you! Matt and Tammy…not all heroes wear capes! Thank you for investing yourselves so fully in the coding process of my dissertation. Your enthusiasm and dedication to my work was a beautiful thing to witness. To the SEP and Counseling faculty members and my dissertation committee. I have been lucky to grow both personally and professionally under the wings of such compassionate, dedicated, and pioneering people. Dr. Clement: over the years you have pushed me to become the best possible version of me. You have supported my independence while also reaching out a helping hand when I needed it. Dr. Zizzi: You have helped me trust my way of being and enjoy the journey as it unfolds. Your kindness has been so appreciated. Dr. Etzel: it has meant more than you know to journey around the world with you through our chats about music, books, recipes, and life experiences. Thank you for trusting and nurturing my vision for consulting when I was still searching for my professional identity. Dr. Whitley: You have dedicated your life’s work to using sport as a platform for the positive and holistic development of youth all over the world. Your passion and work ethic is truly an inspiration. I hope to emulate that in my own professional journey. Dr. Abildso: Thank you for taking a leap with me. I look forward to continuing to explore the intersection of sport and community-based public health programming under your mentorship. To my dearest friends, you are my heart and soul connections for life! The greatest gifts of life are friendships, and I have been blessed with some truly beautiful ones. See you in eSwatini one day! Killeen, it’s hard to describe how you have impacted my life. In some of my most difficult iv moments of challenge, you were an unwavering presence. You give to everyone around you so selflessly. I feel privileged to have shared this chapter with you, to have watched your continued growth into a strong, compassionate, and balanced woman. Aaron. Morgantown will always be synonymous with you. Your way with people is something that will stick with me. You have an incredible ability to connect with others and make everyone you meet feel valued. Thank you for giving me a space to share the contents of my heart. Sofia, in you I have found a kindred spirit. A playful, optimistic, and deeply values-oriented soul. Thank you for the light you have brought to my life! Jay. Your determination and resilience have been pillars for me. Challenge upon challenge has been thrown your way and you have stepped up to the plate every time. Please know that even when you feel alone in those experiences, you are shaping the lives of those who are watching your fighting spirit. Thank you for all the laughter and roasts. I have met my match…but never underestimate the slow roast!  Bobby. We have truly adventured far and wide together…through the depths of some personal sorrows, through the dark but also beautiful caves of consulting and counseling internship, all the way to the humor and authentic connection that characterizes our friendship. Thank you! August…our journey did not go the direction we imagined it. But you were my pillar and biggest supporter for a very long time. Thank you for growing with me and loving me. I will forever cherish the depth of the love we shared. Most of all, thank you to my family, klavertje vier – AZRA – for showing me how to put love, kindness, and compassion at the center of all things. To my sister, Aissa…my moon spirit…my life companion – for journeying through life with me and showing me what the purest form of love feels like. “Both sun and moon blissfully call the tune. The one at midnight, the other at noon.” Rolf Huysmans. “You are imperfect, you are wired for struggle, but you are worthy of love and belonging.” Brené Brown. To my mammsy, Ann…my pillar of strength – for grounding me so firmly in optimism, kindness, and determination. “The way we talk to our children becomes their inner voice.” Peggy O’Mara. To my wonderful dad, Rolfinho – your presence is eternally missed. Not a day goes by that I don’t reflect on how incredibly fortunate I was to have your light of integrity, beauty, and vision guiding me. You were truly an exceptional human. You and mammsy showed me what love really means…when it is unconditional, when it is reflected in our everyday choices of how we treat others. Merci beaucoup! Quand on n’a que l’amour Pour unique raison Pour unique chanson Et unique secours… Quand on n’a que l’amour Pour tracer un chemin Et forcer le destin A chaque carrefour… Alors sans avoir rien Que la force d’aimer Nous aurons dans nos mains Amis le monde entire. - Jacques Brel – COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI v Table of Contents Chapter 1: Introduction ................................................................................................................... 1 Chapter 2: Methods ....................................................................................................................... 11 Paradigm .................................................................................................................................... 11 Positionality ............................................................................................................................... 12 Setting........................................................................................................................................ 13 Needs assessment/pilot phase .................................................................................................... 13 Participants ................................................................................................................................ 15 Sport Program Design ............................................................................................................... 17 Sport Program Implementation ................................................................................................. 22 Instrumentation/Measures ......................................................................................................... 26 Procedures ................................................................................................................................. 32 Pre-program data collection procedures .................................................................................... 35 During-program data collection procedures .............................................................................. 36 Post-program data collection procedures .................................................................................. 37 Data Analyses ............................................................................................................................ 39 Chapter 3: Results ......................................................................................................................... 43 Preliminary results ..................................................................................................................... 44 Program implementation ........................................................................................................... 44 RQ1: What is the youth participation experience in a TPSR-based youth sport program in eSwatini? ............................................................................................................................... 44 RQ2: What are the coaching strategies and program design elements (strengths and weaknesses of coach training and sport program) that contribute most strongly to life skills learning in a TPSR-based youth sport program in eSwatini? ................................................ 54 RQ3: To what extent was fidelity to the TPSR model achieved in terms of daily structure, youth responsibility behaviors, and coaching strategies? ...................................................... 82 Program impact ......................................................................................................................... 92 RQ4: What positive developmental outcomes and changes in life skills are associated with youth participation in a TPSR-based youth sport program in eSwatini? .............................. 92 Researcher reflexivity ............................................................................................................... 99 Youth experiences ................................................................................................................. 99 Program design .................................................................................................................... 102 Chapter 4: Discussion ................................................................................................................. 105 Program implementation ......................................................................................................... 106 COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI vi Research question one: youth participation experiences ..................................................... 106 Research question two: coaching strategies and program design elements ........................ 112 Research question three: fidelity to the TPSR model .......................................................... 131 Program impact ....................................................................................................................... 140 Research question four: youth positive developmental outcomes and life skills ................ 140 Limitations .............................................................................................................................. 146 Practical Implications and Future Directions .......................................................................... 148 Conclusions ............................................................................................................................. 152 References ................................................................................................................................... 154 Tables and Figures ...................................................................................................................... 177 Appendix: Extended Introduction ............................................................................................... 194 Scope of the Study................................................................................................................... 194 Basic Assumptions .................................................................................................................. 195 Limitations of the Study .......................................................................................................... 196 Definition of Terms ................................................................................................................. 197 Significance of the Study ........................................................................................................ 198 Appendix: Extended Literature Review ...................................................................................... 200 Youth, development, and sport: eSwatini context ................................................................... 201 Sport for development and peace ............................................................................................ 211 Sport for development in South Africa and eSwatini ............................................................. 223 Youth coaching in Southern Africa and eSwatini ................................................................... 232 Role of coaches in positive youth development and sport for development ........................... 240 Teaching personal and social responsibility through sport ..................................................... 248 Application of the TPSR model .............................................................................................. 253 Theoretical framework ............................................................................................................ 280 Precede-Proceed model ....................................................................................................... 281 Needs assessment/pilot phase (PRECEDE) to inform dissertation feasibility study .......... 283 Youth sport program: Theoretical framework ..................................................................... 290 Summary of Literature Review ............................................................................................... 296 Appendix A: Sport Program Outline .......................................................................................... 299 Appendix B: Coach Training Manual ......................................................................................... 329 Appendix C: Demographics Survey ........................................................................................... 351 COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI vii Appendix D: Demographics and Personal and Social Responsibility Questionnaire (PSRQ) ... 352 Appendix E: Multidimensional Scales of Perceived Self-Efficacy (MSPSE) ............................ 353 Appendix F: Student Learning Quiz ........................................................................................... 357 Appendix G: Coach Focus Group Guide .................................................................................... 358 Appendix H: Youth Focus Group Guide .................................................................................... 359 Appendix I: Teacher Interview Guide ........................................................................................ 360 Appendix J: Tool for Assessing Responsibility-Based Education (TARE) – Post-Teaching Reflection .................................................................................................................................... 361 Appendix K: TPSR Implementation Checklist ........................................................................... 365 Appendix L: Coach Consent Form ............................................................................................. 366 Appendix M: Youth Assent Form .............................................................................................. 368 Appendix N: Parental Consent Form .......................................................................................... 370 Appendix O: Teacher Consent Form .......................................................................................... 372 COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI 1 Chapter 1: Introduction Adolescence is a formative period in the healthy development of youth and lays the foundation for future well-being and fulfillment (Holt, 2008; Fatusi & Hindin, 2010). In developing countries, this age demographic makes up the largest proportion of the population (UNFPA, 2015). However, young people in these areas are facing significant health-related challenges as well as limited resources to support their development (Fatusi & Hindin, 2010). In the Kingdom of eSwatini (formerly known as Swaziland), a small country in Southern Africa, 36% of the population is between the ages of 10-24 years (WHO 2013; Mavundla, Dlamini, Nyoni, & Mac-Ikemenjima, 2015). While youth in eSwatini struggle with the more universal challenges associated with adolescence such as social identity development and peer pressure, emaSwati youth are also faced with major context-specific challenges. These include but are not limited to economic and resources concerns such as unemployment, low school attendance, and high poverty rates as well as health challenges such as risk for HIV/AIDS (Huysmans, Clement, Hilliard, & Hansell, 2017). Specifically, the population-level poverty rate in eSwatini is 63%, unemployment for youth aged 15-24 is 42.6%, and only about half of youth attend school (Mavundla et al., 2015; Ministry of Sports, Culture and Youth Affairs, 2015). Of even more concern is the fact that eSwatini has the highest global prevalence of HIV/AIDS; almost 30% of adults (15-49 years old) are infected (UNAIDS, 2016). The high prevalence of HIV/AIDS in eSwatini has not only put youth at significantly higher risk for infection (AVERT, 2014), but it has also had psychological, social, and economic effects on the lives of young emaSwati (Foster & Williamson, 2000). These include, but are not limited to, becoming the caretaker of a sick parent, experiencing increased financial pressure in already poor living situations, having to drop out of school to earn a living, and experiencing the death of one or both parents (AVERT, 2014; Foster & Williamson, 2000). This is consequential given the COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI 2 significant body of research that indicates that exposure to adverse childhood experiences (ACEs) such as neglect or chronic illness and the death of a parent put children at greater risk for future cognitive, emotional, social and health impairments (Anda, Butchart, Felitti, & Brown, 2010; Felitti et al., 1998). Furthermore, the high adult mortality rates due to the HIV epidemic in eSwatini has resulted in a youth population (under 18 years of age) composed of almost 50% orphans and vulnerable children (AVERT, 2014). This is concerning because emaSwati (Swazi) youth are therefore not only exposed to adverse childhood experiences alongside health and resources challenges, but they are also lacking guidance and mentorship from adult role models to support their healthy development. Investing in youth development and mentorship initiatives in eSwatini should therefore be prioritized. Although there are government-led policies, and initiatives, for youth development operating at the national and community level in eSwatini, youth buy-in to these systems is limited (Mavundla et al., 2015; Ministry of Sports, Culture and Youth Affairs, 2015). Moreover, the gap between provision, and adoption, of youth services may suggest that there is a need to find ways to engage young people in their own development through creative, fun, and intentional programming. Sport-based youth development programming may be one avenue through which to achieve this goal (Beutler, 2008). Sport is seen as an appropriate vehicle through which to deliver youth development initiatives because it is an engaging and well-liked avenue for health promotion and behavior change in adolescents (Kaufman, Spencer, & Ross, 2013). It is also valued as an innovative, practical, and cost-effective tool for development (Beutler, 2008). On a global scale, a multitude of research supports the role of sport as a vehicle for youth development (Schulenkorf, Sherry, & Rowe, 2016; Svensson & Woods, 2017). COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI 3 The role of sport in youth development is conceptualized as a fertilizer (Coakley, 2011) that can create the right environment to help cultivate socially desirable skills that all young people have the innate potential to develop (Coakley, 2011). Positive youth sport experiences have been found to not only meaningfully contribute to performance outcomes and future sport participation, but also personal development (Côté & Hancock, 2016). It also exposes youth to positive role models, social connections, and constructive environments that may buffer the negative impacts of ACEs and developmental trauma (Hughes, Ford, Davies, Homolova, & Bellis, 2018; Whitley, Massey, & Wilkison, 2018), build resilience (Bellis et al., 2018), and help them grow into civically engaged and conscientious adults (Beutler, 2008; Coakley, 2011). For socially vulnerable populations, sport participation can also help youth develop the life skills needed to overcome the challenges of everyday life and “succeed in the different environments in which they live, such as school, home and in their neighborhoods” (Danish, Forneris, Hodge, & Heke, 2004, p.40). Life skills may be important for socially vulnerable youth to develop due to the increased likelihood that they face stressors, mental health issues, and social isolation (Hermens, Super, Verkooijen, & Koelen, 2017). Sport-based life skills development programming may therefore be a potential vehicle through which to support the healthy development of emaSwati youth. Several studies in eSwatini indicate a large percentage of youth hold positive attitudes toward sport and its benefits on health and well-being (Huysmans et al., 2017; Ndlangamandla, Burnett, & Roux, 2012; Toriola, 2010). Both male and female youth have indicated that sport helps them develop life skills including but not limited to discipline, respect, team work, and managing emotions (Huysmans et al., 2017). Youth also reported that sport has the potential to help them overcome some of their developmental and community challenges by serving as a positive COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI 4 distraction and teaching them helpful skills. In addition, youth expressed that sport may help them interact with peers who share similar struggles, and support them in building the confidence and self-esteem to progress through adversity (Huysmans et al., 2017). However, only a small percentage of youth actually participate in sport or physical education at school (Huysmans et al., 2017; Ndlangamandla et al., 2012; Toriola, 2010). Further, female perceptions of competence and participation in sport is generally much lower than for males and decreases significantly from primary school to secondary school (Toriola, 2010). This is partly affected by a culture of male dominance combined with a lack of female role models in sport (Toriola, 2010). In addition, financial, structural, and equipment barriers also limit higher youth sport participation levels (Huysmans et al., 2017; Ndlangamandla et al., 2012; Toriola, 2010). Therefore, despite youth enjoyment of sport and awareness of its positive benefits, there are significant systemic and cultural barriers that limit youth sport participation, especially for girls. Further, there is negligible programming that utilizes sport as a context for youth life skills development in eSwatini. Although there is limited sport for development programming in eSwatini, successful implementation of sport-based life skills initiatives in South Africa suggests there is potential for these programs to create meaningful developmental outcomes for emaSwati youth. South Africa is a comparable context to eSwatini given that 66% of the population is below the age of 35 and youth face similar developmental challenges (UNFPA South Africa, 2011). These include high unemployment, teenage pregnancy, poverty, HIV, and youth-led households (UNFPA South Africa, 2011). In the Kayamandi township of South Africa, research indicates that sport participation helped youth develop valuable intrapersonal, and interpersonal, life skills as well as overcome significant community challenges (Whitley, Hayden, & Gould, 2016). Sport COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI 5 participation helped youth overcome community challenges by creating an environment of positive peer influences and support, keeping youth out of trouble, and giving them a reason not to make bad decisions (Whitley, Hayden, & Gould, 2013). These findings are further supported in the Buffalo Soccer Coaching Club (BSCC) in the Eastern Cape province of South Africa (Draper & Coalter, 2016). That is, youth experienced personal development across several life skills and also reported positive experiences in the program including social connection with peers and a sense of safety and belonging (Draper & Coalter, 2016). Burnett’s (2014) work with Might Metres in South Africa also emphasizes the positive impact of sport-based programming on youth pro-social behavior and building teacher learner relationships built on trust and enjoyment (Burnett, 2014). These findings from South Africa are consistent with studies from North America that support the role of youth sport participation in facilitating cognitive, emotional, and social life skills outcomes for normal adolescent development as well as for socially vulnerable or at-risk youth (Camiré, Trudel, & Bernard, 2013; Danish, Forneris, & Wallace, 2005; Gould, Collins, Lauer, & Chung, 2007; Hermens et al., 2017; Holt et al., 2017; Martinek & Hellison, 2016). The work of sport for development (SFD) and life skills programming in South Africa (Burnett, 2014; Whitley et al., 2013; Whitley, Wright, & Gould, 2016) and in Western contexts such as the USA and Canada (Hermens et al., 2017; Martinek & Hellison, 2016) support the value of investing in sport-based youth development programs in under-privileged contexts. However, sport participation does not automatically result in life skills outcomes (Coakley, 2011). Positive development outcomes associated with sport are contingent upon a wide range of factors. These include the culture of the sport environment, the social connections established during sport participation, the meaning and values associated with sport participation, and the COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI 6 coach-athlete relationship (Coakley, 2011; Holt et al., 2017). Therefore, the people in charge of establishing the sport climate such as the coach become especially important in ensuring life skills learning (Gould et al., 2007). Coaches are the gatekeepers of the youth sport experience and are also often viewed by athletes as important mentors in their development (Bean & Forneris, 2016; Giges, Petitpas, & Vernacchia, 2004; Gould et al., 2007; Holt et al., 2017; Vella, Oades, & Crowe, 2011). Coaches are therefore in a unique position to be facilitating life skills development through sport (Gould et al., 2007). Specifically, when the coach is able to foster a caring and supporting sporting environment, personal development and positive developmental outcomes are more likely to occur (Spaaij, 2009; Vella et al., 2011). This is consistent with the positive youth development (PYD) framework that states that every adolescent is capable of positive developmental change but that the interaction between the individual and their sport context will heavily influence their personal development (Holt & Neely, 2011). This means that the extent to which coaches carefully craft a nurturing sport environment and include intentional life skills building activities will determine the resultant life skills outcomes (Bean & Forneris, 2016; Gould et al., 2007; Holt et al., 2017; Vella et al., 2011). In South Africa, coaching effectiveness frameworks explicitly outline the role of coaches in engendering outcomes in youth participants that are more holistic than just sport-specific outcomes (International Council for Coaching Excellence, Association of Summer Olympic International Federations, & Leeds Metropolitan University, 2013). Several studies have explored the role of youth coaches in intentionally facilitating life skills learning and positive youth development in South Africa (Meir, 2017; Whitley et al., 2013; Whitley, Wright, & Gould, 2016). These studies have found that coaches were cognizant of the challenges facing youth in COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI 7 the community and therefore intentionally employed strategies to build life skills (Whitley et al., 2013). These strategies included building close relationships with youth, creating safe and caring sport climates, engaging youth in discussion, and providing opportunities to practice skills. Further strategies identified were encouraging self-reflection, modeling behavior, and empowering youth to problem-solve. (Whitley et al., 2013; Whitley, Wright, & Gould, 2016). These findings support empirical and review research in North America that emphasize the two fold role of coaches in creating a caring and positive sport climate and using explicit life skills building strategies (Collins, Gould, Lauer, & Chung, 2009; Gould & Carson, 2008; Gould et al., 2007; Holt et al., 2017; Santos, Camiré, & Campos, 2016). Despite the valuable role of coaches in facilitating life skills outcomes for youth sport participants, coaches often struggle to articulate the explicit strategies that they employ to build life skills (Camiré et al., 2013; Gould et al., 2007; Santos et al., 2016) or they face significant barriers to emphasizing life skills in their coaching (Whitley, Gould, Wright, & Hayden, 2017). Coaches have voiced concerns over the incompatibility of performance and life skills foci and the pressure to teach tactical and technical sport skills over life skills (Santos et al., 2016; Whitley et al., 2017). Further, coaches have expressed that coaching education curricula are lacking in PYD emphases and do not effectively communicate how to facilitate personal development outcomes (Santos et al., 2016). In addition, life skills development is often absent from coaching philosophies to begin with (Whitley et al., 2017). Therefore, although there is justification for the use of coaches as implementers of youth life skills programming, there is a need to first identify the barriers that prevent coaches from adequately emphasizing life skills in their coaching (Whitley et al., 2017) as well as for further coach education on the successful integration of life skills and performance foci (Santos et al., 2016). Coaches may also benefit COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI 8 from training that develop teaching strategies to facilitate youth life skills learning and provides opportunities to practice those strategies (Santos et al., 2016; Whitley et al., 2013). In addition, there is limited research on this topic in non-Western contexts where youth could benefit from positive coach mentors and sport-based life skills programs. One possible solution to equipping coaches with the skills they need to deliver youth development programming would be to train them in the use of a more structured model that integrates physical and life skills objectives. One of the most well-known instructional models for life skills education through sport in North America is Hellison’s (2011) Teaching Personal and Social Responsibility model (TPSR; Hellison, 2011). The TPSR model is designed to help youth develop the necessary skills to take more responsibility for their well-being and for the welfare of others (Hellison, 2011; Martinek & Hellison, 2016). It is an intentionally structured model that employs active learning strategies to help youth achieve small successes that build confidence and self-efficacy to engage in their own development. The TPSR framework includes five responsibility levels, or goals, that youth need to take ownership of along their developmental journey: 1) respecting the rights and feelings of others; 2) effort and cooperation; 3) self-direction; 4) helping others and leadership; and 5) transfer. In helping youth attain these responsibility goals, program instructors are expected to use the following strategies: empowerment, self-reflection, integration of physical activity and life skills, being relational with kids, and transfer to life outside sport. In addition, there is a standard daily structure for TPSR sessions that allow for relationship building, group and individual reflection, life skills awareness-building, and physical activity time (Hellison, 2011; Martinek & Helison, 2016). The TPSR model has been used as the guiding framework in a multitude of youth development programs (Gordon & Doyle, 2015; Hellison, 2011; Martinek & Hellison, 2016). COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI 9 These programs have primarily targeted underprivileged or at-risk youth and have been implemented in numerous settings ranging from in-school physical education classes to community-based programs (Caballero-Blanco, Delgado-Noguera, & Escartí Carbonell, 2013; Gordon & Doyle, 2015; Martinek & Hellison, 2016). The effectiveness of TPSR programs in engendering positive developmental outcomes is supported by significant literature. Multiple studies have demonstrated improvements in self-control, effort, reaching goals, leadership, and helping or cooperative behaviors (Bean, Kendellen, & Forneris, 2016; Caballero-Blanco et al. 2013; Cryan & Martinek, 2017; Escarti, Gutiérrez, Pascual, & Marín., 2010). Further, qualitative accounts of participant experiences during TPSR programs indicate high levels of enjoyment, experiencing caring adult relationships, developing a sense of belonging, and feeling safe (Caballero-Blanco et al. 2013; Escarti et al., 2010; Hellison & Walsh, 2002; Whitley, Coble & Jewell, 2016). In addition, studies also support the transfer of intrapersonal and interpersonal skills such as self-control, emotion regulation, effort, respect, and social skills to domains such as school, home, and peer groups (Bean et al., 2016; Caballero-Blanco et al. 2013; Hellison & Walsh, 2002; Hemphill & Richards, 2016; Whitley, Coble, & Jewell, 2016). Two noteworthy TPSR programs are the ‘Girls Just Wanna Have Fun’ (GJWHF) program in Ontario, Canada (Bean, Forneris, & Halsall, 2014; Bean et al., 2016) and the Refugee Sport Club (RSC) in Lansing, Michigan (Whitley & Gould, 2010; Whitley, Coble, & Jewell, 2016). Both programs successfully created safe, empathetic and supportive youth environments for sport participation and contributed to the holistic development of youth participants. These programs provided key lessons for future TPSR programming including useful program design elements and coaching strategies that contribute to positive youth development outcomes. Further, the COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI 10 RSC program illustrated the value in adapting the program to the cultural context of the participants through taking a collaborative approach to program design. The aforementioned research indicates that the TPSR model may be a useful guiding framework to help coaches deliver life skills-focused sport programming across multiple youth contexts. In eSwatini, the TPSR model could provide the foundation for the design of sport based youth development initiatives that use coaches as primary program implementers. Moreover, there is justification for exploring this type of programming given the significant need to find more creative and effective platforms to address the developmental challenges facing emaSwati youth. In addition, there is evidence for the success of sport-based youth life skills development programs in South Africa where youth face similar developmental challenges. However, any further explorations of sport-based youth life skills programming should be theory-driven and need to employ more rigorous monitoring and program evaluation as weak methodologies have been over-relied on (Coalter, 2015; Levermore, 2011; Spaaij, 2009). In addition, although the TPSR model has demonstrated significant success in fostering life skills with at-risk youth, the majority of TPSR programs have been implemented in Western contexts where youth challenges are culture-specific (Caballero-Blanco et al., 2013; Gordon & Doyle, 2015; Whitley, Coble, & Jewell, 2016). An exploration of TPSR programming in eSwatini would therefore provide an opportunity to explore how the model might operate differently in a distinct youth context (Wright, Jacobs, Ressler, & Jung, 2016). The multitude of research in North America supporting the value of the TPSR model in cultivating positive developmental outcomes for underprivileged youth suggests that it would be an appropriate framework for sport-based youth life skills programming in eSwatini. The main aim of this feasibility study was therefore to explore the youth participation experiences and COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI 11 successes/challenges associated with implementing a TPSR sport program for underprivileged youth in a community in eSwatini. A secondary aim of the study was to examine the positive youth outcomes and changes in life skills associated with participating in a TPSR sport program. The specific research questions were as follows: RQ1: What is the youth participation experience in a TPSR-based youth sport program in eSwatini?; RQ2: What are the coaching strategies and program design elements (strengths, weaknesses, and improvements of program and coach training) that contribute most strongly to life skills learning in a TPSR-based youth sport program in eSwatini?; RQ3: To what extent was fidelity to the TPSR model achieved in terms of daily structure, youth responsibility behaviors, and coaching strategies?; and RQ4: What positive developmental outcomes and changes in life skills are associated with youth participation in a TPSR-based youth sport program in eSwatini? Chapter 2: Methods Paradigm The current study was guided by a social constructionist paradigm (Crotty, 1998). Social constructionism is grounded in the belief that there is no singular objective truth. Rather, we create and construct meaning through our interactions with our social and cultural context. This means that individuals may experience the same phenomenon differently and construct varying, and equally valid, “truths” related to those experiences (Crotty, 1998; Ponterotto, 2005). One of the central aims of constructionist research is therefore to understand the lived experience of the research participant as expressed from their viewpoint (Ponterotto, 2005). This epistemological stance was chosen because the author posited that the youth experience in the sport program, and the successes and challenges encountered in implementing the program, would be influenced by the social and cultural context of the community. Positionality COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI 12 The emphasis on co-construction of meaning in social constructionism makes it necessary to examine the background of the primary researcher that may influence the interpretations made along the research journey (Creswell, 2007; Ponterotto, 2005). I was born and raised in eSwatini, Southern Africa, but my ethnic heritage is European, as my parents grew up in Belgium. Consequently, I was raised with a mixture of Swati and Belgian cultural influences, in a home environment that subscribed to European belief systems and a school and social environment that was rooted in Swati culture and beliefs. From a young age I experienced life in eSwatini both as an insider as well as an outsider. That is, I grew up in eSwatini, I attended a public primary school and had majority emaSwati (Swazi) friends, but I was also White in a nation where 97% of the population is Black. After attending a local public primary school in eSwatini, I attended a United World College (UWC) for high school. Waterford Kamhlaba, a UWC located in eSwatini, is an international high school that attracts students of over 60 nationalities. Being surrounded by students from all over the world was a pivotal experience in shaping what I consider to be a multicultural worldview. However, this worldview is sometimes at odds with the more traditional beliefs in Swati culture. Waterford was then the stepping stone to gain a scholarship to attend college in the United States, at Duke University. At 19, I left eSwatini to start my tertiary education in the United States. My educational experiences at Duke, and then at West Virginia University as a doctoral student, have significantly shaped my identity as an academic and a scholar. However, throughout my undergraduate, and graduate, educational experiences, I have made strong efforts to connect the material I was learning to life in eSwatini, and to the belief systems that are valued there. COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI 13 Nonetheless, I am aware that the majority of my higher education was experienced in a culture different from my home country, where I conducted my doctoral research. These experiences were likely to influence how I interacted with the research process; from choice of methodology, to program implementation and data analysis. From the participants’ perspective, it was also likely that I was considered an outsider (ethnicity and identity as a researcher). However, my ability to speak conversational SiSwati and the fact that I was born and raised in eSwatini may have given me, somewhat of, an insider status. Setting The feasibility study took place at a community-based children’s organization that operates in the Lobamba region of eSwatini. The children’s organization is a non-profit that provides psychosocial services and school funding support for underprivileged youth in the community including orphans and vulnerable children (OVC’s). In addition, the organization offers parenting skills programs for members of the community and infrastructure support for local schools. The organization also facilitates skill-building workshops in local schools on topics surrounding school administration, HIV/AIDS, abuse, grief, health, and basic counseling interventions. On a daily basis, the organization also provides pre-school education for OVC’s in the community and afternoon clubs (i.e. classes) to assist primary school-aged children with literacy development. During these afternoon clubs, children are provided with a light meal (mahewu – a maize-based drink). The grounds of the children’s organization have a vegetable garden, a sheltered outdoor play area as well as a soccer field. Needs assessment/pilot phase COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI 14 Based on the preliminary results from the needs assessment/pilot phase, several decisions were made to guide the development of the feasibility study (current dissertation). First, sport is a beloved and creative context through which to engage emaSwati (Swazi) youth in positive development. Using sport as the platform for youth programming in the feasibility study was therefore an appropriate path forward. Second, HIV/AIDS prevention is an immensely complex issue that requires long-term investment, strong community connections, and a multidisciplinary approach. The feasibility study therefore took out the HIV/AIDS component and instead focused on developing the life skills that HIV/AIDS experts identified as most valuable for HIV/AIDS prevention i.e. the PRE factors from phase 3. These included: self-belief, social & personal responsibility, goal-setting, decision-making, self-efficacy, and emotional expression. Third, youth within the 15-24 years old demographic have already developed a strong set of beliefs related to relationships, gender roles, sexual intimacy etc. It would therefore be more effective to engage younger age demographics in youth development programming. Fourth, emaSwati youth are lacking caring and empathetic adult mentors. Given that coaches believed in their role as mentors and educators for youth athletes, they were an appropriate population to engage with to implement sport-based positive youth development feasibility programming. Fifth, coaches were keen to learn strategies and approaches to strengthen their ability to facilitate life skills learning for their athletes. Using the Teaching Personal and Social Responsibility (TPSR) model to guide coach education for the feasibility study was therefore a viable option. Sixth, emaSwati youth were interested in engaging in mixed gender sport-based programming where they could learn multiple sports. The feasibility study was therefore designed to include these elements. Last, social cognitive theory and the positive youth development (PYD) framework were used as the theoretical foundation of the feasibility COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI 15 study. The emphasis of PYD on creating positive sporting environments and treating youth as inherently capable of becoming successful complemented the emphasis of social cognitive theory on human agency and the active role that youth may play in their development. The use of both implicit and explicit PYD learning pathways also provided the right social environment for self-efficacy beliefs to emerge in youth sport participants. Participants Youth participants were thirty-three students (N=33, 22 females and 11 males) aged 11 15 years old (M=12.6 years old, range=11-15) who attended the grades 6 and 7 afternoon club (grade 6 (n=24), grade 7 (n=9)) at the community-based children’s organization. Sample size at the outset was intended to be 15 youth participants as this has been found to be optimal for group activities and to create a caring climate (Cryan & Martinek; Whitley & Gould, 2010). However, all youth who attended the afternoon class at the time were keen to participate so the primary researcher decided not to deny participation to any youth given the ethos of the program. Eligibility criteria for participation included: 1) current enrollment in a primary school in the Lobamba area of eSwatini; 2) current attendance at the afternoon club at the children’s organization; 3) conversational English language proficiency; 4) aged 10-15 years old; and 5) signed parental consent and youth assent to participate in the study. Although all youth who attended the organization were either single or double orphans, they all lived in a household where there was an adult guardian who could sign a consent form. Youth were recruited through convenience sampling from an afternoon club at the community-based children’s organization that they attended. Coach participants in the study were three (N=3) male youth coaches (2 emaSwati, 1 Zimbabwean; M=27.3 years old) from the Lobamba region of eSwatini. This sample size was COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI 16 chosen given recommendations that the ratio of coaches to youth participants should not exceed 1:5 to provide the opportunity for quality one-on-one interaction (Cryan & Martinek; Whitley & Gould, 2010). Evidently this coach to youth ratio could not be retained given the significant increase in the number of youth participants. In addition, after one week of the sport program a coach had to drop out because he finally got a full-time job after two years of unemployment. The remaining two coaches ran the last 2 weeks of the program on their own. Coach eligibility criteria included: 1) at least two years of experience coaching a youth or adolescent sport team; 2) at least 18 years old; 3) English language proficiency; and 4) SiSwati language proficiency. The coaches included in the study had an average of 5.5 years of coaching experience and previous expertise coaching a range of sporting codes including basketball, soccer, volleyball, athletics, badminton, and aerobics. All coaches had a background coaching a similar age-group (U12 and U14) to the youth participants in the sport program. Two of the coaches had grown up in the same community as the youth participants while the third coach shared a similar socio economic background to the youth although he had grown up in a different country. Two of the three coaches had no prior training in positive youth development while the third coach had partially completed a training course in positive youth development. Initial contact with coaches began via phone and email while the primary researcher was still in the United States. This was reasonable given the connections that were established through the researcher’s study the previous summer on youth coaches in eSwatini. Every effort was made to recruit at least one male and female coach, but this was not possible given the limited number of female coaches in the country. The primary researcher also aimed to recruit coaches who were relatable (i.e. similar ethnicity and gender, and less than 20 years older than youth) to the youth and could be viewed as mentors. Relatability and the mentorship role of COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI 17 coaches has been found to be an important predictor of positive youth development outcomes through sport participation (Gould, Collins, Lauer, & Chung, 2007). Moreover, during recruitment, the primary researcher emphasized the youth participant demographics with the coaches to highlight the privileged role they would be in as role models and trusted adults in the lives of the youth participants. Only coaches who seemed invested in that mentorship and educator role were asked to participate in the study. Coaches received a financial incentive and certificate for participating in the program, which they were informed of during the consent process. Sport Program Design The overall research objectives of the sport program (intervention) were to: 1) explore the youth participation experiences and successes/challenges associated with implementing a Teaching Personal and Social Responsibility (TPSR) sport program in eSwatini; and 2) examine the positive youth outcomes and life skills associated with participating in a TPSR-based sport program. Separate from these research objectives, the goals of the sport program for the youth and coach participants were to: 1) provide youth with opportunities to be physically active; 2) provide youth with opportunities to participate in a range of different sports and physical activity-based games; 3) provide youth with opportunities to have fun; 4) facilitate youth life skills development through sport; and 5) provide coaches with the opportunity to learn new coaching strategies to promote life skills development through sport. The sport program was named “Talabasha - Temidlalo Nemfundvo”, which means “Youth time - Of sports and education/learning” in SiSwati. This name was chosen together with the coaches during the coach training. COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI 18 The sport program took place for 75-100 min every week day for three weeks with a total of 15 sessions. This was consistent with recommendations from prior TPSR programs that sport sessions occur at least two to three times per week for 60 minutes (Cryan & Martinek, 2017; Whitley & Gould, 2010). Although three weeks was a short amount of time to achieve sustainable program outcomes (Bean, Kendellen, & Forneris, 2016), the current program was intended to be a feasibility study. The successes and challenges of implementing this type of youth sport programming will be used to inform more long-term programming in eSwatini. Sessions took place either on the soccer field or in the outdoor play area of the children’s organization during the afternoon club slot between 2:30 and 4:10 pm every day. Sport equipment was purchased for use in the program thanks to the Association for Applied Sport Psychology (AASP) Gualberto Cremades International Research Grant. This included volleyballs, basketballs, soccer balls, netballs, frisbees, pinnies, cones, a volleyball net, and a video camera. This equipment was gifted to the children’s organization after the end of the sport program. The sport program was designed, and implemented, according to the key programmatic features of the TPSR model as well as using the information gathered during the needs assessment/pilot phase. The program was therefore grounded in the foundational TPSR principles of holistic youth positive development, youth centered approaches, and fostering human decency (Hellison, 2011; Martinek & Hellison, 2016). The TPSR model was chosen over other life skills education through sport models for the following reasons: 1) the option to tailor the life skills focus to values and skills that are appropriate to the cultural and youth context that the program operated in; 2) the focus on teaching coaches how to use intentional strategies to COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI 19 facilitate the learning of life skills; and 3) the emphasis on transfer of life skills learning in the sport setting to domains outside of sport (Hellison, 2011; Martinek & Hellsion, 2016). As a brief overview, the sport program was designed using the standard TPSR daily structure (relational time, awareness talk, physical activity, group reflection, and individual reflection) and responsibility levels/goals (respecting others, effort and cooperation, self direction, helping and leadership, and transfer). Specific design elements from several successful TPSR-based youth sport programs also informed the development of the program. These TPSR based programs included the ‘Girls Just Wanna Have Fun’ (GJWHF) program in Ontario, Canada (Bean, Forneris, & Halsall, 2014; Bean et al., 2016), the ‘Refugee Sport Club’ in Lansing, Michigan (Whitley & Gould, 2010; Whitley, Coble, & Jewell, 2016), and the Soccer Coaching Club in central North Carolina (Cryan & Martinek, 2016). Each day of the program followed the same TPSR daily structure except for session one. Session one was used for ice breakers and to briefly introduce youth to all the responsibility levels and the expectations for the program. The remaining 14 sessions used the same daily structure: 1) relational time (10 minutes); 2) awareness talk (20-45 minutes); 3) physical activity (30 minutes); 4) group reflection (10 minutes); and 5) individual reflection (5 minutes). Details of the program design will now be described. Each day started with a brief period dedicated to building the relationship between the coaches and the youth i.e. relational time. Coaches made an effort to briefly chat with as many youths as possible and build a caring and meaningful coach-youth relationship. Various pieces of sport equipment were available for the youth to play around with as they relaxed and refocused after their day at school. To encourage timeliness, youth were given a small piece of candy for arriving on time. A local maize-based drink (emahewu) was also made available for the youth to COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI 20 consume as this was something that was normally provided by the children’s organization for their afternoon club classes. The awareness talk followed the relational time and was an opportunity for the coaches to teach the youth a life skill or responsibility that is valuable to develop. Awareness talks took place under a large tree on the sport field as it is customary in Swati culture to have group discussions under the shade of a tree. Although the awareness talks were intended to be facilitated in a mixture of English and SiSwati, it became apparent very quickly that youth confidence was very low in English so SiSwati was used as the primary means of communication. This decision ultimately promoted higher youth participation in discussion. Each day of the program focused on a specific responsibility level and main life skill. As the weeks progressed, the responsibility level foci shifted to the more complex responsibility behaviors i.e. moving from respect (level 1) to effort (level 2) to self-direction (level 3) and to caring and leadership (level 4). The final level, transfer (level 5), was included in every session given that this is an integral component of the TPSR model and previous programs have recommended integrating transfer into as many sessions as possible (Bean et al., 2016; Whitley, Coble, Jewell, 2016; Walsh, Ozaeta, & Wright, 2010). Transfer was operationally defined as any individual conversations, reflection opportunities or discussions related to applying life skills and responsibility concepts learned in the program to other domains of life such as school. Visual posters defining each life skill in English and siSwati were hung on and around the tree to aid learning. Using visual aids is an effective teaching strategy that accommodates for differences in the developmental needs and learning styles of youth (Allison & Rehm, 2007). A whiteboard was also used in most sessions where the poster for the life skill focus of that day was placed for easy reference. Although the sport program was delivered primarily in SiSwati, the use of the COACHING LIFE SKILLS THROUGH SPORT IN ESWATINI 21 visual aids that translated each SiSwati concept into English nonetheless helped youth learn about how the concepts could be referred to in English. In an effort to make the awareness talk an interactive and engaging component of the daily structure, there was always an activity integrated into the awareness talk that focused on the responsibility level and life skills of the day. These structured life skills learning activities were drawn from the Sports United to Promote Education and Recreation (SUPER) model (Danish, Forneris, Hodge, & Heke, 2004) of life skills education through sport (e.g. Dare to Dream activity) as well as sport psychology literature (e.g. deep breathing and muscle relaxation). An extended version of the awareness talk was used to provide time for the integration of those activities into the awareness talk. However, although the awareness talk was intended to be 20 minutes, most days had awareness talks that lasted between 30 and 45 minutes. Swati culture has a strong oral tradition which is typified by very deliberate and slow-paced discussion where talking points are e

Use of Four Predictive Screening Variables for Determination of Sacroiliac Joint Dysfunction in Adolescent Soccer Athletes Use of Four Predictive Screening Variables for Determination of Sacroiliac Joint Dysfunction in Adolescent Soccer Athletes Brian Hanson Follow this and additional works at: https://researchrepository.wvu.edu/etd Recommended Citation Hanson, Brian, "Use of Four Predictive Screening Variables for Determination of Sacroiliac Joint Dysfunction in Adolescent Soccer Athletes" (2018). Graduate Theses, Dissertations, and Problem Reports. 5759. https://researchrepository.wvu.edu/etd/5759 This Thesis is protected by copyright and/or related rights. It has been brought to you by the The Research Repository @ WVU with permission from the rights-holder(s). You are free to use this Thesis in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you must obtain permission from the rights-holder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/ or on the work itself. This Thesis has been accepted for inclusion in WVU Graduate Theses, Dissertations, and Problem Reports collection by an authorized administrator of The Research Repository @ WVU. For more information, please contact researchrepository@mail.wvu.edu. Use of Four Predictive Screening Variables for Determination of Sacroiliac Joint Dysfunction in Adolescent Soccer Athletes Brian Hanson, ATC, CES Thesis submitted to the College of Physical Activity and Sports Sciences At West Virginia University In partial fulfillment of the requirements for the degree of Master of Science in Athletic Training Michelle A. Sandrey, PhD, ATC, Chair Jean L. McCrory, PhD Benjamin Moorehead, MD Department of Sport Sciences Morgantown, West Virginia 2018 Keywords: sacroiliac joint dysfunction, adolescent soccer athlete, functional movement screen, injury risk Copyright 2018 Brian Hanson i ABSTRACT Use of Four Predictive Screening Variables for Determination of Sacroiliac Joint Dysfunction in Adolescent Soccer Athletes Brian Hanson, ATC, CES Context: Chronic onset of sacroiliac joint dysfunction (SIJD) is increasing in adolescent athletic populations including soccer. However, there is currently no pre-season screening tool for SIJD in this population. There are variables that are currently associated with SIJD, however, it is unknown if these variables developed into a screening tool can accurately predict the risk of sustaining SIJD. Objective: The purpose of this study was to create an effective screening tool for SIJD in adolescent soccer athletes and establish predictive values for SIJD injury risk. Design: A retrospective exploratory study to screen for risk factors contributing to SIJD in the adolescent soccer athletes. Setting: The testing took place in an athletic training facility at a mid Atlantic high school. Only one clinician administered the testing procedures. Patients or other participants: This study included members of the varsity and junior varsity boys’ (n = 6, 16.33±1.37 yrs, 176.50±6.98 cm, 72.12±9.92 kg) and girls’ (n = 14, 16.00±1.11 yrs, 165.93±6.39 cm, 61.11±6.92 kg) soccer teams from one high school in north central West Virginia. All participants were members of these teams with a sports physical on file. Inclusion criteria included those subjects who are healthy, have no disorders affecting ability to perform any of the tests included in this study, no history of acute injury to the lower extremity or back in the past six months, and no history of surgeries to the core or back within the past year. Exclusion criteria included subjects who have a history of surgery to the core or back within the past year, and those who have a disorder affecting ability to perform any of the tests included in this study. Interventions: Each participant performed during one testing session the Functional Movement Screen (FMS), including all 7 functional movements and the 3 clearing tests, active knee extension test, Palpation Meter (PALM) measurement for pelvic angle, and goniometry assessment of active hip range of motion (flexion/extension/abduction/adduction /internal rotation/external rotation). Main outcome measures: The dependent variables that were measured are the final composite score of the FMS, angle measurement in degrees from the active knee extension test, pelvic tilt angle in degrees from the PALM, and angle measurement in degrees for active hip flexion, extension, abduction, adduction, internal rotation, and external rotation. Results: A significant correlation with large strength (PCC = 0.545, p = .013) was found between SIJ injury and active hip abduction. A significant correlation with large strength (PCC = 0.732, p <.01) was found between the PALM and active hip extension. A significant correlation with medium strength (PCC = 0.473, p = .035) was found between the AKET and active hip flexion. One model in the binary logistic regression created a best fit with an odds ratio of 1.115 (CI95 = 1.003, 1.239, p = .044) with the variables of SIJ injury and active hip abduction. Two nonsignificant models with moderate odds ratios were produced for the PALM (OR = 1.141, CI95 = .841, 1.547, p = .397) and years playing soccer (OR = 1.319, CI95 = .854, 2.036, p = .212). A stepwise binary logistic regression created a best fit model with an odds ratio of 1.168 (CI95 = 1.004, 1.359, p = .045) that included both active hip abduction and the FMS to detect and SIJ injury. Conclusion: The results from this study indicate that active hip abduction will significantly predict an SIJ injury. Years of playing soccer, the FMS, and pelvic positioning may also be clinically useful assessments to predict an SIJ injury. ii ACKNOWLEDGEMENTS I would like to start by thanking my parents, Steve and Marilu. They have provided me with endless support and discipline throughout my entire academic career. If it weren’t for them and the countless opportunities they provided me I would not be where I am today. I would like to thank my two older sisters, Jackie and Stephanie. They have always been the perfect role models, not only as students, but by showing me what it takes to be a good person. The high level of success they have achieved in life continues to fuel my ambition to make myself a better person and for that I am forever grateful. I would like to thank the rest of my family. It has been tough living away from all of you for the first time and in a new state for the past two years, but your support has been unwavering. I would like to thank my friends, both the new ones made here, and the ones still back home. You all have kept me feeling sane while balancing the rigors of graduate school and work. Thanks to those who blew away any expectations and came to visit me in the mountains. Thank you to my committee members, Dr. Benjamin Moorehead and Dr. Jean McCrory. I am very appreciative of the time and effort you have put into this process. A giant thanks to my committee chair and graduate advisor, Dr. Michelle Sandrey. You certainly pushed me beyond my previous limits in the realm of research and writing. The amount of time spent reading my drafts, making suggestions, and meeting with me did not go unnoticed. Thank you for all the challenges provided both inside and outside the classroom. To my clinical supervisor at HealthWorks, Mike Casselman, it has been the utmost pleasure to serve under you for the past two years. Your guidance and expertise has assisted me to improve as a clinician. Best of luck with your new job and all future endeavors. To my athletic director, Jeff Bailey. Thanks for being the world’s best AD, you have certainly made my job easy. To my soccer coaches, Graham Peace, Kat Devlin, and Dustin Talton at University High School. You all have been a pleasure to work with and helped with my transition as a newly certified athletic trainer. I appreciate the trust you had in me from day one to always give the best care to our student athletes. To my subjects/athletes. You all have kept me on my toes and kept me feeling young these past two seasons. Thank you for all the laughs and success on the field. Lastly, I want to thank everyone else I did not mention that has helped me get to this point. I am incredibly appreciative of the impact everyone has made on my life. iii TABLE OF CONTENTS ACKNOWLEDGMENTS………………………………………………………………………..iii LIST OF TABLES………………………………………………………………………………..v INTRODUCTION………………………………………………………………………………...1 METHODS………………………………………………………………………………………..4 RESULTS………………………………………………………………………………………..15 DISCUSSION……………………………………………………………………………………18 CONCLUSION…………………………………………………………………………………..28 REFERENCES…………………………………………………………………………………..30 APPENDICES…………………………………………………………………………………...37 APPENDIX A THE PROBLEM………………………………………………………..38 APPENDIX B LITERATURE REVIEW……………………………………………….47 APPENDIX C ADDITIONAL METHODS…………………………………………….72 APPENDIX D ADDITIONAL RESULTS…………………………………………….106 APPENDIX E RECOMMENDATIONS FOR FUTURE RESEARCH………………110 ADDITIONAL REFERENCES………………………………………………………………...111 iv LIST OF TABLES TABLE B1. Ligamentous/Fascia Support Structures of the Sacrum……………………………49 TABLE B2. Muscle Origin/Insertion/Action/Innervation Surrounding the SIJ…………………51 TABLE B3. Measurement Techniques for Hamstring Length/Extensibility……………………64 TABLE B4. Hip Range of Motion……………………………………………………………….69 TABLE C1. Informed Parental or Guardian Consent……………………………………………72 TABLE C2. Informed Assent……………………………………………………………………78 TABLE C3. Informed Consent 18 Years or Older………………………………………………82 TABLE C4. Subject Demographics……………………………………………………………...88 TABLE C5. Verbal Instructions for Functional Movement Screen……………………………..89 TABLE C6. Functional Movement Screen Scoring Procedures………………………………...93 TABLE C7. Active Knee Extension Test………………………………………………………..97 TABLE C8. Pelvic Positioning…………………………………………………………………..98 TABLE C9. Hip Range of Motion – Goniometer………………………………………………100 TABLE C10. Functional Movement Screen Scoring Sheet……………………………………104 TABLE C11. Data Collection Sheet……………………………………………………………105 TABLE D1. Descriptive Statistics (Means ± SD) for Subject Demographics………………….106 TABLE D2. Descriptive Statistics (Means ± SD) for All Screening Variables………………...106 TABLE D3. Descriptive Statistics (Means ± SD) for Subject Demographics and SIJ Injury….107 TABLE D4. Descriptive Statistics on Means and SD for Screening Variables and SIJ Injury...107 TABLE D5. Pearson Product Correlations of Demographic Data to SIJ Injury……………….107 TABLE D6. Pearson Product Correlations of Predictive Variables to SIJ Injury……………...108 TABLE D7. Crosstab of Lower Extremity (DS, IL, HS) Movements from the FMS………….108 v LIST OF TABLES TABLE D8. Binary Logistic Regression Model for Screening Variables Associated with the Occurrence of a SIJ Injury……………………………………………………………………...109 TABLE D9. Stepwise Binary Logistic Regression Model for Screening Variables Associated with SIJ Injury…………………………………………………………………………………..109 vi INTRODUCTION Low back pain (LBP) has been shown to affect up to 80% of the general population at some point in their lifetime.1,2 Although LBP is a main symptom, sacroiliac joint dysfunction (SIJD) often clinically presents with LBP, thus leading to the conclusion that LBP can be caused by various injuries. Specifically, amongst the adolescent population, prevalence of LBP has reported to range from 30% to 74%.3,4 Low back pain, which can be caused by SIJD, was found to increase with age amongst the adolescent population. Increases in LBP are evident starting with 1% at seven years of age, to 17% at twelve years of age, and climbs to 53% at 15 years of age.5 Further, prevalence amongst adolescents with SIJD pain has been reported to range from 13% to 30% of all injuries with LBP as a symptom.6,7 Historically SIJD has been seen in young athletes who have sustained some form of mild trauma, however, more athletes now are experiencing a chronic onset.8 SIJD is commonly seen in sports with unilateral and repetitive biomechanical forces, such as kicking in soccer. Although there is little research on specifically SIJD, there is an apparent link between LBP and SIJD resulting in play time loss for athletes, specifically soccer. In one study,9 LBP was found to be the most prevalent previous overuse injury with an incidence of 28% among soccer players. At least 60.6% of soccer players (n=190) were found to have experienced LBP in their lifetime, and 56.9% felt it in the previous 12 months, resulting in 27.7% missing training from injury.10 Another study11 reported 54.4% of futsal players experiencing LBP in their lifetime, and 25.7% had absence from training sessions due to LBP. The nature of soccer places high intensity forces on the lower extremities that are often unilaterally dominant. These forces are transferred superiorly to the trunk through the sacrum and SIJ acting as the gateway. The biomechanical demands of playing soccer, including bending 1 and twisting of the trunk and variable lateral movement are a reason for SIJD to occur at such a high rate.11,12 With consideration of the biomechanics and prevalence of SIJ in soccer athletes, a screening tool should be created to evaluate potential risk factors. Four different components that have the potential to biomechanically evaluate SIJD prevalence are the Functional Movement Screen (FMS), pelvic positioning, hamstring length, and hip range of motion (ROM). The FMS is a preexisting screening tool that investigates seven fundamental movement patterns (deep squat, hurdle step, active straight leg raise (ASLR), rotary stability, inline lunge, shoulder mobility, and trunk stability push up). Currently there is little research available on whether the FMS subtests correlate with predicting SIJD. Only one study13 was conducted comparing FMS with chronic LBP patients to healthy controls. The authors13 reported that the chronic LBP patients scored significantly lower on the deep squat, hurdle step, ASLR, and rotary stability compared to the healthy controls. The results of this study indicate that those four tests of the FMS could contribute to accurately predicting SIJD. The movement of the innominates in both static and dynamic positions directly affects the movement of the sacrum, and potentially the motion that occurs at the SIJ. Malalignment of the innominates has the potential to negatively impact the SIJ. Pelvic asymmetry has been shown to contribute to altered lower extremity mechanics and contribute to SIJD in the frontal and sagittal planes.14 Athletes who participated in a sport with lateral movements, much like a goalkeeper or defender in soccer, would over time develop pelvic asymmetry problems leading to an increased incidence in back pain.15 Hamstring tightness in individuals with LBP could be a compensatory mechanism to weak gluteal muscles, which in turn decrease the compression stability mechanism of the SIJ.16 19 Subjects with SIJD had significantly shorter hamstring muscle length in individuals with 2 gluteal weakness compared to those who did not have gluteal weakness.20 In soccer players a natural hip adaptation may occur resulting in unilateral hip ROM deficits from a repetitive kicking motion. Hip ROM is well cited in the literature in contributing to SIJ motion.15,21,22 Hip rotation was a strong predictor for innominate angle, which in turn affects the motion occurring at the SIJ.23 The link between hip internal and external rotation and SIJD was also evaluated. Individuals with LBP including some with designated SIJ pain demonstrated a hip asymmetry of decreased internal rotation on the affected side compared bilaterally to the unaffected side with patients who had specific SIJ pain.21 Using a control group design, subjects with non-specific low back pain were compared to healthy controls to analyze hip rotation and extension. There was a difference in hip extension where the controls had greater hip extension then those with LBP.22 There is a plethora of knowledge on the SIJ in terms of anatomy, biomechanics, treatment, and rehabilitation. There is also a great deal of research on SIJD and LBP in athletes in the adult population across a wide span of sports. Conversely, there is a lack of knowledge on SIJD in adolescent athletes. Pain caused by SIJD historically has been more prominent in the adult population, however it has become increasingly prevalent in the adolescent population for reasons that are not well understood.2 With the increase of SIJD incidence in the adolescent population, some type of screening tool must be developed to assess predictive factors of SIJD, especially in soccer athletes. Currently there is no constructed clinical screening tool to assess predictive factors for SIJD in the adolescent soccer athlete population. With no known screening tool available, four different biomechanical and functional components that should be considered are the Functional Movement Screen (FMS), pelvic positioning, hamstring length, and hip ROM. 3 Thus, the purpose of this study was to create an effective screening tool for SIJD in adolescent soccer athletes and establish predictive values for SIJD injury risk. METHODS Design This study was a retrospective exploratory screening study to determine SIJD risk in adolescent soccer athletes. The independent variable was whether the athlete sustained a SIJ injury over the course of the past season. The dependent variables were the composite score of the FMS, the angle taken from the active knee extension test, pelvic angle measurement of both innominates, and goniometric angle hip range of motion measurements (flexion, extension, abduction, adduction, internal rotation, external rotation). These dependent variables were evaluated to predict potential SIJD injury risk. Subjects This study included members of the varsity and junior varsity boys’ and girls’ soccer teams from a high school in north central West Virginia. Twenty subjects (14 females, 6 males, 16.10±1.17 yrs, 169.1± 8.09 cm, 64.41± 9.25 kg) were recruited and completed all procedures of this study. Inclusion criteria included those subjects who are healthy, have no disorders affecting ability to perform any of the tests included in this study, no history of acute injury, other than a SIJD, to the lower extremity or back in the past six months, and no history of surgeries to the core or back within the past year. The subject had a sport physical on file and were currently a member of either the boys’ or girls’ soccer team at one high school during this past sports season. Exclusion criteria included subjects who have a history of surgery to the core or back within the past year, and those who have a disorder affecting ability to perform any of the tests 4 included in this study. This study was approved by the Institution’s Office of Research Compliance. Instruments Functional Movement Screen (FMS): The FMS was developed by Cook in an effort to connect pre-participation medical screening and performance testing.24-28 This screening was created in attempt to detect deficiencies by incorporating the mobility of the kinetic chain and stability necessary for performance. Although inconclusive results on the validity of the FMS to screen or detect movement deficiencies was evident, the procedures reproduced with consistency was apparent.28-33 Intra-rater reliability has been reported to range from ICC = 0.74 to 0.99.33 Thus, clinicians frequently use the FMS as a screening tool and despite not being the original intent of the FMS, professionals in the field of exercise, sport performance, and sport medicine use the FMS to analyze the movement capabilities of athletes and those who are at risk for injury. This interpretation of the FMS has been heavily investigated and the results show that athletes who score 14 or less points on the FMS are at an increased risk for injury.34-39 While a lot of research exists on collegiate aged athletes, there is little research that exists investigating the use of the FMS as an injury prediction tool on adolescent soccer athletes. Active knee extension test: Hamstring length measures the dynamic lengthening ability of the hamstring muscle group as the origin rests in a fixed position while the distal portion is in movement. It has been determined that the active knee extension test provides the best objective measurement of hamstring length due to the ease of measurement and excellent reliability of the test.40-43 An average range of motion for this test in normal healthy adults was shown to have a deficit of full extension of 35.6 +/- 10.4˚ for men, and 27.1 +/- 13.5˚ for women.44 In 5 comparison, elite track and field athletes (n = 127) established a normal value ranging between 72.3˚ and 73.9˚ with the active knee extension test.45 Palpation meter (PALM): The PALM is a device with a built in inclinometer that has been used to objectively measure pelvic angle. Despite little use in the adolescent population the PALM has shown to be both valid and reliable in measuring pelvic angles in the sagittal plane.46 48 A neutral pelvis has been established at 0 degrees with positive degrees describing an anterior innominate tilt, and negative degrees describing a posterior innominate tilt.47 Normative values in an asymptomatic adult population have been reported to be 6.49˚ in males and 6.78˚ in females.47 Hip range of motion: The hip has six degrees of freedom allowing for flexion, extension, abduction, adduction, internal rotation, and external rotation. Measurement of these movements can be assessed using a goniometer providing an angle in degrees. Goniometer use for angle measurement has been shown to be both reliable and valid in healthy populations and those with chronic LBP.49-51 Average hip range of motion values in males and females aged 11 to 17 years of age have been established. Results for males and females, respectively are flexion (113˚, 120˚), extension (15˚, 22˚), abduction (34˚, 44˚), adduction (14˚, 17˚), internal rotation (35˚, 35˚), and external rotation (40˚, 46˚).52 Procedures Before the screening tool procedures started, an informational meeting took place with the subjects and their parents. In this meeting, the informed parental consent form with HIPAA included (Table C1), informed assent form (Table C2), the informed consent form with HIPAA for subjects 18 and older (Table C3), and the demographic questionnaire (Table C4) were discussed. The informed consent forms with HIPAA and the demographic questionnaire were 6 completed during this informational meeting. After subjects and parents completed the necessary paperwork, screening tool procedures were explained. Instructions for the testing procedures were explained to all subjects during the informational meeting and before performing the tests. Those subjects who met all inclusion criteria were invited to participate in the study. Times were established for subjects to meet with the researcher once within a three-week period to complete all components of the screening tool; approximately one 30-minute session. The participants were permitted to engage in normal daily routines without limitations. Participants were allowed to wear self-selected athletic shoes and athletic clothes (shorts and a t-shirt) for the FMS, while shoes and socks were removed for the active knee extension test, pelvic positioning measurements, and hip range of motion measurements. All screening tool procedures were performed in the athletic training room and auxiliary space at one Mid-Atlantic high school to serve as an environmental control. Administration and supervision of all testing was completed by the primary researcher. Functional Movement Screen (FMS): Standard FMS procedures (Table C5, Table C6) were used as previously defined by Cook.25 A script was read (Table C5) to ensure understanding of the tested movements. Participants were not “cued” of their movements. Each participant was instructed to perform the 7 fundamental movements and 3 clearing tests (Table C6). Individuals were limited to a maximum of three trials for each movement, and an extensive warm up was not included. A movement was given a score between 0 and 3. A score of 1 indicates the inability to complete the movement, 2 represents compensation while completing a movement, and 3 signifies a correct completion of the movement without compensation. The raw score was used to denote right and left side scoring. The final score denoted the overall score for 7 the test. The lowest score for the raw score (each side) carried over to give a final score for the test. The first movement in the FMS (Table C6) was a deep squat designed to assess bilateral, symmetrical, functional mobility of the hips, knees, and ankles. A dowel was held overhead to assess bilateral symmetrical mobility of the shoulders and thoracic spine. The participant assumed a shoulder width apart stance and grasped the dowel so that the arms formed a 90 degree angle at the head. The participant then pressed the dowel overhead with the elbows in full extension. The participant was instructed to descend as far as possible into a squat while keeping heels on the ground and maintaining an upright torso. A one second pause at the bottom of the squat was completed before returning to the start position. The participant had a maximum of three trials to complete the movement to the best of his/her ability. The second movement in the FMS (Table C6) was the hurdle step. This movement is designed to assess mobility and stability of the hips, knees, and ankles. The height of the hurdle was set to the height of the participant’s tibial tuberosity. The participant (while holding a dowel behind the head and across the shoulders) was instructed to step over the hurdle with one leg, touch the ground on the other side of the hurdle (without accepting weight), and then return the leg back over the hurdle. This test was completed bilaterally. The participant had a maximum of three trials to complete the movement to the best of his/her ability. The third movement of the FMS (Table C6) was the in-line lunge. This movement is designed to assess quadriceps flexibility, hip mobility, and stability, and bilateral ankle and knee stability. The participant stood on a 2 x 6 board and held a dowel behind the back. The dowel maintained three points of contact (base of skull, thoracic spine, and sacrum) throughout the lunge. The opposite hand of the front foot was used to grasp the dowel at the head while the 8 other hand was placed on the dowel in the lumbar spine. The height of the tibial tuberosity was used as the distance between the two feet. The back knee touched the board behind the front foot and the feet were kept in the sagittal plane during the lunge. This test was assessed bilaterally. The participant had a maximum of three trials to complete the movement to the best of his/her ability. The fourth movement of the FMS (Table C6) was the shoulder mobility test. This movement is designed to assess shoulder range of motion. The tester measured (in inches) the length of the participant’s hand from the crease of the wrist to the end of the third finger. The participant was then instructed to close the fist, and maximally adduct, extend, and internally rotate with one shoulder and maximally abduct, flex, and externally rotate the other. The flexed shoulder was the side that was scored. The tester then measured the distance between the two fists. The test was assessed bilaterally. The participant had a maximum of three trials to complete the movement to the best of his/her ability. The shoulder clearing test (Tale C6) was performed at the end of the shoulder mobility test. This movement was not scored but was used to observe a pain response. This clearing test is necessary to detect impingement symptoms that can go undetected with the shoulder mobility test. The individual was instructed to place the hand on the opposite shoulder and attempt to point the elbow upward. If pain was produced, a score of zero was given for the test. The clearing test was performed bilaterally. The fifth movement in the FMS (Table C6) was the active straight leg raise. This movement is designed to assess active flexibility of the hamstrings and gastroc-soleus complex while maintaining a stable pelvis and core. The participants were instructed to lie on the back with the 2 x 6 board under the knees with the leg straight. The leg that was not tested remained in 9 contact with the floor with the foot in a dorsiflexed position. The tester then identified the midpoint between the ASIS and midpoint of the patella. A dowel was then placed perpendicular to the floor at the measured midpoint. While maintaining contact with the floor through the head and lower back, the participant was instructed to raise the test leg with a dorsiflexed ankle and extended knee as far as possible. If the malleolus did not pass the dowel, the dowel was moved in line with the malleolus of the test leg and scored per the criteria. This test was performed bilaterally. The participant had a maximum of three trials to complete the movement to the best of his/her ability. The sixth movement in the FMS (Table C6) was the trunk stability push-up. This movement is designed to assess trunk stability while a closed-chain upper body motion is completed. The participant assumed a prone position with the hand spaced shoulder-width apart and the feet together. Females were instructed to place thumbs in line with the chin. Males were instructed to place thumbs in line with the forehead. The participant was then instructed to lift the body as a unit with the knees extended and ankles dorsiflexed to complete one push-up. If the participant was not able to complete the push-up the hand position was moved level with the chin for males, and moved level to the clavicle for females. The participant had a maximum of three trials to complete the movement to the best of his/her ability. The spinal extension clearing test (Table C6) was performed after the trunk stability push-up. This movement was not scored but was used to observe a pain response. The clearing test is necessary to detect back pain that can go undetected with movement screening. The participant was instructed to perform a press-up in the push-up position. If pain was produced, a score of zero was given for the test. 10 The seventh movement in the FMS (Table C6) was the rotary stability test. The participant was instructed to assume a quadruped position with both hands and both feet on the ground at relatively 90 degree angles (shoulders relative to the upper torso; hips/knees relative to the lower torso). The 2 x 6 board was placed between the knees and hands so that both the hands and knees are touching the board. The participant was then instructed to lift the arm and leg (flexes shoulder, extends hip) on the same side and attempt to touch the knee and elbow together. If the participant was unable to complete such a repetition, the pattern changed to a diagonal pattern (opposite arm and leg). This test was performed bilaterally. The participant had a maximum of three trials to complete the movement to the best of his/her ability. The spinal flexion clearing test (Table C6) was performed at the end of the rotary stability test. This movement was not scored, but was used to observe a pain response. The purpose of this clearing test is necessary due to back pain going undetected by movement screening. Spinal flexion was cleared when a quadruped position was assumed, and then rocked back to touch the buttocks to the heels and chest to the thighs. Hands remained in front of the body, reaching out as far as possible. If pain was produced, a score of zero was given for the test. Active knee extension test: The next measurement in the screening tool was hamstring length. Procedures that have been previously described were used for the active knee extension test and are outlined in Table. C7.42,53 The subject was supine on the table and was instructed to flex the testing extremity to 90 degrees and maintain that position. The investigator then secured the non-tested extremity to the table using a strap across the lower third of the thigh. The subject was then instructed to extend the knee as far as possible while keeping the foot in a relaxed position and held that position for approximately five seconds. The investigator then aligned the fulcrum of the goniometer to the midpoint of the lateral joint line, aligned the stationary arm to 11 the greater trochanter of the femur, and aligned the movable arm to the lateral malleolus of the fibula. An angle measurement in degrees was taken from the goniometer. This test was performed bilaterally. The participant had two trials bilaterally, one after the other, and the average of both was taken. Palpation meter (PALM): Procedures that have been previously described were used for assessment of pelvic angle and are outlined in Table C847,48 The investigator created markings on the floor that are 30 cm apart that the participant stood on. Participants adopted an erect posture and kept arms crossed over the chest. Participants were instructed to look at a fixed point ahead of them as to help control for postural sway. Palpation by the investigator was performed over the clothes. Palpation began by locating the ASIS bringing the thumbs inferior to superior and marked the most prominent protrusion with an adhesive felt pad. The investigator then located the PSIS by following the iliac crest with the thumbs first posteriorly, then superior and laterally from the sacrum and marked the most prominent protrusion with an adhesive felt pad. The subject held the pads in place as to limit movement of the pads over the athletic shorts. The calipers were placed over the marked ASIS and PSIS on the ipsilateral side and compressed to a firm resistance. The angle of inclination was read from the inclinometer built into the PALM device. Positive degrees were used to describe anterior innominate tilts, and negative degrees were used to describe posterior innominate tilts. The test was performed bilaterally. The participant performed two trials bilaterally, one after the other, and the average of both was taken. Hip range of motion: Active hip range of motion was assessed by a goniometer for hip flexion, extension, abduction, adduction, internal rotation, and external rotation. These motions and the goniometer measurements for each are outlined in Table C9. The tests were performed 12 bilaterally for all six motions. The participant performed two trials bilaterally, one after the other, and the average of both was taken. Hip flexion measurements52 were taken with the participant lying in supine. The participant was then instructed to actively flex the hip as far as possible with the knee in a flexed position. The fulcrum of the goniometer was placed at the greater trochanter of the femur, the stationary arm was aligned parallel to the trunk of the participant, and the movement arm was aligned with the midpoint of the lateral joint line. Angle measurements were taken from the goniometer in degrees. Hip extension measurements22,52 were taken with the participant lying prone with the extremity extended beyond the table. The participant was then instructed to actively extend the hip as far as possible. The fulcrum of the goniometer was placed at the greater trochanter of the femur, the stationary arm was aligned parallel to the trunk of the participant, and the movement arm was aligned with the midpoint of the lateral joint line. Angle measurements were taken from the goniometer in degrees. Hip abduction measurements23,52 were taken with the participant in a side lying position. The participant was then instructed to actively abduct the hip as far as possible. The fulcrum of the goniometer was placed at the ASIS of the tested leg. The stationary arm was aligned with the contralateral ASIS, and the movement arm was aligned with the midpoint of the patella. Angle measurements were taken from the goniometer in degrees. Hip adduction measurements52 were taken with the participant in a standing position. The participant was then instructed to actively adduct the hip as far as possible. The fulcrum of the goniometer was placed at the ASIS of the tested leg. The stationary arm was aligned with the 13 contralateral ASIS, and the movement arm was aligned with the midpoint of the patella. Angle measurements were taken from the goniometer in degrees. Hip internal rotation52 was taken with the participant in a short-seated position. The participant was then instructed to actively internally rotate the hip as far as possible. The fulcrum of the goniometer was placed at the center of the patella. The stationary arm was aligned horizontally with the table, and the movement arm was aligned with the shaft of the tibia. Angle measurements were taken from the goniometer in degrees. Hip external rotation23,52 was taken with the participant in a short-seated position. The participant was then instructed to actively externally rotate the hip as far as possible. The fulcrum of the goniometer was placed at the center of the patella. The stationary arm was aligned horizontally with the table, and the movement arm was aligned with the shaft of the tibia. Angle measurements were taken from the goniometer in degrees. All data from these measurements were recorded on the FMS scoring sheet (Table C10) and the data collection sheet (Table C11). Statistical Analysis Descriptive analysis consisted of means and standard deviations of all subjects for demographic information, FMS composite scores, active knee extension test, PALM, and hip range of motion measurements. To determine the strength of the relationship between all variables, Pearson’s Correlation Coefficient was used. Relationship strengths are defined as small (.1-.29), medium (.3-.49), and large (.5-1.0).54 To determine predictors of injury other statistics including binary logistic regression, Cox & Snell R2, Nagelkerke R2, and odds ratio were used with 95% Confidence Intervals. A binary logistic regression was used producing a Cox & Snell pseudo R2, Nagelkerke pseudo R2, and odds ratio statistics. The higher the Cox & 14 Snell pseudo R2, and Nagelkerke pseudo R2 the better the model fits the data. The ability to predict outcomes or characteristics that may predispose an athlete to sustain a SIJD can be useful both clinically and in applied settings. Eleven models were selected to indicate best fit. The first model compared FMS composite scores and SIJ injury history. The second model compared the average of both extremities’ active knee extension test and SIJ injury history. The third model SIJ compared the average of both innominates’ pelvic angle tilt measurement from the PALM and SIJ injury history. The fourth through ninth model compared the average angle for both extremities for active hip flexion, extension, abduction, adduction, internal rotation, and external rotation and SIJ injury history. The tenth model compared years of playing soccer and SIJ injury history. The eleventh model compared current athletic participation and SIJ injury history. A stepwise binary logistic regression was analyzed to investigate any interaction between the previous eleven variables. The P value was set at P = 0.05 for all analyses. IBM/SPSS software (IBM/SPSS, Inc., Chicago, IL) version 24.0 was used for all analyses. RESULTS Demographic Data Fourteen females (age = 16.00±1.11 yrs, height = 165.93±6.39 cm, mass = 61.11±6.92 kg) and six males (age = 16.33±1.37 yrs, height = 176.50±6.98 cm, mass = 72.12±9.92 kg) adolescent soccer athletes who participated on the varsity and/or junior varsity teams at one north central West Virginia High School volunteered for this study. Three (15%) of the subjects were in the freshman class, three (15%) of the subjects were in the sophomore class, ten (50%) of the subjects were in the junior class, and four (20%) of the subjects in the senior class. None of these subjects had an injury status that prevented them from any of the study measurements at the time 15 of data collection. Five (25%) of these athletes sustained a SIJ injury over the course of the previous soccer season. Other injuries that occurred over the course of the season were ankle injuries (n=3, 15%), knee injury (n=1, 5%), and hamstring injury (n=1, 5%). None of these players missed significant time from these injuries, and therefore were not excluded from the study. Position was divided into four categories, keeper (n=1, 5%), defense (n=8, 40%), midfield (n=8, 40%), and forwards (n=3, 15%). Descriptive subject data including age, height, weight, years playing soccer, playing soccer year-round, and current athletic activity is presented in Table D1. Descriptive subject data on the means and standard deviations of the screening variables for male and female participants are presented in Table D2. Descriptive subject data on demographics and the means and standard deviations of the screening variables between those who have an SIJ injury and those who do not are presented in Tables D3-D4. Correlation Coefficients Pearson correlation coefficients were run for the relationships between demographic data and SIJ injury (Table D5) and the relationships between the predictive variables and SIJ injury (Table D6). No significant correlations were found between SIJ injury, years playing soccer, and current athletics participation. Small to large correlations were present among the predictive screening variables and SIJ injury. A significant correlation with large strength (PCC = 0.545, p = .013) was found between SIJ injury and active hip abduction. As hip abduction increased so did the occurrence of a SIJ injury. A significant correlation with medium strength (PCC = 0.473, p = .035) was found between the AKET and active hip flexion. As hip flexion increased so did the AKET results. A significant correlation with large strength (PCC = 0.732, p < .01) was found between the PALM measurement and active hip extension. As the pelvis was tilted anteriorly active hip extension increased. 16 Cross Tabs of Lower Extremity FMS Movements A cross tabs of the three lower extremity based movements, deep squat, inline lunge, and hurdle step, from the FMS was run with SIJ injury occurrence set as the dependent variable. This information is presented in Table D7. The cross tabs revealed that those who did and did not have an SIJ injury scored similarly on the deep squat and hurdle step. The inline lunge, however, demonstrated that those without a SIJ injury performed well, whereas, the majority with a SIJ injury had decreased performance. Logistic Regression and Odds Ratios A binary logistic regression was run producing a Cox & Snell pseudo R2 and Nagelkerke pseudo R2 statistics. The higher the Cox & Snell pseudo R2 and Nagelkerke pseudo R2 statistics, the better the model fits the data. One model provided the best fit. The 2 x 2 contingency table using the variables SIJ injury and active hip abduction produced a Cox & Snell R2 (.282), Nagelkerke R2 (.418), and an odds ratio of 1.115 (CI95 = 1.003, 1.239, p = .044). This logistic model “moderately” fits the data and accounts for 28.2% - 41.8% of the variance of hip abduction being able to predict SIJ injury or not. The odds ratio for hip abduction increased the risk of SIJ injury by 11.5%. All other models did not produce statistically significant results and are presented in Table D8. Two nonsignificant models with moderate odds ratios were produced for the PALM (OR = 1.141, CI95 = .841, 1.547, p = .397) and years playing soccer (OR = 1.319, CI95 = .854, 2.036, p = .212) The models using the variables 1) SIJ injury and FMS composite scores; and 2) SIJ injury and years playing accurately predicted one subject with SIJ, however, did not produce statistically significant results for the entire model. A step wise binary logistic regression was run producing a Cox & Snell pseudo R2 and Nagelkerke pseudo R2 statistics to investigate interaction affects within and between the 17 variables. Two models provided the best fit. The 2 x 2 contingency table using the variables SIJ injury and active hip abduction produced the same outcome listed above. The second model included three variables, SIJ injury history along with hip abduction and FMS composite scores. All other variables were not found to be included into the model equation. This model produced a Cox & Snell R2 (.426), Nagelkerke R2 (.631), and an odds ratio of 1.168 (CI95 = 1.004, 1.359, p = .045). This logistic model “moderately” fits the data and accounts for 42.6% - 63.1% of the variance of hip abduction being able to predict SIJ injury or not. The odds ratio for hip abduction and FMS increased the risk of SIJ injury by 16.8%. The interaction term was not significant (OR = 1.003, CI95 = .999, 1.007, p = .095) between active hip abduction and FMS composite scores. All stepwise binary logistic regression statistics are presented in Table D9. DISCUSSION The main purpose of this study was to determine screening variables that can effectively predict SIJD for adolescent soccer athletes. The results of this analysis showed that there were large statistically significant correlations between active hip abduction and SIJ injury occurrence, and PALM measurement and active hip extension. There was also a medium statistically significant correlation between the AKET and active hip flexion. One model, active hip abduction, of the binary logistic regression produced a statically significant finding. The model reflected the concept that those with the highest angle of active hip abduction had an increased risk of an SIJ injury by 11.5%. All other models did not produce statistically significant results. A stepwise binary logistic regression produced another statistically significant model that included the FMS with active hip abduction. In this model, those with the highest angle of active hip abduction, and the lowest FMS composite scores had an increased risk of SIJ injury by 16.8%. These findings suggest that ROM, especially hip abduction, and FMS scores may be an 18 important consideration in deciding which variables to evaluate, as well as to consider for prevention and intervention strategies. As this is the first study to evaluate potential predictor variables for SIJD in adolescent soccer players, the findings from the current study cannot be directly compared with the prior studies that evaluated risk factors and the effect on low back pain in adolescents55 or the FMS in relation to low back pain.13 However, the results from those studies provide a basis as to why certain variables should be considered. Injury Demographics and SIJ Injury Among the 20 subjects that volunteered for this study, five had an SIJ injury, all females, over the course of the past soccer season. The higher incidence of SIJ injury in females compared to male counterparts may partially be explained by anatomical differences between the two sexes. In males, the articular surface between the sacrum and ilium are shaped like an “inverted L”, while in females they are generally smaller and more oblique shaping a “C” appearance.17,56 Females are also generally not able to produce as much force with muscle activation compared to males. This decreased muscle output could negatively impact the “force closure” mechanism. In this mechanism the latissimus dorsi works with the contralateral gluteus maximus to generate the force closure on the SIJ as co-activation occurs and force is transferred through the posterior layer of the thoracolumbar fascia.18,19,57 The decreased amount of stability at the SIJ could explain this observed difference in injury occurrence between sexes. Position on the team also had an influence on SIJ injury. The five with an SIJ injury, two were backfield players, and three were midfielders. This is in agreement with current literature as midfielders have been reported to be at the highest rate of LBP potentially caused by an SIJ injury.10 This could be due in part that midfielders cover the most distance throughout the 19 game.58 Upon movement, roles are switched between attacking and defending. This involves increased use of the hip adductors and abductors which may lead to an inflare or outflare of the innominates59 This may result in a compression of the SIJ and a decrease of mobility in the joint. An inflare or an outflare could be potential mechanisms for the creation of pain and dysfunction at the SIJ. It has been postulated that the number of years playing soccer may have an influence on developing an SIJ injury.60 Of the five with an SIJ injury, four currently play soccer year-round and all five remain physically active. These five subjects have also been playing soccer for 8, 11, 11, 14, and 15 years, respectively. The average number of years playing soccer amongst all subjects was 9.70 years. Although no statistically significant correlations were found between years playing, current physical activity, and SIJ injury, the potential for an SIJ injury exists via a chronic/overuse mechanism. Although current research is limited on the relationship between early sports specialization and overuse injury, especially with the low back, initial findings indicate that playing a sport for 8 months or greater over the year leads to an increased risk of overuse lower extremity injuries.61-63 When injuries were reported by type, low back overuse injuries in sport specialized athletes were 13.7% in relation to all the overuse injuries reported.60 Although the research is limited, currently there is a modest relationship showing that playing a sport year-round may increase risk of an overuse injury such as SIJ. Correlation of Hip Abduction to SIJ Injury Occurrence Hip abduction is a component of multiple functional movements of soccer and this may be contributing to SIJ injury as the results from this study found a positive large correlation between the two. The fundamental skills of soccer are the kick and running involving lateral 20 movement. Hip abduction occurs during the kicking motion and lateral movements, and contribute to the “force closure” mechanism.16,18,19 More specifically, during the backswing of the kicking motion, the hip is slowly abducted and externally rotated by a concentric contraction of the gluteus medius.64 The hip remains abducted and externally rotated during the initiation of forward motion through impact with the ball.64 Meanwhile the gluteus medius on the stance leg is activated to maintain hip stabilization during the kicking motion. The gluteus medius plays an important role in the kicking motion working both as a joint mover and as a stabilizer. With the repetitive kicking motions in soccer this muscle can be quick to fatigue. Soccer players also incorporate forward, backward, and lateral motions moving up and down the field. The sacral motions become increasingly complex during the gait cycle. In walking from heel strike to midfoot stance, and toe off the sacrum goes through rotational movement in both directions as well as side bending.65 These motions and the forces transferred through the SIJ are exacerbated during running. Stress at the SIJ is further increased from the lateral movements involved with cutting in soccer. Therefore, excessive and repetitive hip abduction may result in the gluteus medius decreasing the ability to maintain stabilization of the pelvis and the SIJ, altering the biomechanics and decreasing the effectiveness of the “force closure” mechanism. The decreased stability, created by excessive and repetitive hip abduction, at the SIJ will result in increased shear forces which leads to potential injury.17,65 68 Correlations of HROM to AKET and PALM Hamstring flexibility influences both the performance of active hip flexion and the AKET. The positive medium strength correlation from this study supported that. All subjects were able to bilaterally score a three on the active straight leg test suggesting that each subject 21 has good hamstring flexibility. This is further supported by the subjects exceeding the normative values for both active hip flexion and the AKET. The hamstrings muscles collectively are a two joint muscle as they act upon both the knee and hip joint.17 During active hip flexion the proximal portion at the ischial tuberosity is put under increased strain, whereas, during the AKET the distal portion at the knee is put under increased strain.17,41,57 A subject with increased hamstring flexibility performed well in both screening variables. Active hip extension and pelvic positioning produced a positive large correlation in this study. All of the subjects were recorded to have an anterior pelvic tilt that ranged from 2.25˚ to 18.25˚. This relationship may not be due to the strength of the gluteus maximus. Perhaps this relationship can be explained with soccer specific biomechanics. The hip flexors, such as the iliopsoas and the rectus femoris, undergo eccentric contraction in the back swing followed by a powerful concentric contraction for the remaining portions of the kicking motion.69,70 This load from the hip flexors pulls on the pelvic innominates anteriorly. Additionally, an overused iliopsoas muscle may increase lumbar lordosis and inhibit transverse abdominis activation. An increased lumbar lordosis in turn creates an increased anterior pelvic tilt.71,72 The anterior pelvic tilt, altered the biomechanical positioning of the subjects’ pelvis. This altered positioning may have allowed compensation from other muscles, such as the hamstrings, to produce more force leading to increased performance in active hip extension.18,20 Model of Predicting SIJ Injury The best fit model for predicting SIJ injury was hip abduction. The odds ratio that was produced interpreted that those with the highest angle of hip abduction were at a 11.5% increased risk for SIJ injury. This contradicts current literature that has found that a decrease, rather than an increase in hip abduction is related to having an SIJ injury.22,23 It is also reported in the literature 22 that decreases in hip extension, adduction, internal rotation, and external rotation are related to an SIJ injury.21,73 Although this information conflicts with current literature, the importance of hip range of motion should be addressed, especially if asymmetry is evident in the lumbopelvic region.74 Why an increase in hip abduction may be a concern is related to the biomechanical alteration that occurs at the sacrum during kicking, running, and lateral movements in soccer. The increase in hip abduction also may influence the “force closure” mechanism that is predominantly controlled by the latissimus dorsi, gluteus maximus, and thoracolumbar fascia.16 19,57 If the sacrum cannot properly serve as the gateway between the lower extremities and the spinal column, then the forces will remain in the SIJ and result in injury. This adaptation of excessive and repetitive active hip abduction was most likely acquired over time by the subjects in this study based off the physical demands of soccer and the longevity and frequency that they have played and trained. The other models that may have some relevancy for predicting an SIJ injury included the FMS, and years playing as screening variables. Each of these models were not statistically significant, however, each was able to accurately predict one case of a SIJ injury creating potential clinical relevancy. The FMS model produced an odds ratio interpreted as a higher composite score would decrease the risk of an SIJ injury by 50.5%. This odds ratio supported the concept that clinicians frequently use the FMS as a screening tool for injury risk, despite not being the original intent of the FMS. This interpretation of the FMS has been heavily investigated and the results show that athletes who score 14 or less points on the FMS are at an increased risk for injury.34-39,75 Specifically it has been cited that a score of 14 or less on the FMS resulted in a 4-fold increase of lower extremity risk of injury over the course of a season.34 23 Observed from this binary logistic regression model it accurately predicted SIJ injury for the subject who had the lowest score, 15, of all 20 subjects who volunteered. Conversely, the other four who sustained an SIJ injury performed well with scores of 18, 18, 19, and 19, respectively. Those scores align closer to the average FMS composite score for the non-injury group (18.6 ± 0.83). Overall the group performed well with an average FMS composite score of 18.4 ± 1.10, suggesting that the athletes in this population were highly trained and capable of performing efficient athletic movements. The model for years playing soccer produced an odds ratio, which was interpreted as those with the greatest amount of years played had an increased risk of SIJ injury by 31.9%. The subjects in this group had a mean of 9.70 ± 4.05 years of soccer experience with a mean age of 16.10 ± 1.17 years. Half of these subjects’ lives have been dedicated to playing soccer. Further, there is a clinical difference in years playing soccer between the SIJ injury and healthy group. The SIJ injury group had a mean of 11.80 ± 2.77 years of playing soccer, compared to 9.00 ± 4.24 years in the healthy group. Among the five with the injury, all have been playing for 8, 11, 11, 14, and 15 years, respectively. The model accurately predicted the subject who had played for 15 years. Additionally, the subject who had 14 years of experience is the same subject with a composite score of 15 whom was accurately predicted in the FMS model. Despite limited research available on years playing on the risk of developing an overuse injury, initial findings may support the clinical relevancy of this model as there is a modest relationship between playing year-round and sustaining an overuse injury in the lower extremity.60-63 Upon investigation of a stepwise binary logistic regression, a statistically significant model including both hip abduction, and the FMS together was produced. The odds ratio when the FMS was included increased from 11.5% to a 16.8% risk of SIJ injury. This odds ratio may 24 be low; however, it holds clinical significance. The increased risk of injury suggested that these two screening variables are related to each other. The seven fundamental movements of the FMS are primarily performed in the sagittal plane; however, the subject must be able to maintain stability to not deviate into the frontal or transverse plane. This stability is controlled partly by the gluteus medius, which is the main contributor to hip abduction. The need to activate the gluteus medius during certain functional movements may be why the model’s ability to predict an SIJ injury improved with the inclusion of the FMS. The more applicable movements for soccer in the FMS are those performed in standing, including the deep squat, hurdle step, and inline lunge. Only one study has reported individual scores of the seven fundamental movements in those with chronic LBP.13 A decrease in performance for the deep squat and hurdle step were found in that study.13 Upon investigation of the individual scores from the subject who was accurately predicted by the model, the subject had decreased scores in the deep squat, hurdle step, inline lunge, trunk stability push up, and rotary stability. These decreased scores directly supported the findings of Ko et al.13 that the deep squat, hurdle step, and inline lunge are applicable to soccer. The other four subjects with SIJ injury also support the findings of Ko et al.13 The first subject had decreased performance on the deep squat and hurdle step, the second and third subjects had decreased performance on the inline lunge, and the fourth subject had decreased performance on the hurdle step. These four subjects also performed poorly on the rotary stability, however, performed well on the three remaining movements. When compared to the subjects without a SIJ injury they too produced mixed results with the deep squat and hurdle step, which may suggest an altered biomechanical pattern in soccer players exists. The subjects without a SIJ injury performed very well on the inline lunge, whereas the SIJ injury group had mixed results. This may suggest that those with an SIJ injury have poor hip stability which may 25 explain their poor performance with the inline lunge. This model may be a link to predict an SIJ injury, along with excessive hip abduction that may be caused by a dysfunctional gluteus medius and may explain decreased performance in the FMS. Clinical Importance This is the first screening tool model created for predicting an SIJ injury within this athletic population. Clinicians may use the information created by these models to develop a preseason screening tool. Two models in this study indicated a good fit for prediction which may develop a potential clinical prediction rule for clinicians to utilize active hip range of motion and the FMS in preseason screening. The model that included active hip abduction produced an odds ratio that a clinician may interpret large hip abduction measurements increased the risk of SIJ injury by 11.5%. Therefore, clinicians should be conscious of hip range of motion abnormalities in active athletic populations. In soccer, it is necessary for the hip to have six degrees of freedom to efficiently perform the running and kicking biomechanics of the sport. These motions at the hip interact in concert with motions occurring at the pelvis, sacrum, and SIJ. If one of the components has dysfunction this may transfer up the kinetic chain and create SIJD, therefore assessing hip range of motion is a necessary component to consider for a SIJD screening tool in soccer athletes. For this reason, all hip range of motion measurements, and not only hip abduction, should be included in a prediction model. When the model included the FMS with hip abduction, the odds ratio improved and was interpreted that large active hip abduction angle measurements, with low FMS composite scores resulted in a 16.8% increased risk of SIJ injury. For clinicians this shows relev

Exploring the Use of Sport as a Platform for Health Promotion with Youth in Africa: A Scoping Review. Exploring the Use of Sport as a Platform for Health Promotion with Youth in Africa: A Scoping Review. Adam H. Hansell Follow this and additional works at: https://researchrepository.wvu.edu/etd Recommended Citation Hansell, Adam H., "Exploring the Use of Sport as a Platform for Health Promotion with Youth in Africa: A Scoping Review." (2018). Graduate Theses, Dissertations, and Problem Reports. 8209. https://researchrepository.wvu.edu/etd/8209 This Thesis is protected by copyright and/or related rights. It has been brought to you by the The Research Repository @ WVU with permission from the rights-holder(s). You are free to use this Thesis in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you must obtain permission from the rights-holder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/ or on the work itself. This Thesis has been accepted for inclusion in WVU Graduate Theses, Dissertations, and Problem Reports collection by an authorized administrator of The Research Repository @ WVU. For more information, please contact researchrepository@mail.wvu.edu. Exploring the Use of Sport as a Platform for Health Promotion with Youth in Africa: A Scoping Review Adam H. Hansell Master’s Thesis submitted to the College of Physical Activity and Sport Sciences at West Virginia University in partial fulfillment of the requirements for the degree of Masters of Science in Sport and Exercise Psychology Peter Giacobbi Jr., Ph.D., Chair Dana K. Voelker, Ph.D. Ed Jacobs, Ph.D. Department of Sport and Exercise Psychology Morgantown, West Virginia 2018 Keywords: sport, health promotion, Africa, youth development, disease, community, intervention Copyright 2018 Adam H. Hansell ABSTRACT Exploring the Use of Sport as a Platform for Health Promotion with Youth in Africa: A Scoping Review Adam H. Hansell According to the World Health Organization, Africa has the highest rates of disease and child mortality in the world. Previous research suggests that sport may be an effective vehicle to enhance health knowledge and behaviors among at-risk youth. The primary purpose of this review was to analyze and synthesize published interventions exploring the use of sport or physical activity for health promotion with children and youth in Africa. A total of 916 articles were retrieved from ten electronic bibliographic databases with 28 meeting inclusion criteria. Targeted health outcomes in sport-based interventions included HIV-related knowledge and behaviors, essential health practices, physical and mental health, physical activity, and overall fitness levels. Statistically significant improvements in targeted health outcomes were observed in 23 of the 28 interventions included. However, the authors conducted risk of bias ratings for each study, and 23 articles were rated as having a “serious” or “critical” risk of bias. Our findings suggest that the use of sport- and physical activity as a health promotion intervention may be an effective with children and youth in Africa. However, future researchers must incorporate more rigorous methodological approaches, such as randomized controlled trials with wait-list control or crossover design. iii Table of Contents Page Introduction 1 Methods Overview 7 Study Identification and Data Sources 8 Identification and Selection of Relevant Studies 8 Data Charting and Synthesis 9 Risk of Bias 10 Consultation with Practitioners 11 Results Outcomes 12 Contextual Considerations 14 Funding 18 Risk of Bias 21 Practitioner Feedback 21 Discussion Characteristics of Interventions 32 Recommendations for Future Research 35 Recommendations Based on Practitioner Feedback 38 Limitations 39 References 43 Appendices Expanded Literature Review 52 Limitations 88 Definition of Terms 92 Coding Sheet 93 IRB Approval 94 SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 1 Exploring the Use of Sport as a Platform for Health Promotion: A Scoping Review Infectious diseases such as pneumonia, diarrhea, and malaria are the primary cause of child mortality in Africa (Black et al., 2010; Liu et al., 2015). It has been estimated that more than ten million children under the age of five die every year, and nearly all of these deaths occur in poor, developing countries (Black, Morris, & Bryce, 2003). In 2000, 36 of the 42 countries with the highest global rates of under-five child mortality were in Africa (Black et al., 2003). Since the 1990s, many countries in sub-Saharan Africa have experienced increases in child mortality rates, while others have experienced stalled or slowed progress in this domain (Fotso, Ezeh, Madise, & Ciera, 2007). Another recent report highlighted sub-Saharan Africa as having the world's highest child mortality rate with over three million deaths of children under the age of five, meaning that one child out of every 12 dies before their fifth birthday (United Nations, 2015). Since 2000, 64.3% of deaths in children under five were attributed to infectious diseases, reflecting nearly five million premature deaths (Liu et al., 2015). Infectious diseases were also a leading cause of death for older children and adolescents in Africa, with pneumonia (14.7%), diarrhea (9.9%), and malaria (7.4%) serving as the three biggest culprits (Liu et al., 2015). The World Health Organization reported that Africa has the highest incidence rates of infectious diseases in the world, which include HIV and AIDS, tuberculosis, and malaria (World Health Organization, 2016). Compared to other global regions, HIV incidence rates were over seven times higher in the African Region in 2014 with an average of 2.6 people out of 1000 being infected (World Health Organization, 2016). Globally, of a total of 438,000 deaths caused by malaria in 2015, roughly 90% of fatalities occurred in sub-Saharan Africa, and approximately 70% of deaths were children under the age of five. Africa also had the highest incidence rates of tuberculosis in 2014, with 281 cases per 100,000 people (World Health Organization, 2016). SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 2 Therefore, Africa has the highest incidence and mortality rates of three of the world’s most deadly infectious diseases, which highlights the urgent need for interventions and resources. The World Health Organization (2016) reported that Africa also had the highest number of deaths caused by exposure to unsafe drinking water and inadequate sanitation and hygiene practices. Nearly half of an estimated total of 871,000 global deaths caused by unsafe water exposure occurred in Africa in 2012. The vast majority of these deaths were caused by infectious diseases contracted from contaminated drinking water and inadequate or non-existent hygienic facilities (World Health Organization, 2016). Another study estimated that unsanitary water was responsible for approximately 1.5 million deaths in children in 2000 (Black et al., 2003). Clearly, exposure to, and the use of, contaminated water is a risk factor for early mortality. Due to the dangers posed by exposure to and use of contaminated water, tangible and educational resources should be allocated to communities that are exposed to unsafe water. Socioeconomic status is one of the primary risk factors for acquiring infectious diseases as individuals living in poverty are far more likely to contract these ailments (World Health Organization, 2016). In addition to being at higher risk of contracting infectious diseases, individuals living in poverty often have limited access to resources that can treat infectious diseases after they are contracted (World Health Organization, 2016). Given the disproportionate amount of people living in poverty in Africa compared to the rest of the world, interventions and resources aimed at improving these conditions should be allocated to at-risk communities. Although education and awareness initiatives may have the most long-term preventative impact, there are numerous tangible resources that could both prevent and treat different infectious diseases. These include condoms to prevent the spread of HIV and AIDS, bed nets to help SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 3 protect against malaria and other mosquito-borne illnesses, and water filtration systems to help reduce the instances of infectious diseases caused by contaminated water. It has been noted that 63% of child deaths caused by disease could have been prevented by implementing known and effective interventions, such as vaccines (Bryce et al., 2003). However, many poor and middle-income African countries have unacceptably low accessibility to these essential health resources (Bryce et al., 2003). Thus, it is imperative for researchers to develop feasible health promotion interventions that align with the health-system development of the countries they are aiming to help (Bryce et al., 2003). For example, initiatives could focus on collecting data at the community level to assist and inform public health planning in an attempt to promote widespread accessibility to known and effective interventions such as condoms, water filters, and vaccines (Bryce et al., 2003). Therefore, one plausible direction for future health initiatives would involve a shift in focus away from medical services in hospitals and clinics towards community-based approaches, particularly in countries where the overall access to public health services is poor or non-existent. One example of a preventative, educational approach to health promotion that also can provide tangible resources involves the use of sport. Sport for development initiatives, which use sport as a vehicle to promote positive social change, have become increasingly popular in recent years (Schulenkorf, Sherry, & Rowe, 2016). Specifically, sport for development programs use the popularity of sport to attract large groups of individuals, and use sport-related themes to discuss and initiate positive development (Jones et al., 2017; Schulenkorf et al., 2016). Previous researchers have used sport as a platform to achieve a broad range of positive outcomes for individuals and communities, including disease management and prevention, improved physical and mental health outcomes, life skills development, gender equity, and social cohesion (Jones et SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 4 al., 2017; Schulenkorf et al., 2016). Based on this approach, sport-based programs have potential to play a significant role in helping at-risk youth navigate their environments. Previous research suggests that participation in sport promotes the development of important life skills such as goal-setting, teamwork, discipline, decision-making, time management, and emotion regulation (Theokas et al., 2008). Life skills that are deliberately taught through sport can steer youth away from various risk-taking behaviors that may lead to lifelong consequences, such as substance abuse, sexual activity, and crime (Kulig, 2003). For instance, sport programs can help youth develop essential life skills such as self-efficacy, confidence to withstand peer pressure, and the ability to develop healthy coping strategies, all of which can significantly reduce the chances of contracting an infectious disease (Balfour et al., 2013; Whitley et al., 2016). A recent review of sport for positive youth development research found that sport involvement was most commonly linked to confidence and positive identity, which may contribute to the avoidance of risk-taking behaviors among at-risk youth (Jones et al., 2017). In addition to protecting against non-communicable diseases through life skills development, previous research also suggests that sport is an advantageous platform to educate youth about common infectious diseases and essential health practices as well (Fuller et al., 2010; Kaufman, Spencer, & Ross, 2013). Considering the inherent physical, mental, and social benefits that are associated with playing sport, sport for development initiatives have significant potential to help at-risk youth in Africa (Jones et al., 2017). Instead of physical activity, children and adolescents often engage in maladaptive and self-destructive behaviors such as substance abuse and petty crime, which are often accompanied by unemployment and poverty (Draper et al., 2010; Uys et al., 2016). Using sport as a health promotion platform could also encourage youth to engage in positive and SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 5 adaptive behaviors with their peers while also being physically active (Schulenkorf et al., 2016). For instance, individuals who are involved in a sport-based health promotion initiative may be more likely to play sport in their spare time instead of engaging in risky behaviors such as substance abuse or crime. It has also been well established that exercise and other forms of physical activity can reduce risk factors associated with obesity, diabetes, and cardiovascular disease (Booth, Gordon, Carlson, & Hamilton, 2000; Pedersen, 2006). Therefore, using a health promotion program that engages youth in physical activity can reduce the risks of developing non-communicable diseases through physical activity as well as promote the development of adaptive life skills. Given the worrying statistics regarding infectious diseases in Africa, researchers have also explored using sport for development initiatives to provide youth with resources to protect themselves against infectious diseases such as HIV and malaria (Fuller et al., 2010). The results of a recent systematic review found strong evidence that sport-based health promotion interventions can positively influence HIV-related knowledge, attitudes, stigma, self-efficacy, and communication skills with children and youth in Africa (Kaufman et al., 2013). Although it is unclear how long these improvements are sustained beyond the intervention, it is evident that sport-based initiatives can be effective in educating youth in Africa about infectious diseases and equipping them with protective skills and resources (Kaufman et al., 2013). Although improving national health systems should be the ultimate goal to reduce rates of child mortality, small-scale community-based interventions have been successful in improving overall and disease-specific health knowledge and awareness for children, adolescents, and adults (Balfour et al., 2013; Clark et al., 2006; Fuller et al., 2010; 2011; 2015; Maro, Roberts, & Sørensen, 2009). For instance, three studies used soccer as a platform to educate 5,128 youth SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 6 participants about various infectious diseases, the use of clean water, safe sex, basic sanitary health practices, getting vaccinated, taking prescribed medications, and nutrition (Fuller et al., 2010; 2011; 2015). Following the sport-based interventions, participants’ mean health knowledge scores were 14.3% higher in South Africa, 18.4% higher in Zimbabwe, and 17.8% higher in Mauritius, which highlights the effectiveness of these programs in improving the health awareness and knowledge among children in rural, low-income communities (Fuller et al., 2010; 2011). In the study conducted by Fuller et al. (2015), participants’ mean health knowledge scores following the sport-based intervention were 25.1% higher in Ghana, 10.3% higher in Malawi, 27.4% higher in Namibia, 15.1% higher in Tanzania, and 17.2% higher in Zambia. Furthermore, it has been noted that the use of sport at schools in South Africa can provide a safe place for students to learn and participate in organized activities (Struthers, 2011). The use of sport is an innovative and fun way to promote positive and sustainable health changes with potentially large numbers of youth in communities throughout Africa. Future research that targets the use of soccer and other types of sport as platforms to educate children about essential health practices warrants further exploration. As discussed, previous research suggests that the use of sport as a platform to educate children and adolescents can be a successful vehicle for improving health and disease-specific knowledge among children and youth in many African countries. Based on the observed improvements in health knowledge among youth participants following sport-based health promotion interventions, it is worth investigating the use of sport as a platform for health promotion in a more systematic manner. As this body of research continues to expand, it is important to analyze and synthesize effective components of previous interventions to inform future efforts. A close analysis of the long-term sustainability of these types of programs, SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 7 theoretical considerations, how these interventions were delivered and by whom, and other aspects of the interventions (e.g., gender) could inform future efforts that maximize impact with limited resources. Scoping reviews are ideally suited to address these issues because they provide researchers with a descriptive analysis about the breadth and the depth of a research field and provide justification for future systematic and quantitative reviews (Levac, Colquhoun, & O'Brien, 2010). Although there have been several attempts to promote necessary public health practices that could significantly reduce the high rates of child mortality in Africa, a structured synthesis of this literature could guide future interventions. This is particularly true for rural areas and communities where public health services are hard to access (Bryce et al., 2003). Considering the urgent need for effective interventions to improve rates of child mortality in Africa, a detailed review of the effectiveness of previous health promotion interventions using sport as a delivery mechanism would be helpful for directing future research endeavors in this domain. Specifically, the primary aim of this scoping review is to provide a detailed summary of the measured outcomes observed in previous studies that investigated the use of sport as a platform for health promotion with youth in Africa. Secondary purposes are to identify characteristics of interventions related to the length, nature, content, and methods employed in previous sport based interventions targeting children and youth in Africa. A third purpose was to conduct a risk of bias assessment to thoroughly analyze the methodologies employed in each intervention (Sterne et al., 2016). Finally, to increase the translational utility or practical impact of this study, the major findings will be presented to practitioners in the field for their feedback. Method Overview SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 8 In line with recommendations by Levac et al. (2010), the steps for the current scoping review included the following: (1) identification of the research question; (2) identification of relevant studies; (3) study selection; (4) charting of the data; (5) data synthesis; and (6) consultation with practitioners (e.g., coaches and staff members of sport-based non-profit organizations in Africa). Additionally, the first author independently coded each article included in our review for Risk of Bias using the ROBINS-I tool for assessing risk of bias in non randomized studies of interventions (Sterne et al., 2016). Study Identification and Data Sources Citations were retrieved from ten electronic bibliographic databases (Academic Search Complete, CINAHL, eHRAF, ERIC, Google Scholar, Physical Education Index, PsycInfo, PubMed, SportDiscus, and Web of Science). Keywords included sport, health promotion, Africa, youth, children, adolescents, youth development, disease, community, mortality, and intervention. A range of health terms and disease processes including HIV, AIDS, malaria, and clean water were included in this search, and relevant Medical Subject Headings (MeSH) terms were included. MeSH terms contain all relevant search terms identified by the United States National Library of Medicine’s thesaurus (USNLM, 1999). All searches were conducted in consultation with a West Virginia University Librarian in order to identify all appropriate databases and ensure the use of relevant MeSH terms. Studies were not bound by a specific date range in order to gain a comprehensive assessment of sport-based interventions targeting health promotion outcomes among youth in Africa. Identification and Selection of Relevant Studies For purpose one of the scoping review, the inclusion criteria included the following: (1) the use of sport as the intervention method; (2) the study being conducted in Africa; (3) youth SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 9 participants 24 years of age or younger, or families that included individuals that were 24 years old or younger; (4) pre/post measurements conducted before and following an intervention, and (5) publications in English. Studies were selected by the first author and were reviewed in consultation with the senior investigator. Data Charting and Synthesis To address the second purpose of this study we focused on articles that included sport based interventions. A codebook was developed by the first author which is shown in Appendix D. Variables included the following: (1) study author(s); (2) journal publication and year; (3) study design; (4) study outcomes; (5) country in Africa where study was conducted; (6) total sample size; (7) number of completers; (8) age range and mean age of participants; (9) participant gender; (10) setting of intervention; (11) duration of study; (12) theoretical foundation of interventions; and (13) source of funding. The first author independently coded, with input from the second author, all studies that met our review’s inclusion criteria. Study outcomes were charted and synthesized in three steps. First, the first author read each abstract and documented the outcomes being investigated from terms used in the study titles, abstracts, and key words. This process allowed the first author to observe thematic similarities in measured outcomes across studies which led to the development of a coding template. This template was used in a second round of coding by the first author to qualitatively describe the outcomes observed. A list of outcomes was developed by the first author in consultation with the senior investigator and each outcome was given a dummy code. The outcome frequencies were then calculated among all the included studies using the frequency command in IBM's Statistical Package for the Social Sciences (IBM SPSS). SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 10 Levac and colleagues (2010) suggest that scoping reviews are ideally suited to map the range, extent, and nature of previous research initiatives, and they may inform future research endeavors, including quantitative reviews. Importantly, scoping reviews differ from systematic reviews in the wider breadth of research questions that can be addressed as well as an emphasis on the narrative integration of extant research evidence (Levac et al., 2010). Given that the use of sport-based health promotion interventions with youth in Africa is a relatively new line of research with a clear scope of inquiry and a broad range of research questions, scoping reviews are ideally suited to review existing research regarding the use of sport-based interventions targeting health promotion outcomes for children and youth in Africa (Levac et al., 2010). Risk of Bias All articles were coded for risk of bias using the ROBINS-I tool for assessing risk of bias in non-randomized studies of interventions (Sterne et al., 2016). The ROBINS-I tool was developed over a three-year period by methodological experts and systematic review authors and editors (Sterne et al., 2016). The ROBINS-I tool allows for a comprehensive analysis of risk of bias in relation to a hypothetical randomized control trial, and the categories for risk of bias assessments are low risk, moderate risk, serious risk, and critical risk. If an article does not provide sufficient information to receive a risk of bias rating, it should be coded as no information (Sterne et al., 2016). In addition to addressing important confounding domains and co-interventions, the ROBINS-I tool asks a series of signaling questions across seven domains of bias; baseline confounding, selection of participants into the study, classification of interventions, deviations from the intended intervention, missing data, measurement of outcomes, and selection of the reported result (Sterne et al., 2016). Importantly, the judgments made for each of these seven domains of bias carry forward to an overall risk of bias for the SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 11 study. For example, if a study is deemed to have a moderate risk of bias in six domains and a high risk of bias in the seventh domain, then the article would be considered as high risk of bias. To receive a low risk rating, the risk of bias should be similar to that of a high quality randomized control trial (Sterne et al., 2016). Therefore, most non-randomized control trials are likely to earn a rating of at least a moderate risk of bias. Consultation with Practitioners The sixth and final step of scoping review methodologies is to incorporate consultation with relevant stakeholders to acquire additional insight beyond what is available in published literature (Levac et al., 2010). The first author contacted Grassroot Soccer, which is a non-profit organization that uses soccer to build resiliency in children and adolescents to help protect against the infection of HIV and other infectious diseases (Peacock-Villada, DeCelles, & Banda, 2007). The researchers created an anonymous survey on Qualtrics with a brief description of our preliminary findings and the following questions: (1) What is your role at Grassroot Soccer? (2) What is your gender?; (3) How many years of experience do you have working in Africa?; (4) Please share your general thoughts or observations about these research findings. What stands out to you?; (5) What steps could be taken to help sport-based health promotion?; and (6) What would you like to see in future sport-based health promotion interventions? An anonymous survey link was sent via email to staff members and coaches at Grassroot Soccer working in South Africa, Zambia, and Zimbabwe. Results from this survey were synthesized and exemplar quotations are presented to highlight the potential contributions of sport in future health promotion efforts. SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 12 Results A total of 916 articles were collected and screened for eligibility. The initial comprehensive database search yielded 322 duplicate publications, and a total of 594 articles remained after these were identified and removed. Following the removal of duplicate articles, the first author screened 540 titles and abstracts of the remaining search results to determine if they met the inclusion criteria for our review. Full texts of the remaining 54 articles were evaluated by the first author. Following this final review process, a total of 28 articles were deemed to meet the study’s eligibility criteria. If there was uncertainty about the eligibility of a specific article based on title and abstract alone, the first author obtained and evaluated a full text of the paper. A PRISMA flow diagram of this process is shown in Figure 1 that summarizes reasons for inclusion/exclusion throughout the review process. Outcomes Specific outcomes of each of the 28 articles that met inclusion criteria for this review are included in Table 1. Targeted outcome variables examined in these studies included HIV-related outcomes (n = 8); knowledge and awareness of nine essential health behaviors (physical activity, clean water use, proper sanitation practices, substance abuse, nutrition, malaria prevention, vaccinations, taking prescribed medications, HIV awareness, gender equality, and social support (n = 3); physical fitness (n = 9); physical activity levels (n = 6); social protective factors (n = 3); physical health (n = 4); mental health (n = 1); and injury prevention (n = 2). A total of 36 outcomes were examined in this review. The countries where each intervention was conducted are included in Table 1. Over half of the interventions included in this review were conducted in South Africa (n = 18). Other African countries Mauritius (n = 1), Namibia (n = 1), Nigeria (n = 1), Uganda (n = 1), SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 13 Identification Screening Eligibility Included Figure 1: PRISMA 2009 Flow Diagram Records identified through database searching (n=916) Records after duplicates removed (n=594) Assessment of titles and abstracts (n=594) Full-text articles assessed for eligibility (n=54) Studies included in qualitative synthesis (n=28) Articles excluded with reasons (n=540) Did not include sport (n=86) Did not include an intervention (n=360) Study was not conducted in Africa (n=21) Study did not include health promotion (n=12) Study did not include youth participants (n=61) Full-text articles excluded with reasons (n=26) Did not include sport (n=2) Did not include an intervention (n=11) Study was not conducted in Africa (n=2) Study did not include health promotion (n=4) Study did not include youth participants (n=7) SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 14 Zambia (n = 2), and multiple (n = 5). Eleven of 28 studies reported using specific theoretical frameworks to guide their efforts as shown in Table 1. These theories included Achievement Goal Theory (n = 3), Social Learning Theory (n = 3), the Social-Ecological Model (n = 2), Self Determination Theory (n = 1), the Theory of Planned Behavior (n = 1), and Psychosocial Theory (n = 1). The authors of the remaining 17 articles did not explicitly mention incorporating a theoretical foundation into their interventions. Contextual Considerations Additional contextual considerations for the studies included in our review are included in Table 2. Fifteen of the 28 interventions were conducted with youth in a school setting either as part of the existing school curriculum or immediately after school (See Table 2). Twelve interventions were conducted in community settings such as gyms, sporting venues, and health centers. One intervention included both in-school and community-based components (See Table 2). The majority of interventions were delivered by individuals from the community in which the research initiative took place who were trained in the intervention protocol. Specifically, trained peer coaches (n = 12), trained athletic coaches (n = 2), trained school staff members (n = 4), professional soccer players (n = 1), university students (n = 3), fitness trainers (n = 1), untrained teachers (n = 1), and principal investigators (n = 2) delivered the intervention to program participants (See Table 2). Two articles did not report who administered the intervention to participants. Based on the information provided in Table 2, the average sample size across all the interventions was 704 participants. There was an average of 199 dropouts across the interventions, leaving an average of 505 participants who completed the intervention. Of SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 15 Table 1. Results in selected studies Authors Outcomes Measured Country Theoretical Foundation Results Fuller et al. (2010) Fuller et al. (2011) Fuller et al. (2015) Clark et al. (2006) Maro et al. (2009) Maro & Roberts (2012) Hershow et al. (2015) Sørensen et al. (2016) Awotidebe et al. (2014) Bloemhoff (2006) Bloemhoff (2012) Nine essential health practices Nine essential health practices Nine essential health practices HIV/AIDS knowledge + stigma; awareness of local resources HIV prevention knowledge, attitudes, and awareness Effect of mastery motivational climate on HIV prevention, knowledge, and awareness HIV/AIDS knowledge, attitudes, communication skills, and HCT uptake Gender differences in HIV/AIDS prevention, knowledge, and awareness HIV knowledge and communication skills Resiliency and protective factors Resiliency and protective factors None None None Social Learning Theory Achievement Goal Theory Achievement Goal Theory Social Learning Theory Achievement Goal Theory Theory of Planned Behavior None None South Africa Mauritius and Zimbabwe Ghana, Malawi, Namibia, Tanzania, Zambia Zimbabwe Tanzania Tanzania South Africa Tanzania South Africa South Africa South Africa Significant improvements in knowledge of all measured outcomes Significant improvements in knowledge of all measured outcomes Significant improvements in knowledge of all measured outcomes Significant improvements in HIV/AIDS knowledge Significant improvement in HIV knowledge and awareness No significant improvement in measured outcomes due to mastery motivational climate Significant Improvements in all measured outcomes No significant differences in measured outcomes between boys and girls Significant improvements in HIV knowledge and negotiation skills Significant improvements in all measured outcomes Significant improvements in all measured outcomes SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 16 Table 1 Cont. Results in selected studies Authors Outcomes Measured Country Theoretical Foundation Results Kaufman et al. (2016) Voluntary Medical Male Circumcision (VMMC) uptake Chetty & Edwards (2007) Mental health promotion (self-esteem, depressive symptoms, behavioral problems) Ferguson et al. (2015) Motor skills, fitness Lennox & Pienaar (2013) Aerobic fitness; PA levels Monyeki et al. (2012) Naidoo et al. (2009) Body composition PA levels; sport participation; fitness tests; nutrition Naidoo & Coopoo (2012) PA levels; sport participation; fitness tests Owoeye et al. (2014) Parker et al. (2016) Richards et al. (2014) Injuries; injuries by type of exposure; injuries to lower extremities Pain severity; pain interference; self-efficacy; depression; quality of life Physical fitness; body composition; mental health Social Learning Theory Psychosocial Theory Social Ecological Model None None None None None None None Zimbabwe South Africa South Africa South Africa South Africa South Africa South Africa Nigeria South Africa Uganda Significant increase in VMMC uptake among participants Significant improvements in self esteem and physical self-perception; significant reduction behavioral problems Significant improvements in all measured outcomes No significant improvements in all measured outcomes No significant improvements in intervention condition Significant improvements in health behaviors and PA at school Significant improvements in all measured outcomes Significant reduction in all measured outcomes for participants’ in the intervention condition Significant reduction in pain for both conditions Significant improvements in cardiovascular fitness for both conditions; Significant decrease in positive mental health outcomes for boys SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 17 Table 1 Cont. Results in selected studies Authors Outcomes Measured Country Theoretical Foundation Results Starzak et al. (2016) Tian et al. (2017) Ley et al. (2014) Kemp & Pienaar (2009) Uys et al. (2016) Walter (2014) Peacock-Villada et al. (2007) Saliva tests for mucosal immunity and SNS activation; body composition; cardiovascular fitness PA levels Strength; cardiovascular fitness; weight; BMI Fitness outcomes; body composition PA levels; PA knowledge; fitness tests PA levels during school Resiliency; Decision making skills None Self Determination Theory None None Social Ecological Model None None South Africa South Africa South Africa South Africa South Africa South Africa South Africa; Zambia Significant improvements in measured salivary and fitness outcomes, significant reduction in BMI, body fat %, and waist circumference Significant improvements in MVPA Significant improvements in strength, no significant improvements in cardio fitness, BMI, weight Significant improvements in all measured outcomes Significant improvements in PA knowledge and fitness test outcomes, no significant improvement in PA levels Significant improvements in MVPA levels among participants Significant improvements in all measured outcomes SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 18 these 505 participants, an average of 280 participants were males and 225 were females. Additionally, the average age of participants across the included interventions was 14.08 years. Lastly, the average sport-based health promotion intervention included in our review lasted 21.23 weeks. Funding Of the 28 articles included in our review, 22 reported receiving funding for their intervention (Awotidebe et al., 2014; Chetty & Edwards, 2007; Clark et al., 2006; Ferguson et al., 2015; Fuller et al., 2010; 2011; 2015; Hershow et al., 2015; Kaufman et al., 2016; Kemp & Pienaar, 2009; Ley, Leach, Barrio, & Bassett, 2014; Maro et al., 2009; Maro & Roberts, 2012; Monyeki et al., 2012; Naidoo & Coopoo, 2012; Naidoo et al., 2009; Parker, Jelsma, & Stein, 2016; Richards Foster, Townsend, & Bauman, 2014; Sørensen et al., 2016; Starzak, Konkol, & McKune, 2016; Uys et al., 2016; Walter, 2014). Funding sources included FIFA (n = 3 articles), the International Development Research Center, Ottawa, Canada (n = 1 article), the Bill and Melinda Gates Foundation (n = 1 article), EMIMA Kicking AIDS Out Program (n = 3 articles), VLIR (n = 1 article), 3ie (n = 1 article), South African National Research Foundation (n = 1 article), University of Cape Town Research Committee (n = 1 article), Universidad Politécnica de Madrid (n = 1 article), the National Research Foundation (n = 2 articles), KwaZulu-Natal Department of Health and Education (n = 2 articles), the Dphil Scholarship: University of Oxford (n = 1 article), the Medical Research Council of South Africa (n = 1 article), the World Diabetes Foundation (n = 1 article), and the Nelson Mandela Metropolitan University (n = 1 article). One article mentioned receiving four sources of funding, including Imago Dei, the Elton SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 19 Table 2. Contextual Considerations Authors Setting Sport Personnel Sample Size Completed Age Gender Duration (Weeks) Fuller et al. (2010) School Soccer Trained peer coaches 492 370 13.3 M: 180 F: 190 11 Fuller et al. (2011) School + Community Soccer Trained peer coaches 822 784 12.3 M: 390 F: 394 11 Fuller et al. (2015) School Soccer Trained peer coaches 3,814 3,814 12.4 M:1873 F:1941 11 Clark et al. (2006) School Soccer Professional soccer players 304 304 12-14 M:151 F:153 2 Maro et al. (2009) Community Soccer Peer coaches 950 764 13.7 M:555 F:209 8 Maro & Roberts (2012) Community Soccer Peer coaches 950 764 13.7 M:555 F:209 8 Hershow et al. (2015) Community Soccer Peer coaches 4260 514 14.2 M:0 F:514 48 Sørensen et al. (2016) Community Soccer Peer coaches 950 764 13.7 M:555 F:209 8 Awotidebe et al. (2014) School Soccer Peer coaches 430 340 15.2 M:204 F:226 12 Bloemhoff (2006) Ropes Course Ropes Course Researcher 106 106 15.7 M:106 F:0 0 (4 hours) Bloemhoff (2012) Ropes Course Ropes Course Researcher 92 67 16.8 M:0 F:67 0 (4 hours) Kaufman et al. (2016) School Soccer Trained peer coaches 1226 878 16.2 M:1226 F:0 0 (1 hour) Chetty & Edwards (2007) Children’s Institutional Homes Soccer and Netball Unknown 33 33 10.7 M: 14 F: 19 12 Ferguson et al. (2015) School Playground games Undergraduate students 41 41 7.8 M: 18 F: 23 9 Lennox & Pienaar (2013) School Aerobic, strength, flexibility, sports (soccer and netball) Postgraduate students 318 279 14.5 M: 137 F: 181 26 SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 20 Table 2 Cont. Contextual Considerations Authors Setting Sport Personnel Sample Size Completed Age Gender Duration (Weeks) Monyeki et al. (2012) School Strength, speed, balance, stretching PE teacher 322 322 10.7 M: 322 F:0 43 Naidoo et al. (2009) School Active learning during school Trained teachers 256 185 Not reported M: 81 F: 104 26 Naidoo & Coopoo (2012) School Active learning during school Trained teachers 798 270 Not reported M: 147 F: 123 78 Owoeye et al. (2014) Sports’ field Warm-up activities Trained soccer coaches 416 385 17.7 M: 385 F:0 26 Parker et al. (2016) Community health center Aerobic and strength exercises Trained peer leaders 27 27 30.8 M: 0 F: 27 6 Richards et al. (2014) Community sports’ fields Soccer Trained peer coaches 1462 1447 12.9 M: 618 F:844 11 Starzak et al. (2016) Community sports’ fields Soccer Trained soccer coaches 50 34 12.2 M: 34 F:0 12 Tian et al. (2017) School Aerobic exercise (including soccer), strength training Trained PE teachers 110 Not reported Not reported M: 33 F: 77 12 Ley et al. (2014) Community gym Aerobic exercise, strength training, stretching Fitness trainers 50 23 30 M: 3 F:20 10 Kemp & Pienaar (2009) School Dancing, stretching Not reported 38 38 12.5 M:0 F: 38 10 Uys et al. (2016) School No prescribed activities Trained school staff 1088 997 9.9 M: 471 F: 526 156 Walter (2014) School Games, playground materials, sport equipment (soccer, rugby, netball) University students 120 79 10.3 M: 38 F:41 6 Peacock Villada et al. (2007) School Soccer Trained peer coaches 670 Not reported Not reported Not reported 6 SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 21 John AIDS Foundation, the MAC AIDS Fund, and the USAID-New Partners Initiative (Hershow et al., 2015). Lastly, one intervention stated that they used the 3rd author’s own research funding to finance their intervention (Starzak et al., 2016). Risk of Bias Ratings of risk of bias for each article were conducted by the first author. The final risk of bias ratings for each of the 28 interventions are reported in Table 3. Ten articles were deemed to be at critical risk of bias, thirteen articles were considered serious risk of bias, four articles were rated as moderate risk of bias, and one article was rated as no information (See Table 3). Most of the ratings of serious risk and critical risk resulted from the interventions missing a significant amount of participant data due to exclusion or attrition. Other reasons for ratings of serious or critical risk of bias were due to baseline confounding, lack of blinding of participants’ intervention status to researchers during the intervention, different start and follow-up times among participants, interventions not being classified appropriately, bias in the measurement of the outcome(s), and bias in terms of selecting the results that were reported. The article that received a rating of no information did not report sufficient information to make a risk of bias judgement. Practitioner Feedback Finally, in order to increase the translational utility and practical impact of the major findings presented above, five coaches and staff members employed by Grassroot Soccer responded to our survey and offered feedback on our findings. The five survey respondents included three females and two males with an average of 3.75 years of experience working with the organization. When asked to provide feedback on our results regarding the use of sport for health promotion with children and youth in Africa participants provided the following SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 22 responses: “I would confirm the outcomes are quite true, it’s something that’s on the ground. To me what stands out is ‘improving social protective factors such as resiliency and ability to cope with peer pressure.’” Another participant discussed how sport can be an effective teaching tool, stating “sport is a good tool for learning if you use it for demonstration of activities...What stands out is educating young people on matters that affect them using the power of soccer…Young people find it fun, exciting, and interactive.” Lastly, one Grassroot Soccer staff member highlighted the impact of sport-based interventions with regards to HIV and AIDS Table 3. Risk of bias Article ROB1 ROB2 ROB3 ROB4 ROB5 ROB6 ROB7 ROBoverall Awotidebe et al. (2014) Serious Mod Mod Serious Mod Mod Serious Serious Bloemhoff (2006) Serious Mod Mod NI Mod Serious Mod Serious Bloemhoff (2012) Mod Mod Mod NI Serious Serious Mod Serious Chetty & Edwards (2007) Mod Mod Mod NI Mod Mod Mod Mod Clark et al. (2006) Serious Mod Mod NI Mod Serious Mod Serious Ferguson et al. (2015) Mod Mod Mod NI Serious Mod Mod Serious Fuller et al. (2010) Serious Serious Mod NI Critical Mod NI Critical Fuller et al. (2011) Serious Serious Mod Mod Serious Mod Mod Serious Fuller et al. (2015) Serious Serious Mod Mod Serious Mod Mod Serious Hershow et al. (2015) Serious Serious Serious Mod NI Serious Mod Serious Kaufman et al. (2016) Mod Mod Mod NI Mod Mod Mod Mod Kemp & Pienaar (2009) Mod Mod Serious NI Low Serious Mod Serious Lennox & Pienaar (2013) Serious Mod Serious Critical Serious Serious Mod Critical Ley et al. (2014) Serious Mod Serious NI Mod Mod Serious Serious Maro et al. (2009) Low Mod Mod NI Critical Mod Serious Critical Maro & Roberts (2012) Low Mod Mod NI Critical Mod Critical Critical Monyeki et al. (2012) Serious Mod Mod NI NI Serious Mod Serious Naidoo & Coopoo (2012) Serious Mod Mod Serious Critical Serious Mod Critical Naidoo et al. (2009) Serious Mod Mod NI Critical Serious Mod Critical Owoeye et al. (2014) Mod Mod Mod NI Low Serious Mod Serious Parker et al. (2016) Low Low Low NI Low Mod Mod Mod Peacock-Villada et al. (2007) NI NI NI NI NI NI NI NI Richards et al. (2014) Low Low Mod NI Mod Mod Mod Mod Sorensen et al. (2016) Low Mod Mod NI Critical Mod Critical Critical Starzak et al. (2016) Serious Mod Critical NI Critical Serious Mod Critical Tian et al. (2017) Serious Mod Mod NI Low Critical Mod Critical Uys et al. (2016) Mod Serious Mod NI Mod Serious Mod Serious Walter (2014) Serious Mod Serious NI Critical Serious Mod Critical Note: ROB1) Bias due to confounding; ROB2) Bias in selection of participants; ROB3) Bias in classification of interventions; ROB4) Bias due to deviations from intended interventions; ROB5) Bias due to missing data; ROB6) Bias in measurement of outcomes; ROB7) Bias in selection of reported result SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 23 prevention with youth, stating “HIV-related outcomes…stand out because sport is playing a huge role in reducing new HIV infections and also changing attitudes and knowledge of beneficiaries. This [suggests] that sport-based education involves everyone even in the hard to reach areas.” When asked what steps could be taken to help sport-based health promotion, one participant reported: “increase its buy-in in all societies by engaging all communities. Engage key stakeholders and ministries. Make sport education an ongoing process not a once off event in societies.” A second participant discussed the potential role that sport can have in strengthening communities: “Support the role of sports in strengthening communities where young people come from—use sport as a vehicle to communicate about priority health matters.” Additionally, a participant stated that they wanted to “advocate for health services through sport-based health activities.” Lastly, participants provided the following responses when asked what they would like to see in future sport-based health promotion initiatives: “A more inclusive way of addressing harmful gender norms that have a large effect on the development of young aspiring female sports players and females in general.” Other participants stated that they would like to see “more stakeholders to come on board and support sport-based health” and “more free health services with sport-based health.” Lastly, one participant shared that they would like to see “increased participation in sport especially for females—increased social connections— increased healthy eating habits—reduce smoking and alcohol intake in young people.” Discussion The results of the present study suggest that sport can be an effective platform for health promotion with children and youth in Africa pending improvements in the methodology of future studies. Statistically significant improvements in health-related outcomes were observed in 23 of the 28 articles that met our study’s inclusion criteria. Targeted health outcomes included HIV SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 24 related knowledge and behaviors, essential health practices, physical activity, physical and mental health outcomes, and overall fitness levels. Considering the broad range of health outcomes in interventions included in this review, our results suggest that sport-based interventions may improve multiple physical and mental health outcomes with youth in Africa. We conducted risk of bias assessments for the included articles to enhance the quality of our review. The results of our risk of bias ratings for the 28 studies included in our review report that ten articles were deemed to be at critical risk of bias, 13 were at serious risk of bias, four were at moderate risk of bias, none of the articles were rated as low risk of bias, and one article was coded as no information. These findings are similar to those of a meta-analysis of sport based HIV prevention interventions, which found that only two of the 21 studies included in their analyses could be considered “good quality” (Kaufman et al., 2013). However, it is important to note that the ROBINS-I tool rating protocol involves comparing each intervention to a hypothetical randomized control trial (Sterne et al., 2016). Considering that many of these interventions were conducted with at-risk youth in low socio-economic communities, strictly adhering to a randomized control trial procedure would have been difficult. Furthermore, it could be argued that using a true control group in health promotion interventions with at-risk children is not ethical, as it requires researchers to not administer a potentially life-saving program to a group of youths. Ethical issues notwithstanding, future researchers should target conducting more scientifically rigorous studies to gain a more comprehensive understanding of how, why, and under what circumstances sport-based health promotion interventions are successful to maximize and sustain impact with limited resources. Bearing in mind the above methodological considerations in the reviewed studies, participants in this review demonstrated statistically significant improvements in HIV-related SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 25 outcomes (Awotidebe et al., 2014; Clark et al., 2006; Hershow et al., 2015; Kaufman et al., 2016; Maro & Roberts, 2012; Maro et al., 2009; Peacock-Villada et al., 2007; Sørensen et al., 2016). Specific HIV-related outcomes included knowledge and attitudes (Awotidebe et al., 2014; Clark et al., 2006; Hershow et al., 2015; Maro & Roberts, 2012; Maro et al., 2009; Sørensen et al., 2016), communication skills (Awotidebe et al., 2014; Hershow et al., 2015; Peacock-Villada et al., 2007), awareness of local preventative resources and treatment facilities (Clark et al., 2006; Hershow et al., 2015; Kaufman et al., 2016), and uptake of preventative treatments (Hershow et al., 2015; Kaufman et al., 2016). Therefore, our results support the findings of a recent meta analysis of 21 sport-based HIV-prevention initiatives that found strong evidence of positive effects with regards to HIV-related knowledge, stigma, self-efficacy, communication, and recent condom use (Kaufman et al., 2013). To our knowledge, our review is the first to suggest that sport-based health promotion interventions can significantly improve the uptake of HIV prevention and treatment procedures. Participants in two interventions included in our review demonstrated statistically significant improvements in the uptake of HIV-related services. Specifically, one soccer-based intervention led to a significant increase in HIV counseling and testing (HCT) services among adolescent girls in South Africa (Hershow et al., 2015). Another soccer-based intervention led to a statistically significant increase in voluntary medical male circumcision (VMMC) uptake among a group of adolescent males in Zimbabwe (Kaufman et al., 2016). Taken together, the results of these studies suggest that sport-based health promotion initiatives can be effective in promoting the uptake of HIV-related prevention services among children and youth in Africa. However, additional research is warranted to provide further evidence of this relationship. SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 26 One common theme among the sport-based interventions included in our review that targeted HIV-related outcomes and essential health knowledge is that they were conducted in collaboration with existing non-profit organizations (Awotidebe et al., 2014; Clark et al., 2006; Delva & Temmerman, 2006; Fuller et al., 2010; 2011; 2015; Hershow et al., 2015; Kaufman et al., 2016; Maro et al., 2009; Peacock-Villada et al., 2007). Specifically, eight studies included in our review were administered in collaboration with Grassroot Soccer, which uses a sport-based teaching model to build resilience in children and youth to help protect themselves against HIV (Peacock-Villada et al., 2007). Based on the promising results of each intervention, partnering with existing non-profit organizations is a promising avenue for future researchers, as the organizations’ knowledge and experience can enhance the development and implementation of effective sport-based health promotion interventions targeting children and youth in Africa. Furthermore, collaborating non-profit organizations can have experienced staff members conduct the intervention or provide comprehensive training sessions for the individuals who will administer the interventions to participants (Fuller et al., 2010; 2011; 2015). As part of these partnerships, Grassroot Soccer and other non-governmental organizations have increasingly utilized peer-led interventions with HIV-prevention initiatives in Africa, and the results have been promising (Maticka-Tyndale & Barnett, 2010). This approach is based on the assumption that adolescents rely on their peers to learn from and model their behavior after, and norms and behaviors are most likely to change when those of the group change (Campbell, 2004; Maticka-Tyndale & Barnett, 2010). In our review, trained peer-leaders or peer coaches were used to deliver a sport-based intervention in eleven of the articles. Participants in each study that utilized peer-coaches to deliver the intervention demonstrated statistically significant improvements in HIV-related outcomes (Awotidebe et al., 2014; Fuller et SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 27 al., 2010; 2011; 2015; Hershow et al., 2015; Kaufman et al., 2016; Maro & Roberts, 2012; Maro et al., 2009; Peacock-Villada et al., 2007; Sørensen et al., 2016), cardiovascular fitness outcomes (Richards et al., 2014), and reductions in pain (Parker et al., 2016). Therefore, our results support the use of trained peer coaches and peer leaders in sport-based interventions with children and youth. Our review also included three studies that used an 11-week soccer-based intervention to improve knowledge and awareness of essential health practices among children and youth from eight different African countries (Fuller et al., 2010; 2011; 2015). Participants in all eight countries demonstrated statistically significant improvements in health knowledge scores from baseline to post-intervention in outcomes related to physical activity, HIV prevention, malaria prevention, substance abuse, personal hygiene, clean water use, nutrition, vaccinations, and prescribed medication usage. These findings suggest that sport-based health promotion interventions that focus on a broad range of health behavior practices may be effective for children and youth in many different African countries. Although additional research is needed, these results speak to the potential generalizability and translational utility that sport-based interventions may have throughout Africa. One critique of previous sport-based health promotion interventions is that there has been an over-emphasis on HIV-related outcomes (Fuller et al., 2015). In our review, 39% of the included articles targeted HIV-related outcomes. Although HIV/AIDS is a public health epidemic, research suggests that rates of HIV/AIDS are much lower in children and adolescents in sub-Saharan Africa compared to adults (Delva & Temmerman, 2006). A recent systematic analysis suggested that HIV was responsible for approximately 8% of child deaths in sub Saharan Africa compared to 25% for neonatal disorders, 22% for malaria, 21% for pneumonia, SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 28 and 20% for diarrhea (Black et al., 2010). However, statistics relating to sub-Saharan Africa may be misleading, as health issues vary from country to country (Black et al., 2010). Therefore, one direction for future sport-based health promotion initiatives is to adapt program structures and protocols so they can address the specific needs of the countries and communities they are hoping to serve. Considering the significant amount of evidence supporting the use of sport based health promotion interventions targeting the prevention and treatment of HIV, additional research is warranted to understand the impact of sport-based health promotion interventions with other diseases and essential health behaviors as well. Sport- and physical activity-based interventions can be used to target other important health topics. For instance, it has been well documented that participation in physical activity and exercise is associated with improved fitness outcomes among youth (Armstrong, Tomkinson, & Ekelund, 2011). Our review included ten articles that investigated the impact of a sport- or physical-activity-based intervention on participants’ fitness levels. Specifically, seven studies resulted in statistically significant improvements, including improved muscular strength and endurance (Ferguson et al., 2015; Kemp & Pienaar, 2009; Ley et al., 2014; Naidoo & Coopoo, 2012; Naidoo et al., 2009), cardiovascular fitness (Ferguson et al., 2015; Kemp & Pienaar, 2009), anaerobic fitness (Ferguson et al., 2015), flexibility (Kemp & Pienaar, 2009; Naidoo & Coopoo, 2012), and lean body mass (Starzak et al., 2016). Two interventions resulted in statistically significant improvements in participants’ fitness levels in both the experimental and control conditions, but no statistically significant differences were found between the conditions at post-intervention (Richards et al., 2014; Uys et al., 2016). One study did not observe statistically significant improvements in participants’ fitness levels following a sport-based intervention, but the researchers hypothesized that this was due to low program compliance from SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 29 participants in their program (Lennox & Pienaar, 2013). Therefore, the results of our review suggest support for the notion that participation in sport and physical activity can enhance multiple fitness outcomes for youth. Additionally, participants in five studies demonstrated statistically significant improvements in physical activity levels (Lennox & Pienaar, 2013; Naidoo & Coopoo, 2012; Naidoo et al., 2009; Tian et al., 2017; Walter, 2014). Only one study found no significant improvements in participants’ physical activity levels, which the researchers hypothesized was due to the structure of the physical activity portion on their intervention (Uys et al., 2016). Physical activity is an inherent component of sport-based health promotion interventions, so it is not surprising that participants in these programs demonstrated higher levels of physical activity throughout the study. However, additional research is needed to determine whether participants’ increased levels of physical activity are sustained beyond the intervention. Aside from the physical benefits derived from physical activity, previous research also suggests that youth participation in sport and exercise may enhance mental health functioning (Kulig, 2003; Theokas et al., 2008). For example, it has been suggested that there is a strong positive relationship between physical activity and positive mental health outcomes with children and adolescents, including decreased symptoms of depression and anxiety and improved levels of self-esteem and cognitive functioning (Biddle & Asare, 2011). Our findings support the notion that sport- and physical activity-based interventions can improve mental health outcomes for children and youth in Africa. Six articles investigated the impact of sport- or physical-activity based interventions on mental health outcomes, and four studies resulted in statistically significant improvements in mental health outcomes among participants. Specifically, sport based interventions were found to be effective in reducing participants’ symptoms of depression SPORT FOR HEALTH PROMOTION WITH YOUTH IN AFRICA 30 and anxiety (Parker et al., 2016) and behavioral problems (Chetty & Edwards, 2007). Sport based interventions also resulted in higher levels of self-efficacy (Parker et al., 2016), self perception (Chetty & Edwards, 2007), and coping skills (Bloemhoff, 2006; 2012; Peacock Villada et al., 2007). Therefore, the results of our review suggest that physical activity and participation in sport can significantly improve several mental health outcomes with children and youth in Africa. In addition to the mental health benefits associated with physical activity, it has also been suggested that youth participation in sport promotes the development of important and adaptive life skills such as discipline, confidence to withstand peer pressure, goal-setting, and the ability to develop healthy coping strategies (Theokas et al., 2008). Engaging at-risk youth in sport can foster the development of essential life skills that may help them avoid risk-taking behaviors that can lead to lifelong consequences such as substance abuse, crime, and sexual activity (Kulig, 2003). Therefore, in addition to improving levels of health knowledge and awareness, there may b

Functional Movement Screen Composite Scores for CollegiateFunctional Movement Screen Composite Scores for Collegiate Field Club Sport Athletes at One University Daniel Camillone Follow this and additional works at: https://researchrepository.wvu.edu/etd Recommended Citation Camillone, Daniel, "Functional Movement Screen Composite Scores for Collegiate Field Club Sport Athletes at One University" (2018). Graduate Theses, Dissertations, and Problem Reports. 5304. https://researchrepository.wvu.edu/etd/5304 This Thesis is protected by copyright and/or related rights. It has been brought to you by the The Research Repository @ WVU with permission from the rights-holder(s). You are free to use this Thesis in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you must obtain permission from the rights-holder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/ or on the work itself. This Thesis has been accepted for inclusion in WVU Graduate Theses, Dissertations, and Problem Reports collection by an authorized administrator of The Research Repository @ WVU. For more information, please contact researchrepository@mail.wvu.edu. Functional Movement Screen Composite Scores For Collegiate Field Club Sport Athletes at One University Daniel Camillone, ATC, CSCS Thesis Submitted to the College of Physical Activity and Sport Sciences at West Virginia University in partial fulfillment of the requirements for the degree of Master of Science in Athletic Training Michelle A. Sandrey, PhD, ATC, Chair Jean L. McCrory, PhD Patricia Riley, MS, ATC, PES Department of Sport Sciences Morgantown, West Virginia 2018 Keywords: functional movement screen, composite score, club sports Copyright 2018 Daniel Camillone i ABSTRACT Functional Movement Screen Composite Scores For Collegiate Field Club Sport Athletes at One University Daniel Camillone, ATC, CSCS Context: Functional screening tools to detect musculoskeletal asymmetries and limitations present in functional movement patterns are available to use for the athletic population. Unfortunately, field club sport athletes do not have the opportunity to utilize functional screening tools. Further, normative data of Functional Movement Screen Composite Scores (FMS CS) has yet to be established in this population. Objective: The purpose of this study was to establish normative FMS CS among field club sport athletes, and determine if years of participation and current hours spent per week training have a significant effect on FMS CS. Foot type and orthotic use was also compared with FMS CS. Design: The study was a descriptive screening study. Setting: The assessments took place at a weight room and athletic training room at a DI Mid-Atlantic university. Patients and Other Participants: Thirty-one athletes (age 19.61±1.56 yrs, height 169.58±8.66 cm, weight 72.77±17.42 kg) participating in club soccer, rugby and lacrosse at a Division I Mid-Atlantic university during the 2017-2018 season volunteered for this study. Inclusion criteria for the study consisted of college students who are field club sport athletes between 18-23 years old who had not sustained an injury in the past twelve months that required removal from participation and training and completed the consent form. Exclusion criteria for the study consisted of an injury occurring in the past twelve months that required removal from participation and training and individuals not between the ages of 18-23 years old. Intervention: All participants completed the demographic questionnaire and seven movements of the FMS. A demographic questionnaire was completed to determine self-reported years of participation in the sport, number of hours spent training per week, foot type, and orthotic use. The participants were asked to complete the seven movements and three clearing tests of the FMS. Each participant completed three trials for each movement. Scores were calculated to determine FMS CS. Main Outcome Measures: The dependent variables were the Functional Movement Screen Composite Score and seven individual movement scores. Results: The mean FMS CS and standard deviation for all participants was 15.1±1.49. Women’s Lacrosse (n=4) had the highest average FMS CS (16.0±0.0). Participants with fewer years in sports (15.29±1.2 vs14.94±1.71) and hours of participation (15.17±1.63 vs 15±1.36) scored higher on the FMS CS. Those not wearing orthotics (n=28, 15.2±1.34) scored higher than those who do wear orthotics (n=3, 14.0±0.0). The one participant that reported a pes planus foot (15.0±0.0) scored higher than the seven participants with a pes cavus foot (14.7±1.98). Conclusions: Collegiate field club sport athletes score higher or comparable to varsity collegiate athletes on the FMS. More years of participation and hours per week were associated with decreased FMS. ACKNOWLEDGEMENTS I would like to first start by thanking my parents. Everything about me is the amazing joint effort of two wonderful, loving parents. Having you as parents will never be taken for granted. I love you both. Second, I want to thank my girlfriend Nicole. Our competitiveness has helped drive me to become a better person. Your love, along with an understanding of my pursuits, is something that I will always be thankful for. I love you hun. My classmate Brian Hanson must be thanked, for he was my only classmate to join me on this endeavor. Your work ethic encouraged me to hold a higher standard for myself. I know you will do great things my friend. My roommates DJ and Adam need to be thanked. They were a monumental part of my graduate experience. I know the three of us have created a friendship that will not fade with time. To my supervisor, Dr. Vincent Stilger, thank you for providing the opportunity over the last two years for me to develop as an instructor and clinician. I am beyond fortunate to have worked with you. Thank you to my committee members, Dr. Jean McCrory and Patti Riley. Your time and dedication are greatly appreciated. Lastly, this opportunity would not be possible without my committee chair and Graduate Athletic Training Program Director, Dr. Michelle Sandrey. Thank you creating the opportunities and experiences for my classmates and I, and the copious hours spent diligently reading my drafts. I am thankful for the level of excellence you pushed me to reach. iii iv TABLE OF CONTENTS ACKNOWLEDGEMENTS............................................................................................................iii LIST OF TABLES...........................................................................................................................v INTRODUCTION...........................................................................................................................1 METHODS......................................................................................................................................3 RESULTS......................................................................................................................................10 DISCUSSION................................................................................................................................11 CONCLUSION..............................................................................................................................18 REFERENCES..............................................................................................................................20 APPENDICIES..............................................................................................................................24 APPENDIX A: THE PROBLEM......................................................................................25 APPENDIX B: LITERATURE REVIEW.........................................................................33 APPENDIX C: ADDITIONAL METHODS.....................................................................54 APPENDIX D: ADDITIONAL RESULTS.......................................................................70 APPENDIX E: RECOMMENDATIONS FOR FUTURE RESEARCH..........................72 ADDITIONAL REFERNCES.......................................................................................................73 v LIST OF TABLES Table C1. Consent Information and HIPAA Form........................................................................41 Table C2. Subject Demographic Questionnaire.............................................................................45 Table C3. Verbal Instructions for the Functional Movement Screen............................................46 Table C4. Functional Movement Screen Score Procedures...........................................................50 Table C5. Functional Movement Screen Scoring Sheet................................................................54 Table D1. Most Frequent, Frequency, and Mean For FMS CS and Individual Movements.........70 Table D2. Descriptive Statistics and ANOVA for Year in Sport..................................................70 Table D3. Descriptive Statistics and ANOVA for Hours per Week..............................................70 Table D4. Individual FMS Scores Related To Orthotics and Foot Type......................................71 INTRODUCTION The obesity epidemic has created awareness for the importance of an active lifestyle. Thus, athletic participation has been increasing at all competition levels. One place where this has become apparent is at the university setting. Universities and colleges offer numerous types of physical activity. College students, in general, have the opportunity to participate in recreational sports or club sports. An increase in participation at this level has unfortunately resulted in a rise of injury rates across club sports. Eight and eight tenths million recreation related injuries were reported between 2011-2014 in the United States.1 There were 1.4 million emergency department (ED) visits caused by recreational activity from 2000-2001.2 There are approximately 11,000 ED visits each day in the U.S. related to recreational injury.2 Field club sports offered at colleges and universities include soccer, rugby, and lacrosse. Compared to varsity collegiate sports, field club sport athletes lack similar levels of commitment and access to sports medicine and strength and conditioning professionals. Six and three tenths injuries occurred per 1,000 athlete exposures among youth lacrosse players.3 Six hundred fifty nine injuries were experienced among 369 intercollegiate rugby players during a five year span.4 There were 12,974 injuries to collegiate male soccer players between 1988-2003.5 Despite decreased commitment and availability of resources, field club sport athletes are persistently seeking methods to improve performance and reduce risk of injury. Increasing speed, power, and strength are given priority over recovery and injury prevention measures.6 Increased training demands reinforce existing musculoskeletal asymmetries and limitation that lead to poor functional movement patterns.7-11 These compensation patterns build fitness upon dysfunction.7 11 Deficient movement patterns can lead to injury overtime. Clinicians rehabilitating injuries cannot disregard functional movement patterns to prepare an athlete for return to play. One such 1 screening tool that can be used is the Functional Movement Screen (FMS). The FMS was originally developed to serve as an inexpensive, simple screening tool for functional movement quality.12 The seven movements were selected to recreate the demands of athletic performance and activities of daily living.12 Screening tools, like the FMS, are designed to assess musculoskeletal asymmetries and limitations displayed during functional movement patterns.7-11, 13, 14 High injury rates and deficient movement patterns have encouraged athletic trainers and strength and conditioning coaches to implement movement screenings. High school athletes, varsity collegiate athletes and professional athletes participating in the field sports of rugby and soccer have received significant attention for musculoskeletal assessments using FMS composite scores (CS). 15-20 Twenty-two male recreational team sport athletes participating in soccer, basketball, rugby league, rugby union, Australian football, or touch football were assessed.15, 16 The mean FMS CS equated to 15.09+2.18.15, 16 In contrast, 62 South African professional rugby union players completed the FMS to compare CS between injured and non-injured athletes. 17 The FMS CS was 13.2+1.7 vs. 14.5+1.5, which is lower than in the Lockie15, 16 study. Seventy six male union rugby players completed the FMS at the beginning of each half of a season. An insignificant difference in FMS CS was noted between the first and second half of the season, 15.2+1.94 vs. 15.4+2.05.18 Twenty-three U16 and twenty-five U19 youth elite soccer players completed the FMS.21 Functional movement scores were 13.87+2.93 vs. 14.96+2.07.21 Negligible differences were noted within individual FMS movements between the two age groups.21 A comparison between NCAA Division II men’s and women’s soccer players was conducted to assess differences in FMS CS.19 Men’s soccer scored slightly higher than women’s soccer, 16.16+1.54 vs. 15.78+1.85.19 Forty-seven Division II men’s and women’s soccer players 2 averaged a 15.84+1.73 FMS CS.20 Sixty-two Division I women’s soccer players had an average FMS CS of 14.22 The collegiate field club sport athlete population has not been thoroughly examined throughout the literature. There is no specific screening tool for the club sport athlete, but the FMS could serve the needs of this population. The FMS is a simple, quick movement screening tool to develop an individualized functional movement profile. There is little evidence of screening tools that have examined field club sport athletes in the literature. Application of the FMS and its utility with this population needs further investigation. There are a lack of normative data examining how collegiate field club sports score on the FMS. The rise of athletic participation and subsequent injuries must be matched with injury prevention programs. The movement deficiencies discovered during the FMS can be used to develop an individualized intervention to correct musculoskeletal asymmetries and limitations. As the number of field club sport athletes grows, the need to detect movement deficiencies increases. Implementation of a functional movement screening tool is required to detect these deficiencies. Therefore, the purpose of this study is to establish normative FMS CS among field club sport athletes, and determine if years of participation and current hours spent per week training have a significant effect on FMS CS. METHODS This study was descriptive screening study to determine Functional Movement Screen Composite Scores (FMS CS) across field club sport athletes at a Mid-Atlantic university. Participants were tested during one session. The participants were in-season and out of season. The FMS was used to detect compensation patterns and movement deficits in field club sport athletes. The dependent variable was the FMS CS of each sport (Lacrosse, Soccer, Rugby). 3 Independent variables were the self-reported number of years playing (>10, <10) and self reported number of training hours per week (>12, <12). Participants A total of 31 student-athletes participating in field club sports at a Mid-Atlantic university were recruited during the 2018 club sport season or off season. A demographic questionnaire was provided to each participant. This included demographic information, training hours per week, years of participation, and injury history to determine eligibility for the study. A club sport athlete was defined as an individual who voluntarily participates in sports without the benefit of a scholarship or other benefits provided to a varsity sport athlete. Inclusion criteria for the study included college students 18-23 years old who had not sustained an injury in the past twelve months that required removal from participation and training and completed the consent form. Exclusion criteria included an injury in the past twelve months that required removal from participation and training and will be not between the ages of 18-23 years old. Participants completed all seven movements of the FMS in order for the results to be used in this study. The Office of Research Compliance at the institution approved the study. Procedures Athletes who were currently participating in field club sports (Lacrosse, Rugby and Soccer) were approached by the primary researcher to become participants in the study. The potential participants were explained the purpose of the study. An informed consent (Table C1) was provided to each consenting participant before the start of the study. A demographic questionnaire (Table C2) was provided to each participant. Those participants who met the inclusion criteria were invited to participate in this study. Times were scheduled for the participants to meet with the primary researcher to complete the FMS. Attendance at one 20 4 minute screening was required for each participant. Participants were permitted to engage in normal practices, competitions, and training sessions. Clothes, socks, and shoes were selected by the participants. The FMS was performed in the athletic training room and research laboratory at a Mid-Atlantic university to control for external factors. Administration and supervision of all screenings was conducted by the primary researcher. Verbal Instructions for the FMS (Table C3) were administered as the participants performed the seven functional movements and three clearing tests. Standard FMS Scoring Procedures (Table C4) were used. Movements scores were scored from zero to three. Clearing tests were completed prior to three movements: shoulder mobility, trunk stability push-up, and rotary stability. If pain was elicited, a score of zero is given. If there was an absence of pain, the participant was permitted to perform the movement. A score of three represented completion of the movement without compensation, two demonstrated completion of the movement with compensation, and one identified movements that were not completed. The raw score was used to identify right and left side scoring. The final movement score demonstrated an overall score. The sum of all seven movements determined the FMS CS. Previously described testing procedures were developed by Cook.7-11 Each movement was limited to three trials. A warm-up protocol was not included. A script was read (Table C3) to ensure consistency and clarity of instructions for each movement. No cueing was provided during the movements. The raw score was used to differentiate between right and left side scoring. The final score was used to display the overall score of the test. The lowest score for the raw score on each side was carried over to give a final score for the test. Reliability of the FMS has been found to be as high as .98.7-11 Other studies have discovered the reliability of the FMS to range from moderately high to high (r= 0.87-0.89, 0.971, 5 0.92-0.98).7-11 Level of experience with the FMS has a direct relationship to reliability.12 Recent research has focused on assessing the validity of the FMS on the screening tool’s ability to assess injury risk and athletic performance. Numerous studies13, 17 compare mean FMS CS between injured versus non-injured groups. These studies collectively agree that the differences in FMS CS are insignificant. In the current literature, higher FMS CS do not mean greater athletic performance measures such as multidirectional speed, jumping, Y balance test, 1RM squat, ten and twenty meter sprints, and T -test times.15, 16 Most validity studies on the FMS do not focus on the ability to assess musculoskeletal asymmetries and limitations. The FMS (Tables C3-5) was designed to assess fundamental movements of an individual.7-11 The goal was to identify musculoskeletal asymmetries and limitations. These findings determined the design of an individualized intervention. The seven movements of the FMS include the: deep squat, hurdle step, in-line lunge, shoulder mobility, active straight leg raise, trunk stability push-up, and rotary stability. The deep squat (Table C3) was used to assess bilateral, symmetrical, functional mobility of the hips, knees and ankle.7-11 A dowel was grasped and placed horizontally overhead so the shoulders and elbows are at ninety degrees. The dowel was extended overhead to assess thoracic and shoulder mobility. An upright torso and heel contact was maintained as the participant descends as deep as possible.7-11The participant held the descend position for a count of one, and then returned to the starting position.7-11 The participant had a maximum of three trials to complete the movement to the best of their ability. The hurdle step (Table C) emphasizes proper stride mechanics. The hurdle height was equivalent to the participant’s tibial tuberosity.7-11The participant placed toes on the test and placed the dowel across the back of the shoulders. At this point, the participant raised one leg to 6 step over the hurdle to contact the heel with the ground.7-11This movement was assessed bilaterally. The participant had a maximum of three trials to complete the movement to the best of their ability. The inline lunge (Table C3) imposed a narrow base of support to challenge the stability of the trunk and extremities.7-11The participant grasped a dowel behind the back before stepping onto the 2 x 6 board. Tibial tuberosity height was measured to determine the distance between the feet.7-11The left leg stepped forward as the right hand grasped the dowel behind the neck. The participant descended until the right knee touched the 2 x 6 board and returned to the starting position.7-11The movement was assessed bilaterally. The participant had a maximum of three trials to complete the movement to the best of their ability. The shoulder mobility (Table C) movement assessed bilateral mobility of the shoulder, scapula, and thoracic spine.7-11The participant made fists with the thumb inside. The right fist reached overhead and down the spine. The left fist went behind and up the spine as far as possible. Creeping, or connecting movements, of the fists was prohibited.7-11The distance between the two fists was measured in inches. This score was assigned to the flexed shoulder. The movement was assessed bilaterally. The participant had a maximum of three trials to complete the movement to the best of their ability. The shoulder clearing test (Table C) was performed after the shoulder mobility movement. No score was assigned to this movement. The purpose of this test was to assess for pain. The right palm was placed on top of the left shoulder. While maintaining contact, the right elbow was raised as high as possible to determine if shoulder impingement is present.7-11If pain was present, a score of zero was given.7-11 The clearing test was performed bilaterally. 7 The active straight leg raise (Table C) assessed the flexibility of the hamstrings and gastroc-soleus complex as the pelvic and core maintained stability.7-11The participant remained flat with the back of the knees against the 2 x 6 with the toes pointed upward. The stationary left leg maintained contact with the floor and a dorsiflexed ankle.7-11 A midpoint was identified between the anterior superior iliac spine and middle of the patella. A dowel was placed perpendicular to the floor at the midpoint. The right foot was kept straight and raised as high as possible with the head and lower back in contact with the floor. If the malleolus did not pass the dowel, the dowel was moved in line with the malleolus of the test leg and scored per the criteria.7-11The movement was assessed bilaterally. The participant had a maximum of three trials to complete the movement to the best of their ability. The trunk stability push-up (Table C) assessed stabilization of the core and spine through a closed-chain upper body movement. The participant laid face down with the feet together, and the hands spaced shoulder-width apart.7-11The thumbs were placed in line with the chin. The participant raised the body as a unit with knees extended and ankles dorsiflexed to complete one push-up. If one push-up was performed, the hands were lowered to shoulder level.7-11The participant had a maximum of three trials to complete the movement to the best of their ability. The spinal extension clearing test (Table C) was performed after the trunk stability push up. No score was assigned to this movement. The purpose of this test was to assess for pain. The participant was prone with the palms under the shoulders. With no movement from the lower body, the participant pressed up. If pain was present, a score of zero was given.7-11 The rotary stability movement (Table C) required proper neuromuscular coordination and energy transfer from one segment of the body to another through the torso.7-11The participant was placed in a quadruped position with the hips and shoulders at 90 degrees relative to the 8 torso.7-11The 2 x 6 board was placed between and made contact with the hands and knees.7-11 The arm and leg on the same side were lifted to attempt to touch the knee and elbow.7-11If this movement was performed, the participant was instructed to perform a diagonal pattern. The movement was assessed bilaterally. The participant had a maximum of three trials to complete the movement to the best of their ability. The spinal flexion clearing exam (Table C) was performed after the rotary stability movement. No score was assigned to this movement. The purpose of this test was to assess for pain. The participant started in a quadruped position and rocked backwards to touch the buttocks to the heels and chest to the thighs.7-11The shoulders remained flexed with the hands reaching as far as possible.7-11 A score of 0 was given if pain was noted. Data Analysis The FMS scores were recorded (Table C5). The final score included the lowest score of the movement with right and left values. The highest possible FMS CS was 21. The values gathered were assessed within each sport and across normative values of other sports. Statistical Analyses Descriptive analyses included means and standard deviations for all participants with the FMS, including FMS CS across sports. The overall mean FMS CS for lacrosse, soccer, and rugby will be compared to hours spent training per week, number of years participating in the sport, foot type, and orthotic use. Four separate one-way ANOVA’s were calculated to compare mean FMS CS with 1) hours spent training, competing, practicing and training per week(≥12 hours and <12 hours); 2) the number of years participating in the sport (≥10 and <10 years); 3) foot type (pes planus and pes cavus); and 4) orthotic use ( yes and no). ANOVA’s will be calculated with 95% Confidence Intervals. The P value will be set to P=0.05 for all analyses. 9 IBM/SPSS software (IBM/SPSS, Inc., Chicago, IL) version 24.0 was used for all analyses. It is beneficial to understand how club field sport athletes scores compared to other athletic populations. RESULTS Demographic Data Thirty-one athletes (age 19.61±1.56 yrs, height 169.58±8.66 cm, weight 72.77±17.42 kg) participating in club soccer, rugby and lacrosse at a Division I Mid-Atlantic university during the 2017-2018 season volunteered for this study. Beyond the 31 participants, one athlete was excluded due to a recent injury. Fourteen (45.2%) of the participants were from women’s soccer, 1 (3.2%) from men’s soccer, 4 (12.9%) from women’s rugby, 8 (25.8%) from men’s rugby, and 4 (12.9%) from women’s lacrosse. Thirteen (41.9%) participants were freshman, 9 (29.0%) were sophomores, 4 (12.9%) were juniors, and 5 (16.1%) were seniors. All participants were free of injury for the past six months that prevented full participation in their sport. FMS Composite and Individual Scores for Years of Participation and Contact Hours Table D1 displays the overall FMS CS, FMS CS for individual sports, average for individual movement scores and individual movement scores for each sport. The mean FMS CS for all participants (n=31) in the study was 15.1±1.49 (minimum score of 11, maximum score of 18). Women’s Lacrosse had the highest average FMS CS (16.0±0.0, n=4). Average individual FMS scores were reported for DS (1.971±0.31), HS (2.091±0.40), IL (2.481±0.57), SM (1.91±0.83), ASLR (2.651±0.55), TSPU (2.031±0.66), and RS (2.0±0.0). For average individual movement scores, women’s and men’s soccer had the highest average individual movement score in the IL (2.57±0.51, 3.0±0.0). Women’s and men’s rugby, and women’s lacrosse scored best in the ASLR (3.0±0.0, 2.63±0.52, 3.0±0.0). 10 Table D2 compares years in sport with FMS CS and individual movement scores. There were no significant differences between FMS CS and years of participation in their sport (>10 years, <10 years) (F=0.402, P=0.531). Individually, years of participation was significant for TSPU (F=4.199, p=0.050). Table D3 presents descriptive statistics and results for contact hours. No significant differences were found between FMS CS and hours per week spent training, practicing, and competing (>12 hours, <12 hours) (F=0.104, P=0.104). Individual movement scores were not significant. The movement closest to significance when compared to hours per week was the DS (F=2.967, p=0.096). FMS Composite and Individual Scores in Relation to Foot Type and Orthotics The DS, HS, and IL were the only scores compared to foot type and orthotics. A pes cavus foot type scored higher on the DS (2.0±0.0), HS (2.29±0.49), and IL (2.292.0±0.76) compared to pes planus. The one participant with pes planus had a higher FMS CS (15.0±0.0) than the 7 participants with pes cavus (14.7±1.98). This same participant with pes planus did not wear orthotics. Participants that do not wear orthotics scored highest on the IL (2.54±0.51). Three participants wore orthotics, and averaged 2.0±0.0 for the DS, HS, and IL. Participants not wearing orthotics had a higher average FMS CS (15.2±1.34) than those who wear orthotics (14.0±0.0). DISCUSSION This study was conducted using field club sport athletes to establish normative FMS CS and determine the impact of years of participation and hours spent practicing, training, and competing. Foot structure and orthotic use was evaluated to determine the effect on FMS CS and individual movement scores. All participants averaged a 15±1.49 FMS CS, higher than the hypothesized 14. The hurdle step and rotary stability were expected to be the highest and lowest 11 individual movement scores. In this study, the ASLR was the highest (2.65±0.55) and SM was the lowest (1.91±0.83) individual movement scores. Unfortunately, 31 participants do not offer enough scores to establish normative values. Plus, the majority of participants were female and women’s soccer players. There was one men’s soccer, four women’s lacrosse, and zero men’s lacrosse players. This concept of establishing normative data must be continued for these sports to effectively correct movement deficiencies. The hypotheses that those who participated >10 years in sport (14.94±1.71) and >12 hours per week (15±1.36) would have an FMS CS score lower than those <10 years (15.29±1.2) and <12 hours (15.17±1.63) was exhibited in this study. Participants without orthotics (15.2±1.34) scored higher on the FMS CS than those who do wear orthotics (14.0±0.0). The participant with pes planus (15.0±0.0) scored higher than those with pes cavus (14.7±1.98). As this study is the first study to evaluate club sport field athletes with the FMS, it is difficult to draw direct conclusions with comparisons to other known studies in this area. However, comparisons can be made using the FMS literature in other sports and populations. FMS CS and Individual Scores Athletes are continuously training harder to perform better in their sport with the “more is better” mentality. Despite an athlete’s effort and discipline in their training regiment, movement insufficiencies may be present. The FMS is designed to assess musculoskeletal asymmetries and limitations. Based on the results, an individualized intervention is developed to correct movement deficiencies. With the information obtained from the FMS, an athlete’s inefficient movement patterns can be corrected prior to the start of a season or training cycle. In this study, all participants averaged a 15±1.49 on the FMS CS. Despite being a club sport athlete, the 12 participants in this study scored better or similarly to athletes participating in the same sport at different competition levels. U16 and U19 youth elite soccer players averaged 13.87±2.93 and 14.96±2.07.21 These younger athletes scored lower than female and male club soccer athletes (14.9±1.44, 15.0±0.0). Silva24 stated the difference between U16 and U19 FMS CS could be a result of the ability to control multi-planar trunk stability. The mature club sport athletes may have developed better multi-planar stability and strength, leading to higher FMS CS. Forty-seven NCAA Division II men’s and women’s soccer players between the ages of 17-22 scored significantly higher than the soccer players in this study (16.16+1.54, 15.78+1.85).20 Another study examining FMS CS on 47 Division II men’s and women’s soccer players found an average of 15.84+1.73.19 These findings suggest that soccer players at higher levels of competition score higher on the FMS CS. Although, differences in FMS CS could be consequence of when screenings are performed. Screening in this study was conducted in the off-season, and the previously mentioned studies were performed during the pre-season. Rugby and lacrosse players scored higher or comparable to the results from this study. Seventy-six male union rugby players scored comparable FMS CS (15.2±1.94) to those male and female club rugby players (15.3±2.05, 14.5±1.29).18 Only injury-free athletes were eligible to participate in these studies. Sixty-two non-injured South African professional rugby union players scored 14.5±1.5. Unlike soccer, competition level has is an insignificant effect on FMS CS. The women’s lacrosse athletes had the highest average FMS CS of 16.0±0.0. Lacrosse players may have improved coordination between the trunk with upper and lower extremities. Their sport demands wielding a lacrosse stick to throw, as soccer and rugby do not involve equipment that act as extensions of their extremity. 13 Twenty-two of 31 participants were females in this study. Females are generally more flexible than males. A study of 492 male and 118 female high school athletes were examined to determine sex differences in hamstring flexibility.24 Females displayed greater hamstring flexibility. 24 On the contrary, males reported hamstring flexibility to be more important for athletic performance and to their coaches.24 Both sexes reported similar stretching duration and repetitions.24 Despite a lack of perceived importance, female athletes displayed greater hamstring flexibility.24 Overall, it is difficult to discern if hours per week or sex differences are the cause in FMS CS and individual movement scores. In this study, when individual scores were evaluated, SM had the lowest average score when compared with hours per week. The TSPU and SM concentrate on the upper extremity. Female athletes have typically demonstrated decrease performance in upper extremity strength, endurance, and neuromuscular control.23 Another study compared 29 female and 31 male secondary school athletes and found females scored significantly lower on the TSPU (1.4±0.6 vs. 2.2±0.8). 23 Ninety-three percent of females and 65% of males required modification or were unable to complete the push-up with modification. An additional study 23 also found Division I females to score lower on the TSPU and RS when compared to males, but better on the SM. As previously discussed, females tend to have better flexibility, explaining why other studies display improved performance on SM. Poor performance on the TSPU may also be related core strength and stabilization. FMS CS and Individual Scores and Years of Participation and Contact Hours Participants with <10 years in sport (n=14) and <12 hours per week (n=17) scored higher. The highest individual movement score was the ASLR. Participants with <10 years in sport (n=14) and <12 hours per week (n=17) scored higher. Studies related to FMS CS to years 14 participating in sport are scarce in the literature. However, a study by Bardenett25 found high school athletes with more years of experience to score lower on the FMS (13.11±1.69 vs 13.00±2.32). The largest difference in individual movement scores was with the SM (2.67±0.55 vs 2.23±0.84).25 The study concluded that lower scores were attributed to previous injury history and increased exposure time in high level varsity athletics.25 Another study found 60% of junior Australian Football players to score lower than older, professional American Football players and collegiate athletes.26 Despite conflicting evidence, this study found athletes with more years of participation in their sport had decreased FMS CS and individual movement scores. In this study, the TSPU displayed the lowest individual mean score when compared with years in sport. Aging may also be a consideration as older individuals are usually playing for a longer period of time. The effects of aging negatively impact performance on the FMS.27, 28 A study of 395 men and 227 women were screened and divided into six different age groups.27 Males and females between 20-29 years of age had higher FMS CS than the 65+ years group (14.79±2.76, 15.43±2.44 vs. 12.56±3.27, 13.17±3.01). 27 Another study found men and women 65+ years to score lower on the FMS (12.6±3.3, 13.2±3.0).28 The amount of time spent per week training, practicing, and competing is thought to negatively affect FMS CS. A study of 84 collegiate middle and long distance runners compared FMS CS, injury, and weekly mileage.29 Injury-free runners ran fewer miles (80.9±53.8 vs 98.4±57.3), but scored higher than the injured runners (14.4±2.2 vs 13.3±2.7).29 Another study classified runners as functional (≥14 FMS CS) or dysfunctional (<14 FMS CS).30 Similar to the study by Hotta,29 dysfunctional runners displayed an increase in training sessions per week and injury prevalence in the past 12 months. 30 Increases in mileage provide more opportunity to develop movement deficiencies and musculoskeletal asymmetries and limitations, leading to 15 lower FMS CS. One study reported 13.8 injuries occur per 1,000 athlete exposures among collegiate athletes.31 More deficiencies may present among injured athletes. 31 The FMS could be compared with athlete-exposures to determine if contact-hours affect FMS CS. Foot Type and Orthotics As foot type and orthotics have an influence on movement patterns, it was hypothesized that similar differences would be apparent in this study. Differences were noted in this study between participants with a pes planus or pes cavus foot type. The one participant with pes planus scored higher than the 7 participants with pes cavus (15.0±0.0 vs. 14.7±1.98). The comparison is intriguing but a lack of participants does not make the finding significant. With only one participant having a pes planus foot, that difference was not as apparent. Participants not wearing orthotics scored higher than those wearing orthotics (15.2±1.34 vs. 14.0±0.0). Those without orthotics scored highest in the IL (2.54±0.51). It could be thought that these individuals have stronger intrinsic foot musculature that prevent pronation distortion syndrome of the lower extremity.29 Since foot type and orthotic use was evaluated in this study, there may be concern that the FMS instructions do not provide guidelines on whether participants should wear shoes or be barefoot during screening. The argument for FMS when barefoot is to improve stability through increased sensory input through the feet. Plus, barefoot screening will also be a more accurate representation on how foot type can impact FMS CS and individual movement scores. 32 On the contrary, a lack of support to screen participants with shoes also lessens the importance to screen those wearing orthotics. 32 Participants were divided into shoe and barefoot groups in the Crosby study32 to compare the DS, HS, IL, and FMS CS. There were no significant differences and it was inferred that footwear does not provide supplementary stability.32 Despite the increased 16 sensory input of barefoot screening, athletes and all other participants wear shoes during almost every moment of the day.32 Thus, barefoot screening does not accurately recreate functional movement patterns as they are performed in the real world. It is also important to note that the DS is intended to be a measure of mobility, not stability. Clinical Implications The results from this study provided introductory descriptive data of FMS CS and individual movement scores for collegiate club sport athletes. As this population is underrepresented in the literature, more information is needed to determine where deficiencies are most likely to exist so interventions can be initiated earlier. Despite lacking the benefits afforded to varsity collegiate athletes such as the same time commitments, resources, coaching and tools to improve functional movement, club sport athletes scored similarly or better. The mean FMS CS for all participants in the study was 15.1±1.49. This is very comparable to the eighty-four Division II rowers, volleyball, and soccer players that averaged an FMS CS of 15.84±1.73, 20 as well as 108 Division I collegiate athletes with a FMS CS of 15.546. However, a lower mean FMS CS of 14.3±2.2 was found after examining 59 Division I freshman football players. With similar or better results for FMS CS in comparison to collegiate athletes at different competition levels, the availability of resources and coaching do not appear to have a significant effect on FMS CS. On average, the DS and SM were the lowest scored movements. Both movements emphasize mobility, indicating field club sport athletes are deficient in ankle, hip, spine, and shoulder mobility. Most athletes do not emphasize stretching and mobility in the training regiments. Interventions techniques including static stretching, self-myofascial release, foam rolling, instrument-assisted soft tissue mobilization, joint mobilizations and dynamic stretching 17 can be incorporated to improve individual deficiencies. The negative effects of increased years of participations and hours per week can be counteracted by an individualized intervention developed on FMS scores. Years of participation and hours per week did not significantly affect FMS CS. Clinicians can use this information to develop more effective interventions. This should raise awareness that more research is needed to determine other factors that impact FMS CS. At this time, clinicians should not be concerned about the impact of years of participation and hours spent per week have on functional movement patterns. Although information from this study pertaining to orthotics and foot type in limited, no orthotics and pes cavus may require a more detailed biomechanical analysis of the lower extremity. These groups scored lower in FMS CS, DS, IL, and HS, suggesting abnormalities in the foot are causing stability or mobility deficiencies in proximal joints. Overall, the emphasis is to reestablish functional movement patterns and educate athletes to train smarter, striving to increase the number of years of participation. Limitations of the Study The data from this study are preliminary and further investigation is necessary to establish normative data for this population. Thirty-one participants do not offer enough data since it is estimated that there are approximately 700 athletes at this Division I Mid-Atlantic university. A lack of participants makes it difficult for this data to be generalizable to all field club sport athletes. The study also had a greater representation of female field club sport athletes, decreasing its generalizability to male athletes. Also, the participant’s foot type and orthotic use was determined through self-report on a questionnaire, rather than implementing an objective measurement. This study displayed that most participants do not know their foot type, limiting the amount of data collected. Future studies should include specific measurements of foot type. 18 CONCLUSION Functional Movement Screen studies using field club sport athletes should be conducted. Results from this study indicateD that the FMS CS was higher or comparable to other varsity collegiate athletes. In addition, women’s lacrosse players had the highest mean FMS CS. Participants who reported greater years of participation and hours spent per week had a negative association with FMS CS. Not wearing orthotics and pes planus displayed higher FMS CS. The information gained from this and future studies using field club sports athletes will help in the understanding of movement deficiencies and musculoskeletal asymmetries and limitations specifically present in this population. 19 REFERENCES 1. Sheu Y, Chen L, Hedegaard H. Sport and recreation related injury episodes in the u.s. population: 2011-2014. Med Sci Sport Exerc. 2016;48:868. 2. National Center for Injury Prevention and Control (U.S.). CDC injury research agenda, 2009 2018. Atlanta, GA: US Department of Health and Human Services, Centers for Disease Control and Prevention; 2009. Available at: http://www.cdc.gov/ncipc\ 3. Lincoln AE, Yeger-McKeever M, Romani W et al. Rate of injury among youth lacrosse players. Clin J Sport Med. 2014;24(4):355-357. 4. Peck KY, Johnston DA, Owens BD et al. The incidence of injury among male and female intercollegiate rugby players. Sports Health. 2013;5(4):327-333. 5. Agel J, Evan TA, Dick R, Putukian M, Marshall SW. 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Bardenett SM, Miccaa JJ, DeNoyelles JT, Miller SD, Jenk DT, Brooks GS, Functional movement screen normative values and validity in high school athletes: can the fms be used as a predictor of injury? Int J Sports Phys Ther. 2015;10(3):303-308. 21 26. Fuller JT, Chalmers S, Debenedictis TA et al. High prevalence of dysfunctional, asymmetrical, and painful movement in lit junior Australian football players assessed using the functional movement screen. J Sci Med Sport. 2017;20(2):134-138. 27. Perry FT, Koehle MS. Normative data for the functional movement screen in middle-aged adults. J Strength Cond Res. 2013;27(2):458-462. 28. Fawcett, MA. Reliability of the functional movement screen score for older adults. Bowling Green State University. ProQuest Theses and Dissertations. 2014. 29. Hotta T, Nishiguchi S, Fukutani N et al. Functional movement screen for predicting running injuries in 18- to 24-year-old competitive male runners. J Strength Cond Res. 2015;29(10):2808-2815. 30. de Oliveira RR, Chaves SF, Lima YL et al. There are no biomechanical differences between runners classified by the functional movement screen. Int J Sports Phys Ther. 2017;12(4):625-633. 31. Dorrell BS, Long T, Shaffer S et al. Evaluation of the functional movement screen as an injury prediction tool among active adult populations: a systematic review and meta-analysis. Sports Heath. 2015;7(6):532-537. 32. Crosby BR. Analysis of barefoot and preferred footwear in functional movement screen scores. Illinois State University. ProQuest Theses and Dissertations. 2016. 22 23 APPENDICIES APPENDIX A THE PROBLEM Research Question Athletic participation has been growing rapidly. There are several levels of competition in which athletes can participate. At colleges and universities, students have the opportunity to be a club sport athlete. A surge in club sport participation has lead to an increase in injuries. 43 Recreation related injuries were reported to be 8.8 million between 2011-2014 among the United States (U.S.) population.1 Exercising was the most frequently reported cause of injury. These injuries included 4.3 million strains and sprains, 2.1 million fractures, 2.0 million contusions, and 1.0 million open wounds.1 The Center for Disease Control (CDC) reported 1.4 million emergency department (ED) visits from 2000-2001 caused by recreational activity.2 Approximately 11,000 U.S. citizens visit an ED each day for recreation related injuries.2 Recreational cricket players averaged an injury incidence of 2.3 per 100,000 in New Zealand between 2000 to 2005.44 Sport club participation was the strongest predictor of injury for 5,889 hospitalized Finn’s, where 23.9% of injuries were knee or shin related.6 Twenty-seven percent of adults and 60% of children participate in community-based athletic activities across Australia.42 Despite the information provided on injury epidemiology across the collegiate club sport population, more research is needed. Athletes, especially club sport athletes, are continuously seeking methods to improve performance and reduce risk of injury.27, 38To do so, athletes will train to build strength and increase speed. Unfortunately, injury prevention and recovery techniques are frequently given less priority despite the ability to potentially prevent injury.6, 39 As a result, athletes can develop compensatory movement patterns in an attempt to meet the demands of higher performance. 24 Performing at higher levels adds fitness to dysfunction when executing inefficient movements.7 11 Over time, these deficiencies can lead to injury. Common injury prevention and recovery techniques include stretching, ice baths, foam rolling, therapeutic modalities, and rest.43 Unfortunately, these techniques do not identify musculoskeletal limitations. Thus, implementing functional movement screening can provide an assessment of a club sport athlete’s movement efficiency to help prevent injury.30 In order to assess and correct dysfunction, movement screens should be incorporated into pre-participation screening. Cook and colleagues7-11 developed the Functional Movement Screen (FMS) to bridge pre-participation screening and performance testing. This tool is designed to examine functional movement patterns. The FMS is used to develop individualized, functional interventions to establish a benchmark for functional movement improvement. It is important to understand that the FMS was designed with the goal of determining movement competency.7-11 Seven movements comprise the FMS: the deep squat, hurdle step, inline lunge, shoulder mobility, active straight leg raise, trunk stability push up, and rotary stability. 7-11 Each movement is scored from zero to three.7-11 Zero is assigned to a movement if the patient experiences pain.7-11 A score of three identifies an ideal movement pattern without deficiencies, limitations, or compensation patters. The total score of the seven movements is called a Composite Score (CS).7-11 The average FMS CS is 14.7-11 Fourteen also serves as the cutoff score. In other words, it is conceived that individuals who score <14 are at a greater risk of injury.7-11 The score from the initial screening serves as a baseline. The baseline dictates what program should be implemented to address weaknesses. Comparing the baseline to reassessments exhibits progress with movement competency and improved movement scores. Despite the original intent of the FMS screen to detect movement pattern deficiencies, 25 recent studies have begun to focus on injury risk and performance with collegiate athletes. Fifty nine 59 NCAA Division I American football players had FMS scores compared with knee strength, hip strength, and various hop performance tests.45 Correlation of the FMS with performance measures was not evident.45 The association between 37 Division I rowers’ FMS scores and injury occurrence was examined as poor.13 Low FMS Composite Scores (CS) were more likely to predict low back pain.13 An examination of 195 Division I student-athletes’ FMS CS were not significantly different between injured and non injured groups, 14.3+2.5 vs. 14.1+2.4.36 Overall, studies using the FMS with a collegiate population commonly assessed and correlated CS with performance measures or injury. After reviewing collegiate and high school FMS studies, studies examining different active populations are minimal.41-45 College students participating in club sports have not been examined with the FMS. Despite the higher level of competition in college athletics, numerous college students still participate in intense physical activity through club sports. 41-45 Copious hours are dedicated to training, practice, and competing. 41-45 As participation numbers rise, there is a need for tools to screen those at risk for injury. Unfortunately, club sport athletes do not receive the same level of care as varsity collegiate athletes. 41-45 These individuals still perform explosive maneuvers, feats of strength, and push through the pain of training and injury. 41-45 As the volume and history of participation increase, there is a greater likelihood for musculoskeletal asymmetries and limitations to develop. 41-45 Inefficient movement patterns during activity will cause asymmetries and limitations. Compared to varsity collegiate athletes, the remainder of the active college student population receives less attention to musculoskeletal assessments. There is a lack of studies supporting the need to examine the collegiate club sport student-athlete population. Most studies 26 using the FMS assess varsity collegiate athletes or tactical professionals to measure injury risk, performance, validity or reliability. Without proper neuromuscular control and functional movement patterns, the collegiate club sport student-athlete is at a greater risk of injury. Poor training techniques and compensatory movement patterns can lead to acute or chronic injuries. The FMS is needed to detect deficient movement patterns in the club sport setting, especially field club sport athletes. This is necessary to create an individualized intervention. Therefore, research is needed to support the implementation of the FMS among collegiate club sport student-athletes. Furthermore, there is little on field club sport athletes, let alone if years of experience and hours practicing affects FMS composite and individual scores. Overall, no screening tool exists to assess the quality of functional movement among collegiate club sport student-athletes. The physical demands of these individuals has not been thoroughly assessed in the literature. There is no information regarding the application of the FMS and its utility with this population. It is evident that athletic injuries can have long-lasting detriments to participation, and can be potentially be prevented with an intervention.7-11 In order to match the rise of collegiate club sport student-athletes and number of associated injuries, there must be an implementation of injury prevention programs. The FMS can serve as useful, efficient tool to assess the areas of musculoskeletal asymmetries and limitations that can cause an injury associated with physical activity.7-11 There is lack of information regarding collegiate club sport student-athletes and how they score on the FMS. Thus, collegiate club sport student athletes are expected to have a FMS CS of 14.7-11 Therefore, the following research questions were asked: Research Questions 1. What are the FMS CS’s among collegiate field club sport student-athletes? 27 2. What is the average FMS CS of collegiate field club sport student-athletes? 3. Do collegiate field club sport student-athletes score higher than the 14 point cutoff? 4. Which of the seven movements will collegiate field club sport student-athletes score lowest? 5. Which of the seven movements will collegiate field club sport student-athletes score highest? Experimental Hypotheses 1. The average FMS CS will be 14. 2. Individual movement scores will be highest in the hurdle step. 3. Individual movement scores will be lowest in the rotary stability. 4. Collegiate field club sport student-athletes with >10 years of participation in their sport will have a lower FMS CS in comparison to those with <10 years. 5. FMS CS will be lower in those who spend >12 hours per week spent practicing, training, and competing in comparison to those who spend <12 hours per week. Assumptions 1. All subjects will meet the inclusion criteria for the research study. 2. The FMS is a valid and reliable screening tool. 3. Documentation of FMS scores will be accurate. 4. Participants will complete each FMS movement to the best of their ability. Delimitations 1. Subject population is specific to only collegiate field club sport student-athletes. 2. This study is not generalized to other age groups than a population aged 18-23 and to one college campus. Operational Definitions 1. Collegiate Club Sport - a registered student organization formed by individuals with a common interest in a sport and/or recreational activity that exists to promote and meet regularly to pursue and develop interest within a defined scope.49 2. Collegiate Field Club Sport Student-Athlete - a full-time student committed to and currently 28 participating in a non-varsity sport that plays on a field at a Mid-Atlantic university, through the club sports program. 3. Functional Movement Screen (FMS) - A set of seven physical movements that assess mobility, strength, and coordination to determine an individual’s compensation patterns and/or deficiencies in movement patterns. The battery of movements illustrates an individual’s ability to progress to more difficult tasks.7-11 4. Functional Movement Screen Composite Score (FMS CS) - a subject’s total score of the seven movements performed in the FMS.7-11 5. 10 Years - number of years the athlete has been participating in their sport, beginning between the ages of 8-13, assuming that middle school students have the opportunity to participate.. 6. 12 Hours - an average of two hours per day spent practicing, training, or competing across six days in a week, with the seventh day as a rest day. Limitations 1. Non-certified FMS instructor. 2. Participants may not want to participate in data collection. 3. Threats to internal and external validity. 4. Participants may experience muscle soreness or fatigue at the time of screening from practices, competitions, and training. 5. The type and duration of activity will be dependent on the sport of the participant. Significance of Study The importance of living an active lifestyle has increased as obesity rates and other health complications rise. College students will participate in club sports to fulfill their need for exercise and continue the passion for that sport. As the number of active individuals rise, so will the number of musculoskeletal injuries. The importance of this research is to apply the FMS to a population that has not previously been examined: collegiate club sport student-athletes. Although the number of hours spent training for activity may be less than a varsity athlete, compensatory movement patterns 29 can negatively impact performance and ability to continue participation if injury occurs. The screening tool will be used to collect FMS CS’s, generalizing how this population scores and areas of deficiency. Number of years participating in the sport and hours of activity per week will also be accounted for. From the perspective as a practitioner, this will provide introductory data to establish

Competitive Aggressiveness, Anger, and the Experience of Provocation in Collegiate Athletes Competitive Aggressiveness, Anger, and the Experience of Provocation in Collegiate Athletes Michael E. Berrebi Follow this and additional works at: https://researchrepository.wvu.edu/etd Recommended Citation Berrebi, Michael E., "Competitive Aggressiveness, Anger, and the Experience of Provocation in Collegiate Athletes" (2018). Graduate Theses, Dissertations, and Problem Reports. 5194. https://researchrepository.wvu.edu/etd/5194 This Dissertation is protected by copyright and/or related rights. It has been brought to you by the The Research Repository @ WVU with permission from the rights-holder(s). You are free to use this Dissertation in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you must obtain permission from the rights-holder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/ or on the work itself. This Dissertation has been accepted for inclusion in WVU Graduate Theses, Dissertations, and Problem Reports collection by an authorized administrator of The Research Repository @ WVU. For more information, please contact researchrepository@mail.wvu.edu. Competitive Aggressiveness, Anger, and the Experience of Provocation in Collegiate Athletes Michael E. Berrebi, M.S. Dissertation submitted to the College of Physical Activity and Sport Sciences at West Virginia University in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Sport & Exercise Psychology Edward Etzel, Ed.D., Chair Jack Watson II, Ph.D. Scott Barnicle, Ph.D. David Mitchell, Ph.D. Department of Sport Sciences Morgantown, West Virginia 2018 Keywords: anger, aggression, aggressiveness, provocation, college athletes © 2018 Michael E. Berrebi ABSTRACT Competitive Aggressiveness, Anger, and the Experience of Provocation in Collegiate Athletes Michael E. Berrebi In sport, aggressive behavior is a potentially harmful byproduct of uncontrolled anger. In addition, it is known that provocation can lead to both anger and aggressive retaliation. However, despite the potential consequences of aggressive behavior, little is known about levels of competitive anger and aggressiveness in athletes, and it is unclear if differences exist by gender or type of sport. Little research has also explored intervention approaches to help athletes better manage anger and aggression. Therefore, the purpose of this study was to explore competitive aggressiveness, anger, and the experience of provocation among collegiate athletes. Participants were 243 male and female contact or collision sport athletes competing at NCAA Division I, II, and III universities across the country. Participants filled out questionnaires assessing both competitive aggressiveness and anger and the experience of provocation. Overall, it was found that male athletes scored significantly higher than female athletes on competitive aggressiveness, as well as experiencing more frequent provocative behavior and more negative and intense responses to provocation. Collision sport athletes were also found to be higher in competitive aggressiveness and anger, regardless of gender. Division I and II athletes were found to be significantly higher than Division III athletes in competitive aggressiveness and anger. TABLE OF CONTENTS iii Page # 1. INTRODUCTION……………………………………………………………………….........1 2. METHODS……………………………………………………………………………….......11 2.1. Participants………………………………………………………………………....11 2.2. Research Design and Sampling…………………………………….……………....11 2.3. Instrumentation…………………………………………………………………......12 2.3.1. Demographic questionnaire…………………………………………........12 2.3.2. Competitive aggressiveness and anger…………………………………...12 2.3.3. Provocation…………………………………………………………….....14 2.3.4. Pilot study…………………………………………………………….......15 2.4. Procedure……………………………………………………………………….......16 2.5. Data Analysis…………………………………………………………………….....17 3. RESULTS……………………………………………………………………....….………....20 3.1. Demographics and Descriptive Statistics ………………………………….............20 3.2. Data Cleaning and Assumption Testing ……………………...…….……………...21 3.3. Bivariate Statistics……………………………………………………………….....22 4. DISCUSSION……………………………………………………………………...….…......27 4.1. Competitive Aggressiveness and Anger……………………………………..…....27 4.1.1. Gender comparisons………………………………………………….......27 4.1.2. Sport type comparisons………………………………………………......28 4.1.3. Division level comparisons…………….....………………………….......32 4.2. The Experience of Provocation………………………………………………........35 iv 4.2.1. Gender comparisons………………………………………………….......35 4.2.2. Sport type comparisons………………………………………………......36 4.2.3. Division level comparisons…………………………………………........38 4.3. Future Research and Directions…………………………………….……......…....39 4.3. Study Strengths and Limitations……………………………....…………......…....42 5. REFERENCES…………………………………………………………………………….....44 6. APPENDICES……………………………………………………………………………......53 6.1. Appendix A: Data Tables………………….…………………………..………........53 6.2. Appendix B: Extended Review of Literature…………………………..……….......75 6.2.1. Part I: Competitive Anger in Sport………………………………….......75 6.2.2. Part II: Aggressive Behavior in Sport…………………………………...88 6.2.3. Part III: Managing Anger and Aggressive Behavior in Sport…….........107 6.2.4. Significance of Study…………………………………………………..115 6.2.5. References…………………………………………………...................121 6.3. Appendix C: Assistant and Head Coach Recruitment Letter……..…………….....139 6.4. Appendix D: Participant Cover Page………………………………..….................140 6.5. Appendix E: Demographic Questionnaire…………………………….…..............141 6.6. Appendix F: Competitive Aggressiveness and Anger Scale………………….......142 6.7. Appendix G: Sport Provocation Questionnaire…………….……………….…….143 6.8. Appendix H: SPQ Pilot Data and Feedback…………………………..………......146 AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 1 Introduction In sport, there is sufficient anecdotal and empirical evidence that suggests being able to manage one’s emotions is a key factor in influencing performance (e.g., Hanin, 2010; Lane, 2007; Woodcock, Cumming, Duda, & Sharp, 2012). In addition to athletic ability, teamwork, and strategy, sport performance also hinges upon the ability of the athlete to regulate emotions. Throughout a competition, athletes experience a variety of positive and negative emotions that can influence motivation and change both physical and cognitive performance (Botterill & Brown, 2002). More recently, it has been suggested that being able to regulate emotions in sport is an important determinant of performance outcomes both for individual athletes (e.g., Lane, Beedie, Jones, Uphill, & Devonport, 2012) and teams (Wagstaff & Weston, 2014). Anger has been described as “an emotional state that consists of feelings that vary in intensity, with associated activation or arousal of the autonomic nervous system” (Spielberger & Reheiser, 2009, p. 281). A key component of this definition is the lack of judgment regarding whether anger is a “good” or “bad” thing, but rather a normal, human emotion. In fact, experiencing anger is somewhat unavoidable, especially in high-stress, pressure-packed environments that competitive sports embody. Whether an athlete’s anger becomes problematic appears to be less about the fact that it is present and more about the nature and severity of behavioral outcomes (Kassinove & Tafrate, 2002). In fact, researchers who have explored whether anger helps or hurts performance in sport have presented mixed results (e.g., Robazza & Bortoli, 2007; Ruiz & Hanin, 2011). It seems the most important factor is how anger is interpreted and managed by athletes (Hanin & Syrja, 1995). Despite a growing body of research focused on exploring emotions in sport, anger has not been thoroughly investigated. This is in spite of the knowledge that anger is one of the most AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 2 common emotions that athletes experience during competitive play (Sofia & Cruz, 2016). While anger is an emotion expressed by a high percentage of athletes, researchers suggest gender, competition level, and type of sport may play a factor in the level of anger experienced by athletes (Maxwell, Visek, & Moores, 2009). Some findings suggest the possibility that athletes with a perfectionist orientation are at a greater risk for experiencing anger when the pressure is on (Vallance, Dunn, & Dunn, 2006). It has also been identified that male and female athletes may cope with anger in similar ways (Bolgar, Janelle, & Giacobbi, 2008). Overall, the nature and degree of differences among gender and level/type of sport is still largely unknown. Anger has been associated with a number of negative performance outcomes such as misuse of energy, a decrease in achievement and motivation, and the possibility of violent behavior (Robazza et al., 2006). The fact that uncontrolled anger can lead to aggressive or violent behavior has been known for decades (e.g., Berkowitz, 1993; Feindler & Ecton, 1994). However, few studies have been published in the years since that explore the relationship between competitive anger levels and aggressive behavior. Maxwell (2004) found that simply ruminating about past experiences that have caused anger could increase the possibility of aggression. In addition, being provoked and having thoughts of revenge have been found to be significantly related to self-reported aggression (Maxwell, Moores, & Chow, 2007). Unfortunately, it remains difficult to assess competitive anger, which is required to provide a more clear understanding of how it impacts aggression. Part of the problem stems from how to accurately assess anger and aggressive behavior. Outside of sport, instruments such as the State Trait Anger Expression Inventory (STAXI; Spielberger, 1988) have been constructed to help assess the experience, expression, and control of anger. However, nearly thirty years since the introduction of the STAXI, it still has not been normed on athletes or become a standard form AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 3 of measurement in sport psychology research. There currently exists no standard method to assess anger or aggressive acts in sport. Being able to utilize trained observers to identify aggression would be ideal. This would help identify what led to the aggressive act, the act itself, and the resulting consequences. This is unfortunately a time-consuming and potentially expensive process. In addition, aggressive behavior may not always be noticeable on a game-to game basis (Maxwell & Moores, 2007). The Competitive Aggressiveness and Anger Scale (CAAS) is a notable instrument used to assess both competitive anger and aggressiveness, or the tolerance of aggressive behavior and inclination to aggress. The CAAS (Maxwell & Moores, 2007) is a 12-item instrument that assesses anger (e.g., frustration from missed calls from referees) and aggressiveness in a sport setting. While aggressiveness is a trait rather than a behavior (like aggression), it is one of the better ways to assess the probability of aggressive behavior in a proactive way (i.e., before it actually happens). Few researchers have utilized the CAAS since its inception (e.g., Visek Maxwell, & Hurst, 2011), but it appears to be an efficient and promising instrument for use in the exploration of anger and aggressiveness in athletes. Another consideration in the study of aggression is the lack of a clear consensus on how to define and differentiate assertive and aggressive behavior, and also what constitutes “violence” (Abrams, 2010; Kirker, Tenenbaum, & Mattson, 2000). Currently, one of the more common methods to help understand aggression is to split these types of behaviors into instrumental and hostile types (Husman & Silva, 1984). The major difference is the distinction that instrumental aggression may cause harm, but has the overarching goal of pursuing a nonaggressive goal (such as scoring points). Hostile aggression suggests a primary intent of injuring another person physically or psychologically. Abrams (2010) suggested that violence AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 4 can be spontaneous or planned, with the end goal to hurt another person. Spontaneous violence seems to be a result of being provoked, while planned violence is intentional and a “complete system failure” (p. 6). Abrams went on to suggest that athletes displaying this type of behavior should be immediately removed from the playing field and, in extreme instances, even prosecuted. With these definitions as resources, hostile and planned violence are the most dangerous. What must happen for athletes to feel it necessary to display these types of behaviors? There is no doubt that feeling frustrated and angry are important factors in understanding aggressive behavior (Berkowitz, 1993; Feindler & Ecton, 1994; Robazza et al., 2006;). However, simply feeling angry does not automatically cause one to lash out aggressively. What other factors come into play? To help answer this question, a number of theories have been put forth to help understand the potential causes of aggression. Examples include the instinct theory, frustration aggression theory (Dollard, Doob, Miller, Mowrer, & Sears, 1939), social learning theory (Bandura, 1973), theory of moral reasoning (Bredemeier, 1994), and revised frustration-aggression theory (Berkowitz, 1965; 1993). Instinct theory suggests aggression is an innate human instinct that builds up until it must be expressed either directly or cathartically (through sports for example). Based on Albert Bandura’s seminal work, social learning theory predicts aggression is learned by observation, and aggression that is reinforced is likely to reoccur if not penalized. The theory of moral reasoning postulates that how likely a person is to aggress is based on their level of moral development. One of the more widely held views, Berkowitz’s revised frustration-aggression theory suggests frustration only leads to aggression when an individual encompasses the social cues that indicate aggression is appropriate in a particular instance. This theory is important in AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 5 understanding how frustration in competition can play an important factor in determining aggressive behavior, based on the individual and his/her environment. One of the least understood experiences related to being frustrated and taking it out aggressively, is the act of provocation. According to Maxwell, Moores, and Chow (2007), provocation is “any behavior [of another person or persons] that is judged by the victim as aversive or unpleasant, normally with intent on the part of the perpetrator implicitly assumed, and rousing feelings of anger, frustration, or fear” (p. 11). This definition suggests that provocation is assumed to involve intent by the perpetrator. This is a key distinction, as it should not be considered provocation if an athlete, simply by competing hard and without harmful intent, frustrates or angers an opponent to the point of him/her lashing out. In his work on revised frustration-aggression hypothesis, Berkowitz (1989) suggested that provocation, along with frustration and aversive stimuli, could lead to aggression through the generation of negative affect that is interpreted by the individual as anger. Provocation is one of the clearest antecedents of aggression in both non-sporting (e.g., Harris, 1993) and sporting (e.g., Huang, Cherek, & Lane, 1999) environments. Outside of sport, researchers have suggested that provocation may cancel out any inhibitory effects that empathy can have on aggressive behavior (Phillips & Giancola, 2007; Stranger, Kavusannu, McIntyre, & Ring 2016). Other research suggests that provocation itself is frequently interpreted as offensive and has been linked to increases in overall anger levels (Mohr et al., 2007). Maxwell (2004) was one of the first researchers to focus on understanding the experience and consequences of provocation in athletics. He reported that provocation might be positively associated with aggression in athletes. This mirrored similar findings of research on norm breaking behaviors in sport, in which Kirker, Tenenbaum, and Matteson (2000) observed that AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 6 mild aggressive acts often followed provocation acts in a vengeful manner. In the worst cases, this sometimes resulted in more severely violent aggression. Maxwell (2004) claimed athletes from team sports report greater frequency of provocation than athletes who compete in individual sports. A few years later, Maxwell and Moores (2007) suggested that males experience provocation at a greater frequency than females, suggesting that males may perceive more incidences as provoking in sport. Maxwell, Visek, and Moores (2009) found that athletes who competed in high contact team sports tended to experience higher provocation while playing sport. Findings of this study suggested that provocation can be seen as a justification for retaliatory aggression, but not always between the original combatants, at least in team sports. Importantly, it has also been suggested that individuals with high trait anger are more likely to feel more readily provoked and endorse aggressive acts as a result (Maxwell, Visek, & Moores, 2009). This hypothesis was originally put forth by Spielberger (1988), who suggested in his state-trait anger theory that high trait anger individuals experience anger more frequently and longer than low trait anger individuals. In addition, these people are more likely to express this anger in an aggressive or harmful manner. Unfortunately, this theory has not been explored in the realm of athletics, and little knowledge exists regarding the characteristics of athletes that are more or less likely to have high trait anger (or respond aggressively when triggered or provoked). Clearly, some research exists that suggests provocation is an important factor in determining anger and aggressive behavior (e.g., Maxwell, Visek, & Moores, 2009; Stranger et al., 2016). However, assessing provocation is difficult since ideally (as with aggressive behavior), provocation is assessed by observation. However, this method is timely and unpredictable, in addition to somewhat subjective. An act perceived as provocative to one athlete may not necessarily be perceived the same way by others. Furthermore, sometimes provocation AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 7 is verbal, which can be difficult to assess by outside observers. Currently, neither observer assessment or provocation nor adequate self-report measures have been documented in the literature. Maxwell and Moores (2006) attempted to meet the need of a self-report assessment in sport by crafting the Provocation in Sport Questionnaire (PSQ), a six-item self-report questionnaire that inquires about incidences of provocation common in many sports. These statements were scored by athletes on a five-point Likert-type scale to help understand the frequency of each provocation type and the corresponding intensity of anger. Unfortunately, this scale is no longer available and no other known instrument exists in which to assess the experience of provocation in sport. Since provocation seems to be a key factor in understanding anger and aggressive behavior in sports, a novel assessment of provocation is needed to help develop this area of sport psychology research. Therefore, the purpose of this study was to explore the relationship between self-reported competitive aggressiveness, anger, and provocation in collegiate male and female contact and collision sport athletes. Contact and collision sport athletes are an important population to investigate because they are frequently in close proximity with opponents during competition and are therefore more likely to engage in aggressive behavior. Non-contact sport athletes were not included in this investigation. Based on the modest amount of research available on anger, aggression, and provocative behavior in sport, this study explored these variables while controlling for gender and type of sport (i.e., contact vs. collision). It has been suggested that gender and type of sport have significant competitive anger and aggression differences based on previous research (e.g., Maxwell, Visek, & Moores, 2009). For example, some studies have suggested that male athletes AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 8 are more aggressive than their female counterparts, both on and off the field (e.g., Burton & Marshall, 2005; Coulomb-Cabagno & Rascle, 2006). Male athletes have also been found to perceive aggression as more legitimate than females (e.g., Bredemeier, 1985; Gardner & Janelle, 2002; Tucker & Parks, 2001). Other research has disputed these findings (e.g., Bolgar, Janelle, & Giacobbi, 2008; Keeler, 2007). Ultimately, aggression studies that focused on gender have revealed conflicting findings, with no significant differences being reported between males and females (Kimble et al., 2010). With this knowledge in mind, the first major research question in the study was: “Does competitive anger, aggressiveness, and experience of provocation vary between male and female college athletes?” The second major research question was: “Does competitive anger, aggressiveness, and provocation vary between contact and collision sport college athletes?” Based on prior research, there were two main hypotheses in this study. The first was that male athletes would score higher on the CAAS anger and aggressiveness subscales, in addition to experiencing (and responding negatively to) more provocation than female athletes. The second was that collision sport athletes would score higher on the CAAS anger and aggressiveness subscales, in addition to experiencing more provocation and more frequently responding to provocation than contact athletes. There were a number of assumptions made by the researcher in this study. For example, although prior research was ambiguous (e.g., Coulomb-Cabagno & Rascle, 2006, Keeler, 2007), it was assumed that gender does play a significant role in the relationship between anger, aggressiveness, and provocation. It was also assumed that contact and collision sport athletes differed in aggressiveness, anger, and/or experiences of provocation. Closely related to that is the assumption that provocation played a significant role in determining one’s level of competitive AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 9 anger and aggressiveness. Finally, it was assumed that the original sport provocation questionnaire being used in this study adequately assessed the experience of provocation in collegiate sport. There is currently a major gap in the understanding of how anger, aggressive behavior, and provocation interact in sport settings. There exists no valid assessment tool for the experience of provocation in sport. In order to develop interventions to mitigate anger responses to provocation, a more clear understanding of the interaction of aggression, anger and provocation is required. Understanding the characteristics of athletes who are prone to high anger levels, aggressiveness, and experiencing provocation will help in the development of more focused interventions for these individuals. Male athletes may not actually be more aggressive than female athletes, despite popular perception, and therefore interventions for one gender could be utilized effectively for the other. However, anger levels and aggressiveness may be significantly different, in which case gender-specific programming and interventions may be required. While the current study is largely exploratory, increasing the understanding of provocation can be helpful for athletes, coaches, sport psychology consultants, and even referees. Being able to understand how frequent provocative behavior occurs, how it is being displayed, how it affects athletes, and how often it is reciprocated is valuable both theoretically and practically. Team sport contact and collision athletes can better understand what to expect in competition and coaches may be able to better prepare athletes for provocative behavior. Coaches of certain types of teams (e.g., male teams or collision sports) need better information, education, and programming to help promote an environment more conducive to safe, sanctioned play. AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 10 It is vital to understand who the at-risk athletes may be so they can be provided better education and emotional regulation resources, as it is possible high trait anger athletes are more likely to be involved in aggressive on-field acts (Maxwell, Visek, & Moores, 2009). Similarly, coaches and sport psychology consultants can use the findings to better understand aggression and where and why it is likely to occur. Referees could foster a better sense of how to officiate sport to eliminate provocative behavior before it turns into dangerous reciprocation. Nearly all stakeholders involved in collegiate sport could benefit from the findings of this study, as a better understanding of the relationship between provocation and competitive anger and aggression in sport is necessary. AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 11 Methods Participants Participants were 243 (M = 124) male and female athletes from NCAA Division I, II, and III universities throughout the continental United States. The age range of participants was between 18-23 years. Participants were sampled from both contact and collision team sports. To be considered a contact sport, in-game contact is allowed, but extreme contact or direct collisions are not implicit or required by the rules of the sport (Keeler, 2007; Silva, 1983). For the purposes of this study, men’s and women’s basketball, field hockey, women’s lacrosse, and men’s and women’s soccer were all considered contact sports. For collision sports, collisions are necessary and integral, and they are also considered a predesigned aspect of appropriate goal-directed behavior in that sport (Keeler, 2007; Silva, 1983). Collision sports sampled for this study included football, men’s lacrosse, men’s and women’s rugby, and men’s and women’s ice hockey. Research Design and Sampling This study employed a quantitative, survey-based approach to investigate the relationships between three phenomena of interest: 1) competitive anger, 2) aggressiveness, and 3) provocation in collegiate sport. The researcher used purposive sampling to select participants who met the inclusion criteria for the study (Creswell, 2014). This criterion was being a current NCAA Division I, II, or III athlete and competing in selected contact or collision sports. This was also a sample of convenience due to the researcher using personal contacts at various universities to gain access to athletes competing at those universities. Sampling began during the 2017 summer “off-season” period and ended in October of the Fall 2017 competitive season. After the initial sampling period, additional attempts at recruiting participants were implemented AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 12 every two weeks. This entailed follow-up email reminders to coaches requesting that they pass along the survey link to their athletes. Instrumentation Coaches were contacted via email and asked to forward the survey link to athletes on their team (see Appendix C). If participants were willing to partake, they clicked on the survey link to find an informational cover page (see Appendix D), followed by the online survey that consisted of a short demographics questionnaire, a sports-based competitive anger and aggressiveness assessment, and a provocation questionnaire. The order of the questionnaires was randomized for participants to help reduce the possibility of an order effect (Creswell, 2014). The provocation assessment was an original questionnaire that focused on the participant’s experience of provocation during athletic competition. It was detailed in the participant cover page that consent was implied by completing the online survey. All three sections of the online survey was predicted to take approximately fifteen minutes to fill out. Demographic questionnaire. The researcher used a demographic survey to gather the following seven variables of interest: 1) age, 2) gender, 3) race/ethnicity, 4) year in school, 5) type of sport, 6) name of university, and 7) NCAA division level. While some identifying information such as school of enrollment was collected, all information was kept confidential and secured online using password-protected software. Once downloaded, study data was stored in encrypted files on the researcher’s personal computer. Demographic information was also collected at the beginning of the survey, which has been shown to increase item response rate for participants who begin the survey (Teclaw, Price, & Osatuke, 2011). (See Appendix E) Competitive aggressiveness and anger. The Competitive Aggressiveness and Anger Scale (CAAS; Maxwell & Moores, 2007) is a 12-item self-report questionnaire designed to AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 13 assess competitive anger and aggressiveness, or the tolerance of aggression and inclination to aggress, in sport settings. The CAAS is divided into two subscales: a) anger, and b) aggressiveness subscales, with six items in each subscale rated on a five-point Likert type scale from 1=almost never to 5=almost always. A sample item from the anger subscale is: “I find it difficult to control my temper during a match”. A sample item from the aggressiveness subscale is: “It is acceptable to use illegal physical force to gain an advantage”. Using confirmatory factor analysis (CFA), the authors reported good internal consistencies for each subscale and the total scale score. These Cronbach alphas include: anger (α = .78), aggressiveness (α = .84), and total (α = .87; Maxwell & Moores, 2007). These values all fall within the generally accepted reliability levels as determined by Nunnally and Bernstein (1994). Concurrent validity was established with subscales of the Buss-Perry Aggression Questionnaire (BPAQ; Buss & Perry, 1992). In addition, the authors found adequate one-month test-retest statistics for the subscales and total scale score. Discriminant validity was established using peer perception of aggressive orientation. The anger and aggressiveness subscales were also found to be moderately correlated to each other (e.g., α = .59 and .60), suggesting that they are related but not too similar in nature. This is in agreement with literature that suggests a relationship exists between anger and aggression (e.g., Buss & Perry, 1992; Maxwell, 2004), in addition to a clear link with aggressiveness. When crafting and examining the psychometric properties of the scale, the authors found differences in gender and type of sport, with males and contact sport athletes reporting a higher tendency to aggress than females and non-contact athletes (Maxwell & Moores, 2007). The CAAS is one of the only known sport-specific scales to assess competitive anger and aggressiveness in athletes. However, the factor structure of the CAAS has been found to be AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 14 replicable with both Americans and English-speaking Chinese athletes. It has been identified as an appropriate way of assessing athletes most likely to display acts of aggression (Visek, Maxwell, Watson, & Hurst, 2011). The CAAS was intended to be a trait measure, so it does not take into account fluctuations in state anger and aggressiveness throughout an athletic competition. Other limitations include that it lacks a social desirability check and was constructed using a non-elite sample of athletes. (See Appendix F) Provocation. To assess participants’ experience of provocation during competition, an original questionnaire was utilized in this study. This questionnaire is based on the Provocation in Sport Questionnaire (PSQ; Maxwell & Moores, 2006), which was a scale that contained six short statements representing incidences of provocation that are common in sports. In the only confirmed published study utilizing it, the PSQ was translated to use in Chinese (Maxwell, Moores, & Visek, 2009). The scale measured the frequency at which respondents experienced various types of perceived provocation and the corresponding self-reported intensity of associated anger on five-point Likert type scales. The PSQ was the only known instrument to study the experience of provocation in sport. Unfortunately, the full version of the PSQ is no longer available for use as it cannot be located. Instead, a new provocation questionnaire was created to assess the experience and response of various incidences of provocation (i.e., verbal, gestures, and physical). The Sport Provocation Questionnaire was constructed using the original PSQ by Maxwell and Moores (2006) as a foundation, in addition to information collected from current and former athletes about their experiences. The author’s own experiences and observations of athletic competition also factored into the construction of the questionnaire. Specifically, the items assess the AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 15 frequency of experienced provocation, the frequency of one’s response to provocation, the level of anger felt by provocation, and the intensity of one’s response to being provoked. For each item, scores range from 1 (lowest) to 5 (highest). Higher scores represent greater frequency of provocation and response to provocation, as well as more intense anger felt by provocation. The intensity of provocation is assessed as ordinal data and will be analyzed separately from the other categories of the questionnaire. An example of an item assessing frequency of provocation is: “In competitive sports, how likely do you experience the following types of verbal provocation? a) the use of curse words or verbal abuse; b) the use of racial/ethnic slurs; c) the use of violent threats”. An example of an item assessing anger level from provocation is: “In competitive sports, what is your level anger when an opponent: a) aggressively or inappropriately touches you; b) purposefully shoves or trips you; c) punches or kicks you; d) purposefully strikes you with an instrument (like a helmet or stick)”. (See Appendix G). Pilot study. After obtaining IRB approval, the sport provocation questionnaire was piloted with a sample of twenty-two former high school and collegiate athletes. The mean age for all participants was 25.23 (SD = 4.33); 7 participants were male. Nearly half (45.5%) of all pilot participants played at the NCAA collegiate level, while the remaining played high school sports. Just over two-thirds of participants (68.2%) played contact sports, while the second biggest group (18.2%) played collision sports. The majority (63.4%) of participants played soccer, while the rest played a variety of contact or collision team sports such as basketball, hockey, or football. All participants filled out the questionnaire based on their prior sport experiences involving provocation. Open-ended feedback obtained from the pilot research was used to AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 16 improve the content and structure of the questionnaire and can be found in Appendix H. The four provocation scales were found to have adequate internal reliability, and the scales were moderate-highly correlated to each other (Field, 2009). These values suggest the scales are related to each other but still assessing different concepts in the experience of provocation. This information, in addition to the descriptive and correlational data obtained from the pilot study, can also be found in the tables in Appendix H. At this time, no standardized assessment of provocation in sport exists. With adequate internal reliability and sufficient face validity, it is expected that this new questionnaire will help build the foundation for future research to explore this important phenomenon. Procedure IRB approval was obtained before data collection began. Both assistant and head coaches from selected sport teams were contacted via email to explain the study and request participation from the athletes on their teams. As a small incentive, coaches were informed that participation in the study would grant them access to a general summary of the study findings once the researcher has compiled and analyzed all data. If they chose to participate, coaches were asked to forward the Qualtrics survey link to all of the athletes on their team. After the initial introductory email, all assistant and head coaches were contacted every two weeks with follow-up emails requesting their athletes participate in the study. Towards the end of the data collection period, a small number of other university athletic department personnel (e.g., athletic director or sport psychology consultant) were contacted at some schools to try to increase the sample size and generate adequate statistical power. All participants who opened the survey link first saw an informative cover letter detailing the purpose of the study and an explanation of participant rights (i.e., confidentiality, right to AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 17 withdraw at any time). There was also an option to print a copy of the cover letter for personal records. If participants agreed to continue, they were then asked to enter basic demographic information. Participants were then presented with online versions of both the CAAS and the sport provocation questionnaire. Successful completion of the demographic information and two surveys was predicted to take approximately fifteen minutes. Finally, the participants received the primary investigator’s contact information so that participants could communicate with the researcher about any issues related to the collection procedures, their data, or any other study related concerns. Data collection began during the summer off-season period but continued into the competitive Fall 2017 season. The off-season was decided as the best time to sample since most athletes were not as busy with school and training obligations. Collecting data at this time may also have helped avoid any bias due to abnormally high or low frustration or anger being experienced by athletes in the middle of the competitive season (for example, after a particularly disappointing or successful game or overall season). Data Analysis A G*Power 3.1 analysis (Faul, Erdfelder, Lang, & Buchner, 2007) revealed approximately 120 total participants would be the minimum sample size required to see a significant gender effect at the 95% level. After an adequate sample was collected, data analysis included both descriptive (e.g., frequencies, correlations, measures of central tendency, and standard deviations) and inferential statistical tests (e.g., internal reliability analyses and ANOVAs) to investigate the study hypotheses. All collected data was cleaned in Microsoft Excel and entered into the IBM Statistical Package for Social Sciences version 24 (SPSS, 2016). AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 18 The independent variables in this study included gender and type of sport. These were assessed on the demographic page. There are three dependent variables in the study: 1) competitive anger, 2) aggressiveness, and 3) provocation. These variables were assessed using the CAAS and sport provocation online questionnaires. Frequencies, means, standard deviations, and other descriptive data were calculated for demographic information such as age, gender, race/ethnicity, school, division, and type of sport. Overall means and standard deviations were calculated for all CAAS and provocation subscales. Standard bivariate correlations were also calculated among gender, type of sport, and the competitive anger, aggression, and provocation data. There were two primary research questions in this study. The first was: “How does competitive anger, aggressiveness, and experience of provocation vary among male and female athletes?” The second primary research question was: “How does competitive anger, aggressiveness, and provocation vary among contact and collision sport athletes?” These primary research questions were examined using a general linear model (GLM) to run multiple one-way analysis of variance (ANOVAs). To investigate the possibility of an interaction between the independent variables of gender and type of sport, two-way ANOVAs was used. Two-way ANOVAs helped answer the question of how scores on the dependent variables of CAAS or sport provocation questionnaire scores differed by gender and type of sport. For correlations, anger and aggressiveness subscale scores from the CAAS and provocation subscale scores were run together in a correlational matrix to examine the strength of the relationship between the variables. This was completed for the male and female data, as well as type of sport, to compare correlation strengths among the different variables. AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 19 Additional ad hoc analyses were completed to assess other study variables such as NCAA Division level or year in school. For example, differences in anger, aggressiveness, and experience of provocation were examined between NCAA Division I and Division III athletes. No current research suggests there are anger or aggressiveness differences among NCAA Division levels, but it is possible that at higher competitive levels, more competitive anger and aggressive behavior is produced due to the rising stakes, pressure, and fanfare. AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 20 Results Demographics and Descriptive Statistics A total of 243 NCAA athletes from 18 universities participated in the current study. From the final data aggregate, any participants who completed less than 40% of the survey questionnaire items were excluded from the final data analyses. The mean participant age was 19.53 (SD = 1.36). Participants were composed of 124 males and 119 females. At the time of data collection, they were playing one of ten different male or female team sports that included basketball, soccer, lacrosse, hockey, football, and rugby. Approximately 38% of participants were freshmen, with 20% sophomores, 21% juniors, and 15% seniors. In addition, 5% of participants identified as fifth-year seniors or graduate students. Over one-fourth (26%) of participants were enrolled in NCAA Division I universities, with 29% attending Division II schools and the remaining 44% attending Division III schools. Just over half (53%) of all participants played contact sports, while the rest (47%) were involved in collision sports. This demographic information is summarized in Table A1. Subsequent to data collection, Cronbach’s alpha analyses of internal consistency were calculated for the four provocation and CAAS scales (see Table B1). Review of these analyses revealed that all four provocation scales had adequate internal consistency, and were moderate highly correlated to each other (Field, 2009). These Cronbach’s alphas coefficients provided evidence to support the interpretation that the scales are appropriately related to each other but addressing different parts of the experience of provocation in collegiate sport. Internal reliability analysis was also utilized for the six-item Anger and Aggressiveness subscales of the CAAS, which were found to have moderate-high correlations. AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 21 Data Cleaning and Assumption Testing The following adjustments were made on the data in SPSS to ensure the ensuing bivariate analyses were accurate. The first change was to code an additional “6” Likert-type response (i.e., N/A or have not experienced) as a discrete missing variable. This ensured that these responses were not included in the standard scaled data for the provocation items. The second adjustment was to multiply all of the CAAS scores by the proper mean intensity of each item (following the procedures outlined by Maxwell & Moores, 2007). The authors conducted this step during the development of the CAAS because individual items on the two subscales are not equally weighted, with some impacting the anger or aggressiveness score more than other items. Finally, a total score variable was created for both the CAAS and SPQ instruments. The CAAS total score was created by summing the six-item Anger and Aggressiveness subscales. The provocation total score was calculated as the average of the four provocation scales, using data from participants who filled out at least three out of four mean responses. This decision was made to ensure the anger level provocation subscale data was included despite having to code for the “6” missing data choice. Overall, this resulted in a total of 18 participants being removed from the final database before final analyses were conducted. Before conducting inferential statistical analyses, the data were examined using SPSS to ensure that it met the appropriate assumptions needed for valid two-way ANOVA results. The assumptions of a continuous dependent variable, independence of observations, and independent variables with categorical groups were all satisfied based on random sampling and the type of variables (e.g., continuous, ordinal) utilized in the study. Using box and whisker plots (Field, 2009), only one outlier was identified from the CAAS Anger subscale data and five from the CAAS Aggressiveness subscale data. These were not considered extreme outliers, (i.e., over AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 22 three times the Interquartile Range) so they were retained in the database. Up to three outliers were identified for the four different provocation subscales, but these were also included in the final data aggregate since they did not constitute extreme outliers that would likely have a significant detrimental effect on the analyses. The normality of the data was examined using kurtosis/skewness values as well as histograms and Q-Q plots. Overall, the data for nearly all of the subscales followed a normal distribution, with only slight departures from normality found on the CAAS Aggressiveness and negative response to provocation subscale data. These departures consisted of slight floor effects, meaning the subscales had a clear lower limit of possible participant’s responses. This caused a larger than usual number of scores to congregate near this limit. However, ANOVA is known to be particularly robust to violations of normality, so the analyses were carried out despite these aforementioned slight departures. Levene’s test, as well as assessing the data spread vs. Q-Q plots, was utilized to test the homogeneity of variances (Field, 2009). While the CAAS aggressiveness and negative response to provocation subscales varied more than expected in normally distributed data, the standard deviation spread was not large compared to the mean differences. This suggested that running the ANOVA using the data would not be overly problematic, and it would be unnecessary to run non-parametric tests of ANOVA. Bivariate Statistics The first primary research question in this study was: How does competitive anger, aggressiveness, and the experience of provocation vary among male and female athletes? To answer this question, a one-way between subjects ANOVA was conducted to compare scores on the CAAS among male and female athletes (see Table C1). For all ANOVAs, SPSS was used to calculate effect size, represented as partial eta square (η2). To compare magnitude of effect AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 23 sizes, rule of thumb values (small = .01, medium = .06, and large = 0.14) were used based on recommendations set forth by Vacha-Haase and Thompson (2004). There was a statistically significant effect of total CAAS score among gender [F(1, 237) = 23.68, p < 0.001, η2 = .091], with males (M = 55.79, SD = 19.41) scoring significantly higher than females (M = 45.52, SD = 12.12). Additional one-way between subjects ANOVAs were conducted to compare scores on the CAAS Anger and Aggressiveness subscales by gender. There was no statistically significant effect of CAAS Anger scores among gender [F(1, 241) = 1.35, p = 0.247, η2 = .006], although males (M = 26.43, SD = 8.59) scored non-significantly higher than females (M = 25.23, SD = 7.47) (see Table C2). There was, however, a significant effect for CAAS Aggressiveness subscale scores among gender [F(1, 237) = 46.27, p < 0.001, η2 = .163], with males (M = 29.36, SD = 12.60) scoring significantly higher than females (M = 20.29, SD = 7.02) (see Table C3). There was not a statistically significant effect of total SPQ score among gender [F(1, 217) = 2.49, p = 0.12, η2 = .011], although males (M = 2.38, SD = 0.68) scored slightly higher than females (M = 2.24, SD = 0.55) (see Table C4). However, when separated into the four provocation subscales, statistically significant differences were found among all four provocation subscales between male and female athletes. Specifically, males scored significantly higher than females on frequency of provocation experienced, frequency of negative response to provocation, and intensity of response to provocation. Females scored significantly higher than males on anger felt from provocation (see Table C5). The second primary research question in this study was: How does competitive anger, aggressiveness, and the experience of provocation vary among contact and collision sport athletes? To answer this question, a one-way between subjects ANOVA was conducted to AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 24 compare scores on the CAAS among type of sport (see Table C6). There was a statistically significant effect for total CAAS score among type of sport [F(1, 237) = 31.17, p < 0.001, η2 = .116], with collision sport athletes (M = 56.98, SD = 18.85) scoring significantly higher than contact sport athletes (M = 45.35, SD = 13.13). Additional one-way between subjects ANOVAs were conducted to compare scores on the CAAS Anger and Aggressiveness subscales by type of sport. There was a statistically significant effect for CAAS Anger subscale scores among type of sport [F(1, 241) = 4.04, p = .046, η2 = .016], with collision sport athletes (M = 26.95, SD = 8.35) scoring significantly higher than contact sport athletes (M = 24.88, SD = 7.72) (see Table C7). There was also a significant effect for CAAS Aggressiveness subscale scores among type of sport [F(1, 237) = 52.25, p < 0.001, η2 = .181], with collision sport athletes (M = 30.03, SD = 12.30) scoring significantly higher than contact sport athletes (M = 20.48, SD = 7.84) (see Table C8). There was also a statistically significant effect for total SPQ score among type of sport [F(1, 217) = 7.39, p = .007, η2 = .033], with collision sport athletes (M = 2.43, SD = 0.65) scoring significantly higher than contact sport athletes (M = 2.21, SD = 0.57) (see Table C9). To better understand what aspects of provocation were significantly different, one-way ANOVAs were run for each of the four subscales of the SPQ. The results of these analyses can be found in Table C10. Specifically, collision sport athletes scored significantly higher than contact sport athletes on the frequency of provocation experienced and frequency of negative response to provocation. A two-way ANOVA was conducted to examine the effect of gender and type of sport on total CAAS scores (see Table C11). The results of the two-way ANOVA provided evidence to indicate there was no statistically significant interaction effect between gender and type of sport. AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 25 This suggests that any total CAAS score differences between contact and collision sport athletes were not dependent upon the gender identified with by the participants and that any total CAAS score differences between females and males were not dependent upon which type of sport they played. A separate two-way ANOVA was conducted to examine the effect of gender and type of sport on total SPQ scores (see Table C12). The results of the two-way ANOVA provided evidence to support the notion that there was no significant interaction effect between gender and type of sport. This indicates that any total SPQ score differences between contact and collision sport athletes were not dependent on the gender identified with by the participants, and any total SPQ score differences between male and female athletes were not dependent upon which type of sport they played. Statistical analyses regarding the division level of participants were not part of the researcher’s original research questions. However, since data was collected from athletes in all three NCAA division levels, additional statistical analyses were conducted to explore possible differences among the dependent variables. There was a statistically significant effect of total CAAS score among NCAA Division level [F(2, 236) = 4.96, p = .008, η2 = .040] (see Table D1). Post hoc comparisons using the Tukey HSD test provided evidence to suggest that the mean total CAAS score for Division I athletes (M = 54.74, SD = 19.21) was significantly higher than Division III athletes (M = 47.11, SD = 14.36), but not Division II (M = 53.13, SD = 17.94) athletes (see Table D2). One-way, between subjects ANOVAs were conducted to compare scores on the CAAS Anger and Aggressiveness subscales among NCAA Division level. There was a statistically significant effect of CAAS Anger subscale scores among NCAA Division level [F(2, 240) = AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 26 5.48, p = .005, η2 = .044] (see Table D3). Post hoc comparisons were conducted using Tukey’s HSD test (Field, 2009). The results of this analysis provided support for the interpretation that the mean CAAS Anger subscale score for Division I athletes (M = 27.68, SD = 8.66) was significantly higher than Division III athletes (M = 23.98, SD = 6.94), but not statistically different from Division II (M = 27.01, SD = 8.60) athletes. Division II athletes were also found to score significantly higher than Division III athletes on CAAS Anger subscale scores (see Table D4). There was also a statistically significant effect for CAAS Aggressiveness subscale scores among NCAA Division level [F(2, 236) = 3.12, p = .046, η2 = .026] (see Table D5). Post hoc comparisons using Fisher’s LSD test (Field, 2009) indicated that Division I athletes (M = 27.16, SD = 12.50) scored significantly higher than Division III athletes (M = 23.05, SD = 9.79), but not Division II (M = 26.05, SD = 11.80) athletes (see Table D6). There were no statistically significant differences in total SPQ scores between NCAA division levels [F(1, 216) = .574, p = .564, η2 = .005] (see Table D7). One-way between subjects ANOVAs were conducted for all four provocation subscales to look for differences by NCAA division level. As displayed in Table D8, no significant differences were found by division level among any of the four provocation subscales. AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 27 Discussion The primary goal of this study was to investigate and better understand competitive aggressiveness, anger, and the experience of provocation in collegiate sport athletes. In particular, it was important to understand if these variables differed among male and female contact and collision sport athletes, and if any further differences occurred among NCAA division level. Both male and female collegiate athletes participating in contact and collision sports were surveyed electronically using questionnaires that assessed the variables of competitive aggressiveness and anger, and the experience of provocation. The two hypotheses proposed at the beginning of the study were that: 1) male athletes would score higher on the CAAS anger and aggressiveness subscales, and would report experiencing (and responding negatively to) more provocation than female athletes; and 2) collision sport athletes would score higher on the CAAS anger and aggressiveness subscales, and would report experiencing more provocation and more frequently responding to provocation than contact athletes. Competitive Aggressiveness and Anger Gender comparison. Based on the results of the current study, the first hypothesis was partially supported. Male collegiate athletes scored significantly higher overall on the CAAS than female athletes, and they were significantly more likely to tolerate aggressiveness and be inclined to aggress in an athletic setting. However, while male athletes scored slightly higher on competitive anger, this difference was not statistically significant. These findings point to the notion that the amount of anger felt during competitive sports was not significantly different based on gender. Some researchers have suggested that males are more prone to anger than females (e.g., Maxwell & Moores, 2007; Maxwell, Visek, & Moores, 2009). However, the results of the current study suggest that the female athletes in these types of sports may simply be AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 28 less likely to act on anger than male athletes. For example, female athletes were found to have significantly higher anger levels from provocation by opponents, but males had more negative and intense responses to the same types of provocative behavior. This finding seems to be in disagreement with some previous research on high school tennis athletes who reported that male and females tended to cope with anger in similar ways (Bolgar, Janelle, & Giacobbi, 2008). The notion that male athletes are, in general, more inclined to aggress than female athletes has been suggested in previous literature (e.g., Bredemeier, 1978; Coulomb-Cabagno & Rascle, 2005; Maxwell, 2004). Even at the middle school level, some male athletes displayed significantly more aggression off the field than female athletes, with participation in sport being a risk factor for antisocial behavior (Burton & Marshall, 2005). Further, during the development of the CAAS questionnaire, the authors found that male CAAS scores were higher than female scores on both the Anger and Aggressiveness subscales (Maxwell & Moores, 2007). This result was consistent for both contact and non-contact sport athletes. On the other hand, not all researchers have found evidence to support the classic aggressive male athlete stereotype. For example, Keeler (2007) found that males and females did not differ in hostile or instrumental sport aggression, and this finding was consistent among non-contact, contact, and collision sport athletes. However, males did score higher on questions assessing life assertion and assault aggression. Overall, the finding that male athletes (regardless of sport type) displayed more competitive aggressiveness is in agreement with most of the previous research on gender differences in aggressive behavior. The results of the current study parallel a number of findings from previous research studies (Burton & Marshall, 2005; Coulomb-Cabagno & Rascle, 2006; Gardner & Janelle, 2002). One example is males reporting that they were more inclined to aggress than female athletes, AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 29 regardless of what type of sport they played. However, unlike research conducted in the creation of the CAAS (Maxwell & Moores, 2007), the current findings support the idea that male and female college athletes are not significantly different in the amount of anger experienced in competitive environments. It should be noted that Maxwell and Moores (2007) also utilized participants from non-contact sports. Therefore, the current study is unique in that it is the first known study to explore competitive aggressiveness and anger differences between only contact and collision sport athletes. It is important to differentiate these types of sports from non-contact ones, since contact and collision sport athletes compete as members of teams, in environments that produce consistent physical contact with opponents. The finding that males participating in contact and collision sports reported higher competitive aggressiveness could have important implications for educational programs, such as ones that focus on anger management skills. Aggression has been shown numerous times to be a possible byproduct of anger, especially when anger is unable to be controlled (e.g., Feindler & Ecton, 1994; Maxwell, Visek, & Moores, 2009; Robazza et al., 2006). While the male and female athletes in the current study experienced similar levels of anger during competition, males said that they would be more inclined to justify aggressive behavior as a means of dealing with that anger. It appears that male athletes might benefit more from resources intended to teach athletes other ways to deal with competitive anger, especially under the stressful conditions seen in sport competition. Sport type comparison. The second hypothesis was supported based on the findings of the current study. Collision sport athletes were found to have significantly higher competitive aggressiveness and anger than contact sport athletes. This finding was consistent irrespective of gender. What seems to be one of the clearest predictors of competitive aggressiveness and anger AGGRESSIVENESS, ANGER, AND PROVOCATION IN SPORT 30 is the type of sport an athlete plays. Although all sports involved in the current study featured contact between opponents, the key difference between collision and contact sports is that the latter allows in-game contact, but extreme contact or direct collisions are not implicit (or required) by the written rules of the sport (Keeler, 2007; Silva, 1983). In contrast, collision sports generally involve high-speed collisions as an integral part of the sport. Simply put, they are necessary to achieve appropriate goals needed for success. A few previous studies have produced findings that are relevant to the sport type differences found in the current study. In part

Being Mindful of Perfectionism and Performance Among Athletes in a Judged Sport Being Mindful of Perfectionism and Performance Among Athletes in a Judged Sport Erika D. Van Dyke edv0001@mix.wvu.edu Follow this and additional works at: https://researchrepository.wvu.edu/etd Part of the Other Psychology Commons Recommended Citation Van Dyke, Erika D., "Being Mindful of Perfectionism and Performance Among Athletes in a Judged Sport" (2019). Graduate Theses, Dissertations, and Problem Reports. 7428. https://researchrepository.wvu.edu/etd/7428 This Dissertation is protected by copyright and/or related rights. It has been brought to you by the The Research Repository @ WVU with permission from the rights-holder(s). You are free to use this Dissertation in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you must obtain permission from the rights-holder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/ or on the work itself. This Dissertation has been accepted for inclusion in WVU Graduate Theses, Dissertations, and Problem Reports collection by an authorized administrator of The Research Repository @ WVU. For more information, please contact researchrepository@mail.wvu.edu. Being Mindful of Perfectionism and Performance Among Athletes in a Judged Sport Erika D. Van Dyke Dissertation submitted to the College of Physical Activity and Sport Sciences at West Virginia University in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Sport, Exercise, and Performance Psychology Sam J. Zizzi, Ed.D., Chair Scott Barnicle, Ph.D. Edward F. Etzel, Ed.D. Aaron Metzger, Ph.D. Department of Sport Sciences Morgantown, West Virginia 2019 Keywords: mindfulness, perfectionism, performance, personality, elite athletes, sport psychology Copyright 2019 Erika D. Van Dyke ABSTRACT Being Mindful of Perfectionism and Performance Among Athletes in a Judged Sport Erika D. Van Dyke Literature pertaining to mindfulness and perfectionism in sport has expanded greatly in recent years. However, little research has integrated mindfulness and perfectionism, particularly within sports where athletes are judged on performance to a standard of perfection. The current study had two primary aims: (1) to explore profiles of mindfulness and perfectionism among intercollegiate gymnasts through a person-centered approach, and (2) to analyze differences in objective performance measures across the resulting profiles. The analytic sample consisted of 244 NCAA gymnasts representing NCAA Division I, II, and III institutions. Gymnasts completed self-report measures of mindfulness and perfectionism. Competitive performance records (i.e., national qualifying scores) were then gathered for participating gymnasts. Cluster analyses revealed a three-cluster solution: a moderate mindfulness, high perfectionism profile; a low mindfulness, low/moderate perfectionism profile; and a high mindfulness, very low perfectionism profile. Although competitive performance differences were not observed among the three profiles, exploratory post hoc pairwise comparisons indicated potential performance differences on vault and bars. Interestingly, gymnasts in different profiles performed more favorably on each event. Small to moderate effect size estimates provide some evidence that perfectionism may be adaptive to gymnastics performance. Elite level gymnasts were represented across three distinct profiles, suggesting that more than one profile of characteristics may be adaptive for reaching high levels of performance. Further, the sport context might be considered when interpreting the practical significance of the findings. The results can be used to help coaches, researchers, and practitioners better understand how mindfulness and perfectionism are expressed among athletes in a judged sport, and how these tendencies may be impactful in different ways. Future research exploring determinants of performance and mental health concurrently could provide further understanding of whether the characteristics that facilitate performance are congruent with those that facilitate wellbeing. BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE iii Acknowledgements Many people have crossed the path of my life during this project, and I will be forever grateful for the indelible footprints they have left there. Some of those people have simply left deeper imprints than others. These words acknowledge my gratitude for your presence on my journey. I would like to share an immense amount of appreciation for my advisor, Dr. Sam Zizzi. Thank you for extending me an invitation to join this esteemed doctoral program. Your supportive guidance and mentorship throughout this climb up research mountain has been invaluable, and has allowed me to grow as a scholar and more importantly as a person. Thank you for always inviting my curiosity, for your patience with my “thorough” process, for your white board check boxes of accountability, and for your gentle nudges to step back and get some perspective every so often. You have a remarkable way of seeing each of your students for who they are as learners. Thank you for seeing me. You have helped me to embrace the value in letting go, in imperfection, and in embracing my sunshine. Thank you for walking every step of the path along with me. The view from the top of this climb is spectacular. I would also like to thank Dr. Aaron Metzger for his incredible knowledge of the world of multivariate statistics. You provided the foundational learning that inspired many of the statistical directions taken throughout the course of this research project. Thank you for challenging me to explore interesting and complex questions, for making statistics accessible, and for giving me the skills and confidence necessary to carry out the analyses contained within these pages. I so appreciate you joining me for this glimpse into the experiences of athletes. My dissertation committee members, Dr. Etzel and Dr. Barnicle, have been such wonderful sources of support throughout this project and more broadly throughout my time here in the halls of CPASS. Thank you, Dr. Etzel , for greeting me each day with, “Ah little miss sunshine.” Your endearing reminders to “be well, and do good work,” to “walk between the raindrops,” and to know that “we’ll keep the light on for you” always made me smile and feel a valued member of our learning community. Your lovely words of wisdom and encouragement have and continue to mean so much to me. I am grateful to have been among the many students whose lives you have touched. Thank you, Dr. Barnicle, for always keeping your door open to my many many questions – often multiple in a given day. You have been such a supportive mentor, both in this project and in my growth as a teacher and consultant. I appreciate you being there for me throughout this learning journey. I am forever grateful that Dr. Zizzi crossed our paths, Candice (Clay) Brown. Thank you so incredibly much for the generous time and energy that you devoted to helping with my research project. From thoughtfully entering and checking data, to playing with statistical analyses, to reading drafts of the document, to presenting a poster together during CPASS research day. Your enthusiasm, dedication, and desire to learn and grow is inspiring, and I appreciate you lending some of your sparkle to our collaboration. Your presence throughout this project has been a blessing, and has brought me the joy of beginning my journey as a mentor. Thank you for your support. I am so excited to see what your very bright future will hold. BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE iv Thank you to all of the faculty in our Sport, Exercise, and Performance Psychology program for your belief in me, and for giving me the opportunity to pursue this path. One of the things that drew me here to WVU was the learning community cultivated by faculty and embraced by students in our program. I appreciate the legacy that you have built, and am so glad to have had the opportunity to be a part of this place. To my SEPP family. Thank you for your endless support, encouragement, smiles, and hugs throughout this journey, especially on days when the process felt daunting. A special note of appreciation for my cohort members, Adam, Carra, and Seth. What an amazing group of people with whom to share this experience. I am so grateful to have created so many memories with each of you – thank you for touching my life. I will continue to do my best to supply the sunshine and rainbows. A very special thank you must be extended to the roommates who have helped make this place feel like home during these past four years. Tammy, you led the way and I can only hope to follow in your footsteps to become a real professor someday. Carra, I am beyond grateful to be doing this journey along with you. Thank you for sharing all the laughs, tears, and moments of growth with me. I will forever remember our road trip to New York just after our first semester as doctoral students, and making a pact to do this thing together all the way through. We are so close now #HancockPact. Matt and Jordan (and Hunter), thank you for welcoming me into your little family these past three years, and for making Morgantown feel a little more like Northern California. I love you all. Thank you to my partner, Ben, for his love, laughter, and support. What a ride this has been! Whether living together or at a distance, your belief in me has shaped the course of this journey in a beautiful way. I appreciate you for your love of learning, endless curiosity, and for always being there by my side to go chasing waterfalls. Here’s to the adventure ahead. On a final note, to the people who gave me life, who instilled in me a joy of learning, and who have been my foundation through it all – my parents, Ivan and Anne Marie. I appreciate your unconditional love and support of my aspirations more than these simple words can express. Thank you for always believing that I can accomplish anything I set my mind and heart toward. You two are the best cheerleaders and consultants a daughter could ever wish for. I am so lucky you picked me. “And now that you don’t have to be perfect, you can be good.” – John Steinbeck BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE v Table of Contents Introduction…………………………………………………………………………….………….1 Pilot Study…………………………………………………………………………………………7 Method……………………………………………………………………………………….……8 Research Design and Sampling……………………………………………………………8 Instruments………………………………………………………………………………...8 Mindfulness……………………………………………………………………….8 Perfectionism………………………………………………………………….…...9 Demographic Questionnaire……………………………………………………...10 Competitive Gymnastics Performance…………………………………………...10 Procedures……………………………………………………………………………...…11 Statistical Analyses……………………………………………………………………….11 Results……………………………………………………………………………………………13 Determining the Analytic Sample………………………………………………………13 Descriptive Statistics on the Analytic Sample………………………………………….14 Cluster Interpretation…………………………………………………………………..15 Comparing Performance Across Clusters………………………………………………16 Discussion………………………………………………………………………………………..17 Tables and Figures………………………………………………………………………………..27 Literature Review……………………………………………………………………….………..31 Mindfulness: A Brief Backdrop………………………………………………………….31 Historical Roots…………………………………………………………………..32 Mindfulness-Based Approaches……………………………………………….....33 BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE vi Mindfulness in Sport and Performance Psychology…………………………………….34 Mindfulness-Based Approaches in Sport………………………………………..35 Linking Mindfulness-Based and Traditional PST Approaches…………………37 Mindfulness, Performance, and Psychological Aspects of Sport……………….39 Perfectionism in Sport and Performance Psychology…………………………………..56 Measurement……………………………………………………………………………66 Mindfulness………………………………………………………………….….66 Perfectionism…………………………………………………………………….70 Performance……………………………………………………………………...75 Directions for Future Research……………………………………………………..........77 References………………………………………………………………………………………..82 Table 1: Mindfulness Measurements…………………………………………………………….95 Table 2: Perfectionism Measurements…………………………………………………………...96 Table 3: Adapted Mindfulness-Flow-Performance Model in Sport………………………………97 Appendix A: Athlete Mindfulness Questionnaire………………………………………………..98 Appendix B: Sport Multidimensional Perfectionism Scale-2…………………………………...100 Appendix C: Demographic Questionnaire……………………………………………………...102 Appendix D: Email to Gymnastics Coaches…………………………………………………….104 Appendix E: Cover Letter and Informed Consent……………………………………………….105 Appendix F: IRB Approval……………………………………………………………………..106 BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 1 Introduction Researchers studying mindfulness and acceptance-based evidence among athletes support a cautious yet optimistic view regarding the efficacy of such approaches in the context of sport (e.g., McAlarnen & Longshore, 2017; Noetel, Ciarrochi, Van Zanden, & Lonsdale, 2017; Sappington & Longshore, 2015). In a recent systematic review, Noetel et al. (2017) analyzed over 60 studies of mindfulness and acceptance-based approaches intended to promote positive sport outcomes, including athletic performance. Despite finding large effect sizes for the performance benefits of such interventions, the findings were deemed low in quality, lacking precision in effect sizes and consistency. Among the individual studies reviewed, researchers found preliminary support for mindfulness and acceptance-based interventions across a variety of sport outcomes (e.g., performance, flow, present-moment awareness, confidence, injury prevention, competitive anxiety, and burnout). Continued research efforts with increased rigor are thus needed to support mindfulness as an approach for enhancing sport performance and related outcomes. At their core, mindfulness and acceptance-based approaches focus on modifying the relationship one has with internal experiences (e.g., physical sensations, emotions, cognitions), rather than deliberately aiming to change, consciously control, suppress, or reduce internal experiences (e.g., Gardner & Moore, 2004, 2007; Hayes, Strosahl, & Wilson, 1999; Kabat-Zinn, 1982). Such mindfulness approaches cultivate present-focused awareness and attention, a nonjudgmental and accepting approach to situations, openness and curiosity toward experience, and compassion for self and others – elements that comprise the flavor of mindfulness (Zizzi, 2017). Recognizing the applicability of mindfulness-based approaches to the context of sport, BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 2 researchers examined the link between mindfulness and objective measures of sport performance using a variety of study designs. In support of a mindful approach to facilitating sport performance, researchers found that a greater number of athletes who engaged in a mindfulness and acceptance-based program improved their national performance ranking compared to those who took part in a traditional change-based program (Bernier, Thienot, Codron, & Fournier, 2009). Authors of another study found that elite shooters in a mindfulness meditation group experienced significant increases in shooting performance (i.e., mean performance score increase from 528 to 544, SD = 13) and significant decreases in pre-competition anxiety (i.e., mean salivary cortisol level decrease from 1.33 to 0.66, SD = 0.07) from pre- to post-test compared to a control group (John, Verma, & Khanna, 2011). In a non-intervention study, Gooding and Gardner (2009) found that collegiate athletes’ levels of mindfulness significantly predicted basketball free throw shooting percentage in games across the competitive season (i.e., one standard deviation increase in mindfulness scores resulted in a 5.75% increase in free throw shooting percentage). When competitive experience was controlled for, however, mindfulness no longer arose as a significant predictor of competitive performance. Gooding and Gardner noted that competitive experience and mindfulness may predict sport performance through shared variance. Taken together, researchers suggest that mindfulness may influence objectively measured performance in sport among high level athletes. Further research may provide additional clarity regarding the utility of mindfulness for real-world competitive performance. As mindfulness research continues to evolve, studies that take a more nuanced approach to studying the mindfulness-performance relationship are needed. These kinds of studies can clarify how, when, and by whom mindfulness could be most useful. In a sport like gymnastics BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 3 for instance, in which athletes are judged to a standard of perfection in their skills and technique, perfectionism may be considered contextually relevant to the study of mindfulness-performance relationships. Thus, the study of mindfulness and perfectionism among judged sport athletes may provide more nuanced insights regarding how these constructs are experienced together among individuals, and how those unique experiences may be related to individual differences in sport performance. Perfectionism has been defined as “a personality disposition characterized by striving for flawlessness and setting exceedingly high standards for performance, accompanied by tendencies for overly critical evaluations” (Stoeber, 2012, p. 294). Although different frameworks of perfectionism have been proposed in the literature (e.g., Frost, Marten, Lahart, & Rosenblate, 1990; Hewitt & Flett, 1991), researchers acknowledge that perfectionism is a multidimensional construct. Stoeber and Otto (2006) provided a way to conceptually integrate different proposed frameworks based on two higher-order dimensions of perfectionism – perfectionistic strivings and perfectionistic concerns. Although a point of some debate among perfectionism researchers in recent years (e.g., Flett & Hewitt, 2005), perfectionistic strivings have often been considered adaptive and facilitative of performance, whereas perfectionistic concerns have often been considered maladaptive and debilitative of performance in sport (e.g., Gotwals, Stoeber, Dunn & Stoll, 2012; Stoeber, 2012). In a recent meta-analytic review of multidimensional perfectionism in sport, the researchers further highlighted the complexity of these relationships, noting that perfectionistic concerns seem to be clearly maladaptive, while perfectionistic strivings may be adaptive or maladaptive for athletes (Hill, Mallinson-Howard, & Jowett, 2018). Considering potential contrasts between elements of perfectionism (e.g., self-critical evaluations) and elements of mindfulness (e.g., acceptance and self-compassion), further research integrating the BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 4 two constructs is needed to understand how mindfulness and perfectionism may interact in athletes’ experiences. Many researchers have examined relationships between perfectionism and competitive sport performance among high level athletes (e.g., Gotwals et al., 2012; Hill et al., 2018). Relatively few researchers, however, have explored the intersection of mindfulness and perfectionism in sport. In their follow-up study of the long-term impact of mindfulness-based programming for sport performance, Thompson, Kaufman, De Petrillo, Glass, and Arnkoff (2011) found significant performance improvements in long-distance runners’ mile times from pre- and posttest to follow-up. In addition, the authors found negative associations between performance improvements and aspects of perfectionism, including overall trait perfectionism (r = .74), concern over mistakes (r = .69), and doubts about actions (r = .75). It is important to note that negative relationships are reflected in the positive correlations reported because performance improvement is measured through decreased mile time. Although the links between mindfulness, perfectionism, and performance should be interpreted with care due to the correlational nature of the study, Thompson et al. (2011) support the notion that mindfulness may be related to performance benefits, and that certain dimensions of perfectionism may negatively influence athletic performance. A recent critical evaluation of mindfulness research has raised questions regarding the varied definitions and measurements of mindfulness found in the literature, as well as the proposed, seemingly unquestioned, benefits of mindfulness without regard for potential adverse effects (Van Dam et al., 2018). Rather than leaping with naïve enthusiasm into the application of mindfulness interventions within a new population, researchers might first aim to understand the typical mindfulness experiences of those athletes. Taking a person-centered analytic approach to BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 5 the study of mindfulness may help bring that explicit attention to salient features of mindfulness among athletes in a specific sport setting. Further, new insights gained about the athletes’ mindfulness experiences will be highly influenced by the specific core concepts measured in the selected instruments. Considering the work of Van Dam et al. (2018), researchers are encouraged to clearly define the flavor(s) of mindfulness assessed to enhance interpretability of future research findings. Person-centered approaches to data analysis allow the researcher to better understand unique profiles of the key constructs measured among individuals. Although person-centered approaches have been used in the study of mindfulness (e.g., Kee & Wang, 2008) and perfectionism (e.g., Gucciardi, Mahoney, Jalleh, Donovan, & Parkes, 2012), these constructs have yet to be studied concurrently through cluster analytic approaches. In their person-centered approach to the study of mindfulness in sport, Kee and Wang (2008) identified a four-cluster solution based on university athletes’ mindfulness scores (Mindfulness/Mindlessness Scale, MMS; Bodner & Langer, 2001). Individuals in the profile highest in mindfulness showed the most frequent use of psychological skills in sport. Specifically, athletes in the cluster highest in mindfulness had significantly higher goal setting, positive self-talk, and imagery compared to those in clusters lower in mindfulness characteristics. In addition, the researchers found significant differences in flow dispositions across the four mindfulness clusters. Thus, Kee and Wang identified a stable mindfulness cluster solution, and found significant differences among those mindfulness profiles on the outcome variables of psychological skill use and flow dispositions. Along this line of person-centered research, Gucciardi et al. (2012) explored profiles of perfectionism within a heterogeneous sample of elite athletes through a cluster analytic BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 6 approach. The researchers found three distinct profiles of perfectionism among athletes based on the Sport Multidimensional Perfectionism Scale (Sport-MPS; Dunn, Causgrove Dunn, & Syrotuik, 2002): (1) adaptive perfectionists – high personal standards, low concern over mistakes, moderate perceived parent/coach pressures, (2) maladaptive perfectionists – high concern over mistakes and perceived parent/coach pressures, moderate/high personal standards, and (3) non-perfectionists – low personal standards and concern over mistakes, moderate perceived parent/coach pressures. Gucciardi et al. further revealed significant differences in motivational orientations among the perfectionism profiles. Specifically, adaptive perfectionists reported significantly lower levels of fear of failure, performance approach and avoidance goals, and mastery avoidance goals, and significantly higher levels of mastery approach goals than did maladaptive perfectionists. Non-perfectionists reported significantly lower levels of the motivational orientations assessed than did maladaptive perfectionists, and lower levels of mastery approach goals, performance approach goals, and intrinsic motivation than did adaptive perfectionists. The researchers thus supported a stable three cluster conceptualization of perfectionism, and found differences in motivational outcomes across those perfectionism profiles. Gucciardi et al. highlighted that among these elite athletes both adaptive and maladaptive perfectionists had high levels of personal standards, and that it was primarily the presence or absence of overly critical self-evaluations that differentiated maladaptive from adaptive perfectionists, respectively. Many existing studies that have examined mindfulness and links to performance outcomes have done so following programming and interventions (e.g., John et al., 2011; Thompson et al., 2011). Little research has explored athletes’ typical tendencies toward mindfulness and perfectionism qualities, and how together these characteristics may relate to BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 7 performance in unique ways. The current study will thus explore mindfulness, perfectionism, and performance among gymnasts – athletes in a judged sport. Aims of the research will be twofold: (1) to examine whether unique profiles of mindfulness and perfectionism constructs exist among the athlete participants, and (2) to assess whether objective measures of competitive performance differ across the unique mindfulness and perfectionism profiles. Pilot Study The purpose of the pilot study was to assess the psychometric properties of mindfulness and perfectionism measures, and to explore relationships between mindfulness and perfectionism among intercollegiate gymnasts. Participants were female gymnasts (N = 301), ranging in age from 18 to 22 years (M = 19.46, SD = 1.20), who attended NCAA Division I, II, or III colleges and universities in the United States. Gymnasts completed the Athlete Mindfulness Questionnaire (AMQ; Zhang, Chung, & Si, 2017), and the personal standards and concern over mistakes subscales of the Sport Multidimensional Perfectionism Scale-2 (i.e., Sport-MPS-2; Gotwals & Dunn, 2009). Results of the correlational analyses supported theoretically expected associations among constructs (e.g., present-moment attention and awareness, r = .62; acceptance and concern over mistakes, r = -.41), and internal reliability coefficients across the mindfulness and perfectionism subscales ranged from .74 to .88. Confirmatory factor analyses supported the original three-factor structure of the AMQ [RMSEA = .06, SRMR = .05, CFI = .92]. The two-factor perfectionism model did not show good fit to the data. Modification indices were reviewed to evaluate potential model fit improvements. When residual error terms of items in the concern over mistakes factor were allowed to covary, the two-factor model fit improved markedly [RMSEA = .08, SRMR = .08, CFI = .91]. Through the pilot study, the research team supported the use of the AMQ among intercollegiate level gymnasts, and provided further BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 8 understanding about relationships between mindfulness and perfectionism among athletes in a judged sport context. Research Design and Sampling Method The current study built upon the pilot study to explore mindfulness, perfectionism, and performance using a quantitative, descriptive correlational, research design. Female gymnasts 18 years of age or older attending National Collegiate Athletic Association (NCAA) Division I, II, or III colleges and universities in the United States who took part in the pilot study also participated in the present study. Prior to the pilot study, convenience sampling was used to contact all NCAA collegiate women’s gymnastics coaches with available contact information to seek permission to collect data with their teams. Gymnasts who previously completed the survey and reported their name were included in the first part of the study exploring mindfulness and perfectionism profiles. Participants who performed on at least one event during the 2019 competition season from January to April, and for whom a National Qualifying Score (NQS) could be calculated, were included in the second part of the study assessing performance differences among the resulting profiles. Instruments Mindfulness. The Athlete Mindfulness Questionnaire (AMQ; Zhang et al., 2017) was used to measure mindfulness in the current study. The AMQ is a 16-item, 3-factor measure of mindfulness for athletes. Mindfulness is assessed based on the subscales present moment attention (e.g., When I find myself distracted, I gently bring my attention back to my training), awareness (e.g., I am aware that my emotions during training and competition can influence my thinking and behavior), and acceptance (e.g., During training and competition, it doesn’t matter BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 9 if the situation is good or bad, I can accept myself for who I am). Items are rated on 5-point Likert scales ranging from 1 (never true) to 5 (always true). Confirmatory factor analysis (CFA) revealed satisfactory fit indices for the 16-item, 3-factor structure of the instrument, X2(101) = 221.28, p < .001, CFI = 0.95, TLI = 0.94, WRMR = 1.04, RMSEA = 0.06. Internal consistency reliabilities for the three AMQ subscales ranged from 0.64 to 0.76. In the present study, internal consistency reliabilities for the subscales were slightly higher, ranging from 0.75 to 0.77. Convergent validity for the AMQ was supported through significant positive associations between the present moment attention, awareness, and acceptance subscales of the AMQ and mindfulness as measured by the Mindful Attention Awareness Scale (MAAS; Brown & Ryan 2003). Concurrent validity for the three subscales of the AMQ was also supported through significant negative relationships with burnout and experiential avoidance, and significant positive relationships with well-being, positive affect, and dispositional flow. Perfectionism. The full version of the Sport Multidimensional Perfectionism Scale-2 (Sport-MPS-2; Gotwals & Dunn, 2009; Gotwals, Dunn, Causgrove Dunn, & Gamache, 2010) is a 42-item, 6-factor measure assessing the multidimensional nature of perfectionism in sport. The subscale dimensions include personal standards, concern over mistakes, perceived parental pressure, perceived coach pressure, doubts about actions, and organization. Items are rated on 5 point Likert scales ranging from 1 (strongly disagree) to 5 (strongly agree). Athletes are asked to report how they “view certain aspects of their competitive experiences in sport.” For the purpose of the present study, two subscales, namely personal standards (e.g., It is important to me that I be thoroughly competent in everything I do in my sport) and concern over mistakes (e.g., I should be upset if I make a mistake in competition), were used to measure the two higher-order constructs of perfectionistic strivings and perfectionistic concerns, respectively. The personal BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 10 standards and concern over mistakes subscales were selected because they have been recommended as indicators of perfectionistic strivings and perfectionistic concerns in sport (Stoeber & Madigan, 2016). The reliability of the Sport-MPS-2 has been demonstrated among athletes, with internal consistencies of .74 and .79 for the personal standards and concern over mistakes subscales, respectively (Gotwals & Dunn, 2009). In the current study, internal consistency reliabilities for the personal standards and concern over mistakes subscales were .77 and .88, respectively. Demographic questionnaire. The demographic questionnaire assessed participants’ age, highest level in gymnastics attained before college, race, and ethnicity. Gymnast participants were asked to report their name, and the college or university they attend so the research team could access their publicly available competition scores from an online platform. Experience and satisfaction working with a sport psychology professional, as well as experience with mindfulness, were also assessed. All identifiable information was held confidential, and all data gathered for the study was reported in aggregate to protect the anonymity of participants. Competitive gymnastics performance. Measurement of competitive gymnastics performance was based on the National Qualifying Score (NQS). The NQS is used in collegiate gymnastics to determine placement in post-season competition, and is calculated based on the following criteria: (1) three highest away scores on a given event, plus (2) next three highest scores on a given event, whether home or away, (3) drop the highest of the six scores, (4) average the remaining five scores. An NQS was calculated for each gymnast who participated in the study for each event on which she competed during the regular meet season to allow for comparison of mindfulness – perfectionism – performance relationships across events (i.e., vault, uneven bars, balance beam, floor exercise). BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 11 Procedures After gaining approval from the Institutional Review Board (IRB) to conduct the research methods necessary for both the pilot and current studies, the researcher contacted college gymnastics coaches through email correspondence to request permission to collect data with their athletes. Coaches had the option to receive either paper copies of the counterbalanced questionnaires via mail, or a Qualtrics link to an online version of the questionnaires via email. Coaches then made the surveys available to their athletes to complete on a voluntary basis. All athletes receiving the survey were initially presented with a cover letter description of the study, and were asked to provide their consent to participate. Survey data were collected prior to, or in the beginning of, the competition season for each participant. All data were reported in aggregate, and any identifying information collected in the surveys was used for the sole purpose of accessing the gymnasts’ publicly available competitive performance data. Event scores ranging from 0.00 to 10.00 were retrieved online post-season from https://roadtonationals.com/results/standings/ for gymnasts who completed the questionnaires and who performed in a sufficient number of competitions throughout the season to have an NQS on at least one event. Statistical Analyses For the pilot study, data cleaning and preliminary analyses were conducted and reviewed to determine whether necessary assumptions for the substantive analyses were met. Missing values across the mindfulness and perfectionism items were assessed using Little’s MCAR test (p = .769), and no single item exceeded 1.3% missing data. Due to the low number and random nature of missing values, Expectation-Maximization (EM) procedures were then used to impute missing values. As expected, the gymnastics performance data on each of the four events were BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 12 negatively skewed. Reflection and log base 10 transformation approaches improved the distribution of scores for use in later parametric statistical analyses. For the current analytic sample, descriptive statistics were calculated on demographic and key study variables. Internal consistency reliabilities were also assessed for the measures, as were correlational analyses for the performance data and each of the subscales in the mindfulness and perfectionism instruments. For the current study, cluster analytic approaches were conducted to establish whether unique profiles of mindfulness and perfectionism were present among the gymnast participants. Gymnasts’ scores on the three mindfulness and two perfectionism subscales were submitted to cluster analysis in a two-step procedure: (1) Ward’s hierarchical cluster analysis with squared Euclidean distance was conducted to help determine an initial number of clusters present among the participants, and (2) k-means iterative cluster analysis was used to further refine the cluster solution suggested by the initial hierarchical cluster analysis. The use of both hierarchical and iterative approaches to cluster analysis is supported in the literature (e.g., Gucciardi et al., 2012; Hair, Anderson, Tatham, & Black, 1998; Kee & Wang, 2008). A series of chi square analyses were then carried out to assess the number of athletes in each cluster who performed on each gymnastics event. This step allowed the research team to determine whether a sufficient sample size for each cluster/profile was met prior to conducting subsequent analyses. One-way analysis of variance (ANOVA) was then used to assess differences among the resulting mindfulness/perfectionism clusters in an objective measure of gymnastics performance (i.e., NQS) on each competitive event. Thus, four one-way ANOVAs were conducted to examine competitive performance differences across the clusters on each gymnastics event (i.e., vault, uneven bars, balance beam, floor exercise). Effect size estimates are reported as partial eta BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 13 squared for the ANOVA models, and as Cohen’s d for pairwise mean comparisons. All statistical analyses were computed in recent versions of SPSS. Results Of the total number of participants who completed the mindfulness and perfectionism survey measures (N = 301), 244 gymnasts provided their name. It was only possible to access competition results for athletes who provided their names. Thus, the analytic sample for the current study was 244 gymnasts. Determining the Analytic Sample Prior to conducting the substantive analyses for the study, the research team conducted a series of preliminary analyses to assess potential differences between participants who would be retained in the analytic sample (n = 244) and those who would be omitted from the sample (n = 57) on demographic and key study variables. T-tests indicated no statistically significant (p > .05) differences between the gymnasts on the three mindfulness subscales. Statistically significant (p < .05) differences were found, however, between the participants on the two perfectionism subscales. Gymnasts who did not report their name indicated slightly higher perfectionism scores than those who did report their name for both concern over mistakes (no name: M = 3.18, SD = 0.78; name: M = 2.87, SD = 0.82) and personal standards (no name: M = 3.88, SD = 0.55; name: M = 3.61, SD = 0.58) subscales. Gymnasts who did not report their name were also slightly higher in skill level than the larger group of participants who did provide their name (mean difference = 0.22). Given these differences, cluster analyses were conducted for both the full (N = 301) and analytic (N = 244) samples. Chi square analyses were then assessed to determine the proportion of athletes in each cluster who did and did not report their name. Although gymnasts who did not BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 14 provide their name were disproportionately found in clusters high in perfectionism dimensions, parallel to the findings of the t-tests, the resulting cluster solutions were similar between the two samples, indicating that the gymnasts who omitted their name were likely not driving the cluster solution. The research team thus decided to move forward in reporting the cluster solution established with the analytic sample of gymnasts who provided their name (N = 244), and who would be included in the subsequent analyses incorporating performance data. Descriptive Statistics on the Analytic Sample Demographic information for the analytic sample of collegiate gymnasts is presented in Table 1. Gymnasts in the present study ranged in age from 18 to 22 years (M = 19.46, SD = 1.22) and were predominantly white (n = 196). A majority of the gymnasts reached level 10 prior to college (n = 204), had previous experience with a sport psychology professional (n = 162) and were satisfied with their experience (n = 130), and came into the study with no prior experience with mindfulness (n = 150). Correlations, descriptive statistics, and internal consistency coefficients for the mindfulness and perfectionism subscale scores are outlined in Table 2. As expected, statistically significant (p < .01) positive correlations arose among the three mindfulness subscales, and between the two perfectionism subscales. Significant, weak positive correlations were also found between personal standards perfectionism and both present moment attention (r = .28) and awareness (r = .16); yet there was no relationship between personal standards and acceptance (r < .01). Significant negative correlations arose between concern over mistakes perfectionism and each of the mindfulness subscales, though only one was moderate in size: present moment attention (r = -.14), awareness (r = -.15), and acceptance (r = -.42). The negative relationships between mindfulness dimensions and concern over mistakes perfectionism, as well as the BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 15 positive relationships between aspects of mindfulness and personal standards perfectionism, align well with previous research and theoretical perspectives of the constructs. Cluster Interpretation The five subscales were entered first into Ward’s hierarchical cluster analysis. Based on visual inspection of the resulting dendogram and graphed coefficients from the agglomeration schedule, a three- or five-cluster solution appeared to provide the best description of the data. Together, the dendogram and agglomeration schedule help indicate points at which dissimilar clusters were being forced to merge, and thus provide information to determine relatively distinct groupings of individuals. Centroid values from both the three- and five-cluster solutions were then taken forward to be used as initial seed points in the k-means iterative cluster analyses. The hierarchical and iterative cluster analytic approaches were then compared for both the three- and five-cluster solutions to assess the stability of the two solutions. Through crosstabulation, the percentage of cases similarly assigned to each cluster across the two analytic approaches could be assessed. Specifically, case classification for both the Ward’s and k-means analyses indicated 69% similarity for the three-cluster solution, compared to a slightly improved 73% similarity for the five-cluster solution. Despite a small increase in stability for the five cluster solution, power for subsequent statistical analyses would decrease notably given the smaller number of athletes in each group when moving from three- to five-clusters. The three cluster solution was therefore retained as it provided a nice explanation of gymnast mindfulness and perfectionism characteristics while permitting heightened power for subsequent analyses. Cluster means, standard deviations, and standardized scores for the final cluster solution are shown in Table 3. A visual representation of the final cluster solution is depicted in Figure 1. BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 16 Interpretation of the subscale means for gymnasts in each cluster revealed the presence of three distinct profiles of mindfulness and perfectionism tendencies. The first cluster consisted of 87 athletes (35.7%) with a moderate mindfulness and high perfectionism profile. The second cluster consisted of 71 athletes (29.1%) with a low mindfulness and low/moderate perfectionism profile. The third cluster consisted of 86 athletes (35.3%) with a high mindfulness and very low perfectionism profile. A series of four crosstabulation analyses were conducted to preliminarily assess the number of athletes in each profile who obtained an NQS on each competitive event during the season. Across the analyses, clusters ranged in size from 17 to 34 gymnasts. The group sizes were thus considered adequate for conducting subsequent one-way ANOVAs to assess potential performance differences across the three mindfulness and perfectionism profiles. Comparing Performance Across Clusters Prior to conducting parametric statistics using the performance data, transformations were made to improve the normality of the data. A series of four one-way ANOVAs were then computed using the transformed performance data to assess differences among the profiles. Event means, standard deviations, and sample sizes for each cluster are shown in Table 4. Results of the ANOVAs may be found in Table 5. No statistically significant (p < .05) differences in performance were found among the mindfulness and perfectionism profiles on the four competitive events. Effect sizes (h2 p) across the four analyses ranged from 0.03 to 0.06, and power estimates for this set of analyses was low. Exploratory post hoc t-tests were then conducted between groups with the greatest mean score differences on each event. The event NQS means compared, as well as the Cohen’s d effect size for each pairwise comparison, are indicated in Table 4. Significant mean score differences were found between clusters on vault and bars. On vault, the high mindfulness, very low BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 17 perfectionism cluster performed significantly better than the low mindfulness, low/moderate perfectionism cluster. On bars, the moderate mindfulness, high perfectionism cluster performed significantly better than the high mindfulness, very low perfectionism cluster. Small to moderate effect sizes were found for each of the NQS comparisons across the four events. Statistically significant correlations also arose between vault performance and acceptance (r = .24, p < .05), between bars performance and both personal standards (r = .31, p < .01) and concern over mistakes (r = .23, p = .05), between beam performance and personal standards (r = .23, p = .05), and between floor performance and awareness (r = .24, p < .05). Thus, despite the lack of significant findings when performance differences among the three profiles were considered together, potential relationships may exist between the mindfulness and perfectionism tendencies and competitive gymnastics performance. Discussion Three distinct profiles of mindfulness and perfectionism were observed among the gymnasts. Previous researchers have contributed to our understanding of how athletes may be grouped on each of these constructs independently (e.g., Gucciardi et al., 2012; Kee & Wang, 2008); however, this is the first study to our knowledge that used a cluster analytic approach to understand how athletes in a judged sport experience mindfulness and perfectionism together. Previously, researchers have supported stable three- and four- cluster solutions for perfectionism and mindfulness, respectively. Thus, arriving at a three-cluster solution that helps to explain gymnasts’ propensities for perfectionism and mindfulness concurrently aligns closely with existing notions of the constructs. Furthermore, the current finding that gymnasts were classified quite evenly across three profiles indicates that mindfulness and perfectionism may be experienced in varied ways even BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 18 within a relatively homogeneous group of elite athletes performing at a very high level. This gymnast-specific finding appears consistent with previous multi-sport research, as profiles of mindfulness and perfectionism tendencies have independently been found to vary markedly among high level athletes representing a broad range of sports (e.g., Gucciardi et al., 2012; Kee & Wang, 2008). Although exploring a diverse set of personality characteristics was beyond the scope of the present study, these findings could be used to support the idea that there may not be just one adaptive personality profile for attaining an elite level of gymnastics. Furthermore, a national qualifying score (i.e., successful and consistent performance across a season) was achieved by athletes with and without notable levels of perfectionism and mindfulness. When discussing differences observed across the mindfulness and perfectionism profiles, for instance gymnasts “high in mindfulness” or “low in perfectionism,” scores are considered relative to the other gymnasts who participated in the study rather than compared to some normative criteria. Still, a basic understanding of how the current participants compared on the measurements to athletes included in previous research can provide clarity and highlight points of similarity and difference across studies. Zhang et al. (2017) found during development of the AMQ that subscale means among team and individual sport athletes ranged from 3.54 to 3.73, with standard deviations in the 0.82 to 0.99 range. Comparatively, the gymnasts in our sample had slightly higher mindfulness scores overall, with means ranging from 3.63 to 4.11 across the three subscales, and lower standard deviations in the range of 0.48 to 0.59. Taken together, the single-sport sample of gymnasts who participated in the current study reported slightly higher mindfulness tendencies with lower variation across responses than the multi-sport sample of athletes used when developing the instrument. BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 19 In their research examining the validity of the Sport-MPS-2, Gotwals and Dunn (2009) reported mean scores for intercollegiate team sport athletes on the personal standards and concern over mistakes subscales were 3.68 (SD = 0.52) and 2.87 (SD = 0.68), respectively. In the present sample, the perfectionism scores among the intercollegiate gymnasts were equivalent or just slightly lower, with means of 3.61 (SD = 0.58) and 2.87 (SD = 0.82) for the personal standards and concern over mistakes subscales, respectively. Previously, Dunn et al. (2006) examined perfectionism among a sample of female figure skaters, a group slightly younger than the athletes in our gymnast sample but in a similar individual, judged sport context. The researchers found that the figure skaters’ scores for personal standards and concern over mistakes were also lower than in the team sport sample, with subscale means of 3.33 (SD = 0.86) and 2.37 (SD = 0.97) for personal standards and concern over mistakes, respectively. Thus, the notion that certain sports may be considered more “perfectionistic” than others may not necessarily equate to higher individual reports of perfectionism tendencies. Perhaps athletes in such sport contexts have normalized the pursuit of perfection in a different manner than athletes in team sports might, and thus may self-report their own perfectionism relative to a higher standard resulting in lower scores. In any case, the gymnasts in the present study scored on the perfectionism dimensions in ways that align closely with intercollegiate athletes in various team sports studied previously. Another primary aim of the current study was to assess potential performance differences across the mindfulness and perfectionism clusters. When gymnastics performance was considered on each of the four events across the three profiles, no significant differences were observed. It is important to note that the performance metric selected for comparison was relatively restricted in range given the calculation of the NQS as a snapshot of the better BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 20 performances for each gymnast during the competition season (i.e., best and worst performances are dropped). Still, the NQS was selected intentionally as it is a practical performance metric used in collegiate gymnastics for qualification/placement in post-season competition. Given the utility of this performance score in the sport of gymnastics, the current findings may have practical significance. Specifically, high level performance appears to be attainable for athletes across competitive events, regardless of their propensities for mindfulness and perfectionism. Gymnasts may learn coping strategies that allow them to perform successfully with varying degrees of mindfulness and perfectionism tendencies. This finding may have practical utility for coaches and athletes – that individuals with different personality characteristics are all capable of high quality performance. Despite the lack of statistically significant differences among the three profiles, noteworthy patterns in mean differences in event performance were observed. Researchers have argued that reliance on p values when determining the meaning of results may be problematic, as the statistic is highly contingent on sample size and says relatively little about the real-world meaning of findings (e.g., Gigerenzer, 2004; Kruschke, 2013; Wilkinson, 2014). In recent years, researchers have recommended interpreting test statistics through a contextual lens to better understand the practical significance of the results (Andersen, McCullagh, & Wilson, 2007). A similar process was recently adopted in a study of mindfulness-based programming for injury prevention (Ivarsson, Johnson, Andersen, Fallby, & Altemyr, 2015), and we have followed these recommendations. In the context of gymnastics, very small differences in performance scores may mean the difference between placing and not placing, between qualifying to post-season competition and not qualifying. BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 21 For example, the difference in NQS for the top 10 athletes on each competitive event during the 2019 regular season was approximately five hundredths of a point, 0.05. The mean score differences in the one to two tenth of a point range, 0.1 to 0.2, observed between profiles established in the current study were therefore considered to have real-world meaning in the context of gymnastics. For the comparison across profiles, h2 p effect size values ranged from 0.03 to 0.06, indicating that approximately three to six percent of variance in event performance may be accounted for by profile membership. In our sample of gymnasts, NQS values had a range of approximately one point on each event. Given the explained variance in event performance we observed in the study, a three to six percent change in NQS may mean the difference between first and tenth in the nation. Additionally, when effect sizes were computed for event scores with maximum variation between profiles, Cohen’s d values ranged from 0.37 to 0.65 indicating the presence of some moderate effect sizes. Thus, it is possible that some qualities of mindfulness and perfectionism serve athletes in more adaptive ways on certain competitive events. In support of this finding, statistically significant mean differences arose between the profiles compared on vault and on bars in post hoc pairwise comparisons. On vault, gymnasts highest in mindfulness performed best; whereas, on bars, gymnasts highest in perfectionism performed best. When observing the mean score patterns on each event across profiles, gymnasts highest in perfectionism performed relatively better than gymnasts in profiles lower in perfectionism on bars, beam, and floor. These trends suggest that the degree of mindfulness and perfectionism qualities most favorable for performance may vary by event, and that in contrast to existing research (e.g., Hill et al., 2018) perfectionism may be adaptive for competitive gymnastics performance in the context of the study. BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 22 It seems possible that the mindfulness and perfectionism qualities favorable for performance may also differ from those favorable for wellbeing. For instance, although the findings of the current study lend initial, tentative support for the physical performance benefits of perfectionism in gymnastics, high levels of concern over mistakes perfectionism has previously been considered maladaptive for the emotion and wellbeing of athletes (e.g., Hill et al., 2018). Researchers have provided some evidence of the potential benefits of mindfulness for the wellbeing of athletes, including reduced competitive anxiety, stress, and burnout; injury prevention; and increased confidence and self-efficacy (e.g., Noetel et al., 2017). Although the question of athlete wellbeing was not within the scope of the current research, future researchers might consider including such assessments when studying these constructs to better understand both the quality of athletes’ experiences alongside their objective performance. The current findings may also have practical implications for researchers and practitioners interested in delivering mindfulness-based interventions to athletes such as those who participated in our study. In light of some equivocal research findings in the mindfulness literature, researchers have begun to question the efficacy of mindfulness-based interventions for all participants, and have raised the potential for adverse effects of meditation-related experiences (Van Dam et al., 2018). Understanding individual characteristics that may predispose individuals to have more favorable versus adverse effects to meditation-related practices may help to direct our research and applied efforts toward participants who may benefit most from them. For instance, concern over mistakes perfectionism has been positively associated with anxiety and depressive symptoms (Hill et al., 2018) – experiences that align with the relatively rare albeit real meditation-related adverse effects that have been observed (Van Dam et al., 2018). Future researchers might aim to understand if differences exist across profiles BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 23 of individual characteristics in athletes’ readiness or desire to engage in mindfulness-based interventions, or in the effectiveness of such interventions among distinct profiles. By assessing these constructs prior to interventions, researchers or practitioners might then have a clearer understanding of who may benefit most from mindfulness-based interventions rather than assuming that all athletes participating have the capacity to benefit equally from such practices. We selected the NQS as our performance measure in the current research based on its practical use in determining placement in post-season competition. We recognize, however, that there may be potential limitations to this metric in our study. For instance, given the way the NQS is calculated, only a portion of a gymnasts’ performances throughout the season may be taken into consideration. Further, that portion of the season that is calculated into the NQS would not account for poorer competitive performances if gymnasts competed in most meets during the season. This performance measure may therefore be overly reductive and restricted in range, potentially limiting our ability to notice performance differences across the profiles on the different apparatus using inferential statistics. Future researchers might consider using a different performance metric (e.g., true average of all performances or range of performance scores) or a mix of measures to study the relationship between these concepts and performance. Self-report measures were used to assess individual experiences of both mindfulness and perfectionism among the gymnasts. When self-report measures are involved, there is a potential for bias in the form of accurate recall or social desirability. The potential for social desirability bias in the reported experiences may be especially salient given that athletes were asked to provide identifying information. During the initial screening analyses, small but significant differences in perfectionism scores were noted between gymnasts who did and did not provide their name, with those who did not report their name scoring higher in dimensions of BEING MINDFUL OF PERFECTIONISM AND PERFORMANCE 24 perfectionism than those who did. Although provision of names was a necessary component for carrying out the current study with objective performance measures, it should be noted that authentic self-report of perfectionism may be influenced to some extent when identifying information is provided. We accessed a large sample of elite level gymnasts to participate in the current study. Still, only small effects were found across profiles relative to objective performance – likely due to the restricted range in performance scores observed among this relatively homogeneous, high level sample of athletes, and to the inherently small increments of change frequently observed in the scoring system within gymnastics. With a larger sample of athletes, future researchers may be able to heighten the power to detect small, meaningful differences in performance among the different profiles. Still, that differences in performance outcomes were found between profiles may hold meaning for coaches, athletes, and practitioners operating in a sport where exceedingly small differences in scores often can have large practical consequences. Several directions for future research stem from the present findings. In the current study, we aimed to take a nuanced approach to studying the relationship between mindfulness and performance among collegiate gymnasts by also considering perfectionism as a contextually salient factor in the sport. We found individual profiles of mindfulness and perfectionism, and assessed how those quantitative reports were associated with objective measures of gymnastics performance. Still, further nuance in the contextually situated experiences of gymnasts seems attainable. Researchers have previously acknowledged the importance of understanding impact mechanisms of various facets of mindfulness (Birrer, Röthlin, & Morgan, 2012). By taking a mixed method approach, future researchers might better understand not only athlete profiles of BEING MINDFUL OF