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Functional Movement Screen Composite Scores for Collegiate Functional 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. Descriptive epidemiology of collegiate men’s soccer injuries: national collegiate athletic association injury surveillance system, 1988-1989 through 2002-2003. J Athl Train. 2007;42(2):270-277. 6. Mattila VM, Parkkari J, Koivusilta L, Kannus P, Rimpela A. Participation in sports clubs is a strong predictor of injury hospitalization: a prospective cohort study. Scand J Med Sci Sports. 2009;19:267-273. 7. Cook G, Burton L, Hoogenboom B J, et al. Functional movement screening: the use of fundamental movements as an assessment of function - part 1. Int J SportsPhys Ther. 2014;9(3):396-409. 8. Cook G, Burton L, Hoogenboom BJ, et al. Functional movement screening: the use of fundamental movements as an assessment of function - part 2. Int J SportsPhys Ther. 2014;9(4):549-563. 9. Cook G, Burton L, Hoogenboom B. Pre-participation screening: the use of fundamental movements as an assessment of function - part 1. N Am J Sports Phys Ther. 2006;1(2):62 72. 10. Cook G, Burton L, Hoogenboom B. Pre-participation screening: the use of fundamental movements as an assessment of function – part 2. N Am J Sports Phys Ther. 2006;1(3):132 139. 11. Cook G. Movement: Functional Movement Systems, Screening - Assessment - Corrective Strategies. Lotus Publishing; 2011. 12. Kraus K, Schutz E, Taylor WR, et al. Efficacy of the functional movement screen: a review. J Strength Cond Res. 2014;28(12):3571-3584. 20 13. Clay H, Mansell J, Tierney R. Association between rowing injuries and the functional movement screen in female collegiate division I rowers. Int J Sports Phys The. 2016;11(3):345-349. 14. Everard E, Harrison A, Lyons M. To examine the relationship between the functional movement screen and the landing error scoring system in an active collegiate population. J Strength Cond Res. 2016. 15. Lockie RG, Schultz AB, Callaghan SJ et al. A preliminary investigation into the relationship between functional movement screen scores and athletic physical performance in female team sport athletes. Biol Sport. 2014;32(41):41-51. 16. Lockie RG, Callaghan SJ, Jordan CA et al. Certain actions from the functional movement screen do not provide an indication of dynamic stability. J Hum Kinet. 2015;14(47):19-29. 17. Tee JC, Klingbiel FG, Collins R et al. Preseason functional movement screen component tests predict severe contact injuries in professional rugby union players. J Strength Cond Res. 2016;30:11. 18. Duke SR, Martin SE, Gaul CA. Preseason functional movement screen predicts risk of time loss injury in experienced male rugby union athletes. J Strength Cond Res. 2017;31(10) 19. Sprague PA, Mokha MG, Gatens DR. Changes in functional movement screen scores over a season in collegiate soccer and volleyball athletes. J Strength Cond Res. 2014;28(11). 20. Mokha M, Sprague PA, Gatens DR. Predicting musculoskeletal injury in national collegiate athletic association division II athletes from asymmetries and individual-test versus composite functional movement screen scores. J Athl Train. 2016;51(4):276-282 21. Silva B, Clemente FM, Camoes M et al. Functional movement screen scores and physical performance among youth elite soccer players. Sports. 2017;5(16) 22. Clifton DR, Grooms DR, Onate JA. Overhead deep squat performance predicts functional movement screen score. Int J Sports Phys There. 2015;10(5):622-627. 23. Anderson BE, Neumann ML, Huxell Bliven KC. Functional movement screen differences between male and female secondary school athletes. J Strength Cond Res, 2015;29(4):1098 1106. 24. Nyland J, Kocabey Y, Caborn DN. Sex differences in perceived importance of hamstring stretching among high school athletes. Percept Mot Skills. 2004;99(1):3-11. 25. 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