January 2015

Clinical utility of the FMS and its component tasks

1Sports-iStock_000040897236Large-copy

By Erin Hartigan, PT, DPT, OCS, PhD, ATC; Nicole Chimera, PhD, ATC, CSCS; and Sarah Lamberton, NSCA-CPT

Although some research has found that using the composite score for the seven component tasks of the Functional Movement Screen is a reliable way to predict risk of injury in athletes, other studies suggest that evaluating the individual task scores may be more appropriate.

The Functional Movement Screen (FMS) is a preparticipation screening tool used to assess a person’s ability to perform foundational movement patterns that are essential to sport. The FMS attempts to assess and rank movement patterns using seven individual tasks: a deep squat, a hurdle step, an in-line lunge, a shoulder mobility test, an active straight leg raise, a trunk stability push up, and a rotary stability test. Each task requires both mobility and stability, based on proprioceptive and kinesthetic awareness principles.1,2

The seven tasks of the FMS are designed to assess the fundamental movements of an individual.3 When the FMS is used as part of a comprehensive assessment, performance can be observed to reveal any weaknesses, balance deficits, asymmetries, or all of these. Identifying these deficits or asymmetries may allow for customized recommendations intended to improve a given individual’s functional movement patterns.2 Each component of the FMS is scored from 0 to 3, with 3 being the best possible score, for a maximum composite score of 21 (Table 1).2

Reliability

Many studies have explored the inter-rater and intra-rater reliability of the FMS. Inter-rater reliability can be defined as the degree of agreement among different raters.4 Intra-rater reliability can be defined as the degree of agreement among test-retest measurements obtained by the same rater.4 In general, evidence suggests the FMS has acceptable to excellent inter-rater reliability for scoring, regardless of years of experience with the FMS.5-9 For intra-rater reliability, however, some studies suggest that experience matters. Gribble and colleagues10 found that intra-rater reliability increased with years of professional experience and years of experience with the FMS. Contrary to these findings, Smith and colleagues6 found that intra-rater reliability does not increase with experience. In fact, a certified FMS tester had the lowest intra-rater reliability when compared with an entry-level physical therapy (PT) student with no FMS experience, a certified athletic trainer with a PhD in biomechanics but no FMS experience, and an entry-level PT student who had completed 100 FMS tests but was not a certified tester.6

sports-table1When considering inter-rater reliability studies, it is worth noting the differences among those that were conducted in real time and those using video analysis. Two studies used videos for scoring individuals5,9 and four studies scored the FMS tasks in real time.6-9 Scoring the FMS in real time is more clinically applicable than scoring the screen using off-line video analysis. Video analysis is 2D, whereas during real-time analysis the rater can assess the motion from different vantage points. Interestingly, both studies5,10 that used video analysis had similar reproducibility, indicating that inter-rater and intra-rater reliability were acceptable and that reliability increased with experience. When studied in real time, acceptable levels of inter-rater and intra-rater reliability were also reported;6-9 however, the study by Smith and colleagues6 did find that different professionals with varying experience can consistently and reliably score the FMS after just one two-hour training session.

When considering intra-rater reliability studies, the findings of Frost and colleagues11 should be examined. Twenty-one firefighters were told raters were observing their movements as they performed the FMS. Raters then gave immediate feedback on how to achieve a perfect score and asked participants to repeat the FMS. FMS scores significantly improved and, interestingly, of nine firefighters who received scores below 14 on the initial FMS, only one individual scored below 14 on the second screen. The significant and meaningful changes in FMS scores indicated that eight firefighters were no longer “at risk for injury.” Although no directed feedback was provided, they improved just by receiving knowledge of the scoring criteria. Therefore, Frost and colleagues11 caution against directing efforts to improve individuals’ performance on the FMS, as participants accomplished their gains artificially and without impacting their initially demonstrated and likely preferred movement patterns. Furthermore, visual observations during this low-demand screen did not correspond to an individual’s performance during simulated occupational tasks (eg, simulated hose advance). Lastly, though individuals may achieve perfect squat and in-line lunge scores, ideal frontal plane knee mechanics did not transfer to higher-level tasks, bringing into question the use of the FMS to determine the readiness to return to sports or high-demand jobs.11

Validity

Much of the research on the FMS has been conducted in primarily male cohorts, including firefighters, professional football players, and marine officer candidates.12-14 However, in their study, Schneiders and colleagues8 included 209 participants, 108 of whom were women, and found no statistically significant difference in composite FMS scores between male and female participants. Another study by Loudon and colleagues15 that included 43 runners, 16 of whom were women, also found no significant difference in composite scores between male and female runners.

However, other studies suggest that, while male and female athletes may obtain similar composite scores, they obtain these scores in very different manners. Chimera and colleagues16 compared FMS performance between 81 female and 89 male Division I athletes and found male athletes performed significantly better on trunk and rotary stability tests and female athletes performed significantly better on the in-line lunge, straight leg raise, and shoulder mobility tests. Letafatkar and colleagues17 found similar results, in that male athletes performed significantly better on trunk and rotary stability tests, while female athletes performed significantly better on the shoulder mobility and straight leg raise tests. These findings suggest the FMS composite score may be used to compare individuals in mixed gender populations; however, caution should be used, as male and female individuals appear to obtain similar composite scores with different movement patterns.

sports-table2

The ability of the FMS to identify aberrant movement patterns and asymmetries makes it a useful tool for identifying injury risk.18 Evidence suggests that a predetermined cutoff score for the composite FMS score may be predictive of risk of injury. The highest possible composite score is 21. A composite score of less than 14 was predictive of risk of injury in football players,18 Marine Corps officer candidates,19 and female college athletes.20 Additional analyses on Marine Corps officer candidates indicated that combining poor three-mile run times and poor FMS scores (< 14) increased the ability to predict injury; those who scored poorly on both tests were 4.2 times more likely to experience an injury.21 Another study14 on a cohort of firefighters found that two of the FMS tasks, the deep squat and stability pushup, were predictive of risk of injury. Additionally, a study on a cohort of female collegiate athletes found the FMS was able to identify compensatory movement patterns resulting from contralateral imbalances, which indicated an increased risk of injury.20 However, there is still uncertainty in using the FMS composite score to predict injury, as the study by Kazman and colleagues13 found that high composite scores can also be predictive of injury because of low internal consistency among the seven tasks. Li and colleagues22 also found no evidence for unidimensionality of the FMS in elite athletes. Given the implications of low internal consistency among the tasks of the FMS, more attention should be paid to the score of each task rather than to interpretation of the composite score.

When determining the clinical utility of the FMS to predict injury, it’s important to consider the definition of injury. Kiesel and colleagues18 defined injury in football players as having been on the injured reserve list for at least three weeks. Butler and colleagues14 used a generic musculoskeletal definition of injury and were successful in using the FMS to identify firefighters who were removed from the academy because of said injury. In their study of female collegiate athletes, Chorba and colleagues20 defined musculoskeletal injury as having occurred during practice or competition and having provoked the athlete to seek some form of medical attention or advice. All of these studies14,18,20 found a composite score of 14 or less was predictive of increased risk of injury.

In Marine Corps officer candidates a score of less than or equal to 14 predicted injury with a sensitivity of .45 and a specificity of .71, and a serious injury with a sensitivity of .12 and a specificity of .95.19 However, Warren et al23 were unable to maximize the sensitivity or specificity of a range of FMS scores to identify injury risk in collegiate athletes when the injury was defined as a noncontact injury. Furthermore, when using the previously suggested score of 14 or less to identify injury risk, there was no statistically significant association between FMS composite score and injury (odds ratio = 1.01, 95% confidence interval, .53-1.91). There was also no differences in FMS composite scores between those who were injured and those who were not injured.23

Additionally, recent evidence suggests that perhaps a composite score of 17 should be used, as this cut-off score was found to maximize sensitivity (.645) and specificity (.780); athletes who scored less than a 17 on the FMS had approximately a 4.7 times greater risk of suffering a lower extremity injury that kept them out of participation for at least one full practice or game.17 Collectively, the literature shows the FMS demonstrates good reliability,5 but may lack specificity in identifying individuals at risk for noncontact injury.18,20,23

Composite scores also may be affected by a history of previous injury, surgery, or both, as athletes with a history of hip, hand, and elbow injury and shoulder surgery performed significantly worse and had significantly lower FMS composite scores than those without similar injury histories.16 Further, movement pattern analysis revealed a variety of differences in performance based on individual injuries; for example, a history of knee surgery was associated with poorer performance on the rotary stability test, and a previous hip injury was associated with poorer performance on the deep squat.16 Additionally, Letafatkar and associates17 reported that FMS performance in athletes with a previous history of ankle and knee injuries differed significantly from the performance in a group with no previous injuries.

There is a lack of conclusive research on the association between the FMS and athletic performance. Researchers did a comprehensive analysis of multidirectional speed (eg, 5-, 10-, and 20-m sprint intervals), modified T-test, turn difference, and multidirectional jumping (eg, bilateral and unilateral vertical, long, and lateral jumps) and FMS tasks and composite FMS scores from male athletes.24 They stratified athletes into high, intermediate, and low performers, and did analyses to identify movement deficiencies that would affect performance. Limited significant relationships indicated that the FMS appears to have few associations with the aforementioned performance measures.24 Yet, the findings do suggest that greater deep overhead squat scores correlated with smaller difference between turns (eg, the 505 agility test, a test of 180º turning ability) and greater bilateral vertical height and long jump distances.24 One study25 specifically evaluated the relationship among the in-line lunge component of the FMS and center of pressure, maximum jump height, and a 36.6-m sprint time; that study found performance on the in-line lunge test was not related to balance, power, or speed. However, another study26 found that in-line lunge scores explained 47% of the variance in reactive strength index (eg, jump height [mm]/ground contact time [ms]) and 38% in reactive agility cut performance (eg, the time required to complete an unanticipated cut) in youth soccer players. Lloyd and colleagues26 also found significant relationships between the composite FMS total score and individual tasks (deep overhead squat, in-line lunge, active straight leg raise, and rotary stability tests) and all three performance measurements (squat jump, reactive strength index, reactive agility cut) in these youth soccer players.26

Another study27 found significant positive correlations between the hurdle step, stability pushup, and rotary stability test scores and the backward overhead medicine ball throw (BOMB). The BOMB test was chosen to measure total body power. Yet, this study did suggest that the FMS may not have a meaningful association with performance, particularly given that it was designed to identify potential injury risk.27

There are two ways of interpreting the FMS scores, either as individual tasks or as a composite score.1,2 A composite score of either 1412,20,28 or 1717 has been found to be the cutoff for predicting injury in some studies. When using the FMS to examine functional movement, each FMS task has its own emphasis; however, some of the tasks share similar movement patterns.1,2 When looking at just the composite score, deficits associated with individual movement patterns may not be apparent, and treating the composite score as a single factor also may not be valid. Studies have used Chronbach’s alpha and exploratory factor analysis to determine the internal consistency and factor structure of the FMS in a group of Marine Corps officer13 candidates and elite athletes.22 If the FMS as a whole was constructed around a single factor, one would expect to find a high internal consistency among the seven tasks. However, both studies13,22 found there was a low internal consistency among these tasks, and concluded that results did not support the validity of the FMS composite score as a 1D construct. Chimera and colleagues16 and Letafatkar et al13 also found that, while male and female individuals were obtaining similar composite scores, they were obtaining those scores in different manners. Therefore, evidence suggests that individual scores for each movement pattern may be more clinically meaningful and relevant than a composite score of all seven tasks.

Conclusion

The FMS was designed as an instrument to assess functional movement.1,2 It was created as a screening tool to identify stability and mobility deficits and asymmetries that could be linked to an increased risk of injury.2 The findings of inter- and intra-rater reliability related to scoring the FMS suggest that it can be reliably scored by various professionals.5-10

Previous research has found the FMS is a valid tool for identifying individuals who are at an increased risk of injury, though injury is operationally defined in different ways across studies.14,18,20 However, the work done by Warren and colleagues23 is inconsistent with previous research findings, as there was no statistically significant association between the composite scores and risk of noncontact injury. Research questions the validity of the FMS as a tool in predicting performance levels, and therefore it should not be used to determine readiness to return to sports.11,25,27

Although some research has found that using the composite score for the seven tasks of the FMS is a reliable way of predicting risk of injury18 other research has found the seven tasks have a low internal consistency13,22 and that similar composite scores may be obtained in very different ways and appear to be sex-specific.16,17 This suggests the FMS is not a 1D construct, and evaluating individual scores may be more appropriate than evaluating the composite score.13,22

Because of new revelations, more research needs to be done on the efficacy of predicting injury from a composite FMS score. Similarly, more research should be done to determine the most appropriate way of evaluating scores.

Erin Hartigan, PT, DPT, OCS, PhD, ATC, is an assistant professor of physical therapy at the University of New England in Portland, ME. Nicole Chimera, PhD, ATC, CSCS, is an assistant professor of athletic training and program director in the Athletic Training Program at Daemen College in Amherst, NY. Sarah Lamberton, NSCA-CPT, will graduate from the University of New England in 2015 with a bachelor’s of science in applied exercise science.  

REFERENCES
  1. Cook G, Burton L, Hoogenboom BJ, Voight M. Functional movement screening: the use of fundamental movements as an assessment of function-part 2. Int J Sports Phys Ther 2014;9(4):549-563.
  2. Cook G, Burton L, Hoogenboom BJ, Voight M. Functional movement screening: the use of fundamental movements as an assessment of function – part 1. Int J Sports Phys Ther 2014;9(3):396-409.
  3. Cook G. Baseline sports-fitness testing. In Foran B, ed. High Performance Sports Conditioning. Champaign, IL: Human Kinetics; 2001.
  4. Portney LG, Watkins MP, eds. Foundations of Clinical Research Applications to Practice. 3rd ed. New Jersey: Pearson Education; 2009.
  5. Minick KI, Kiesel KB, Burton L, et al. Interrater reliability of the functional movement screen. J Strength Cond Res 2010;24(2):479-486.
  6. Smith CA, Chimera NJ, Wright NJ, Warren M. Interrater and intrarater reliability of the functional movement screen. J Strength Cond Res 2013;27(4):982-987.
  7. Onate JA, Dewey T, Kollock RO, et al. Real-time intersession and interrater reliability of the functional movement screen. J Strength Cond Res 2012;26(2):408-415.
  8. Schneiders AG, Davidsson A, Horman E, Sullivan SJ. Functional movement screen normative values in a young, active population. Int J Sports Phys Ther 2011;6(2):75-82.
  9. Teyhen DS, Shaffer SW, Lorenson CL, et al. The Functional Movement Screen: a reliability study. J Orthop Sports Phys Ther 2012;42(6):530-540.
  10. Gribble PA, Brigle J, Pietrosimone BG, et al. Intrarater reliability of the functional movement screen. J Strength Cond Res 2013;27(4):978-981.
  11. Frost DM, Beach TA, Callaghan JP, McGill SM. FMS scores change with performers’ knowledge of the grading criteria – Are general whole body movement screens capturing “dysfunction”? J Strength Cond Res 2013 Nov 20. [Epub ahead of print]
  12. Kiesel K, Plisky P, Butler R. Functional movement test scores improve following a standardized off-season intervention program in professional football players. Scand J Med Sci Sports 2011;21(2):287-292.
  13. Kazman JB, Galecki JM, Lisman P, et al. Factor structure of the functional movement screen in marine officer candidates. J Strength Cond Res 2014;28(3):672-678.
  14. Butler RJ, Contreras M, Burton LC, et al. Modifiable risk factors predict injuries in firefighters during training academies. Work 2013;46(1):11-17.
  15. Loudon JK, Wiesner D, Goist-Foley HL, et al. Intrarater reliability of functional performance tests for subjects with patellofemoral pain syndrome. J Athl Train 2002;37(3):256-261.
  16. Chimera N, Smith C, Warren M. Injury history, sex, and performance on the Functional movement Screen and Y Balance Test. J Athl Train 2015 [In press].
  17. Letafatkar A, Hadadnezhad M, Shojaedin S, Mohamadi E. Relationship between functional movement screening score and history of injury. Int J Sports Phys Ther 2014;9(1):21-27.
  18. Kiesel K, Plisky PJ, Voight ML. Can serious injury in professional football be predicted by a preseason Functional Movement Screen? N Am J Sports Phys Ther 2007;2(3):147-158.
  19. O’Connor FG, Deuster PA, Davis J, et al. Functional movement screening: predicting injuries in officer candidates. Med Sci Sports Exerc 2011;43(12):2224-2230.
  20. Chorba RS, Chorba DJ, Bouillon LE, et al. Use of a functional movement screening tool to determine injury risk in female collegiate athletes. N Am J Sports Phys Ther 2010;5(2):47-54.
  21. Lisman P, O’Connor FG, Deuster PA, Knapik JJ. Functional Movement Screen and aerobic fitness predict injuries in military training. Med Sci Sports Exerc 2013;45(4):636-643.
  22. Li Y, Wang X, Chen X, Dai B. Exploratory factor analysis of the functional movement screen in elite athletes. J Sports Sci 2014:1-7. [Epub ahead of print]
  23. Warren M, Smith CA, Chimera NJ. Association of Functional Movement Screen with injuries in Division I athletes. J Sport Rehabil 2014 Sep 8. [Epub ahead of print]
  24. Lockie RG, Schultz AB, Jordan CA, et al. Can selected Functional Movement Screen assessments be used to identify movement deficiencies that could affect multidirectional speed and jump performance? J Strength Cond Res 2015;29(1):195-205.
  25. Hartigan EH, Lawrence M, Bisson BM, et al. Relationship of the functional movement screen in-line lunge to power, speed, and balance measures. Sports Health 2014;6(3):197-202.
  26. Lloyd RS, Oliver JL, Radnor JM, et al. Relationships between functional movement screen scores, maturation and physical performance in young soccer players. J Sports Sci 2015;33(1):11-19.
  27. Okada T, Huxel KC, Nesser TW. Relationship between core stability, functional movement, and performance. J Strength Cond Res 2011;25(1):252-261.
  28. Peate W, Bates G, Lunda K, et al. Core strength: A new model for injury prediction and prevention. J Occup Med Toxicol 2007;2:3.
(Visited 162 times, 1 visits today)

Leave a Reply

Your email address will not be published. Required fields are marked *

Spam Blocker * Time limit is exhausted. Please reload CAPTCHA.