The increased sports participation in recent decades has brought with it an increase in the risk for sustaining musculoskeletal injuries. It has long been thought that isolated muscle stretching would be an effective intervention to reduce muscle soreness or musculoskeletal injury; however, recent research has suggested that this is not the case (10,11,20). To reduce injury risk, sports medicine professionals have begun to focus on improving movement patterns as opposed to focusing on rehabilitation of a specific joint (5,13). Research has demonstrated that an isolated rehabilitation approach after injury is not sufficient to normalize performance that encompasses the entire body (17). Data have also suggested that an isolated injury will adversely affect regions away from the injury site (2-4,9,12,15,18,22,23,25,26). The term regional interdependence has recently been applied to conceptually explain why dysfunction in one body region may be contributing to weakness, tightness, or pain in another region (27). Thus, a valid and reliable measurement tool that assesses multiple domains of function simultaneously is in demand.
Current research has suggested that tests assessing multiple domains of function (e.g., balance, strength, and range of motion) simultaneously may improve the accuracy of identifying athletes at risk for injury (19). These tests can typically be carried out by strength and conditioning professionals in a variety of settings. Assessments by strength and conditioning professionals typically include testing to determine the athlete's strength, speed, agility, and flexibility (1). Strength and conditioning assessments have met an important demand in the overall functional performance assessment of the athlete, but there is still a need to routinely assess the individual athlete's fundamental movement characteristics (5,13). Recently, a tool to assess fundamental movement, The Functional Movement Screen (FMS), has been described by Cook et al. (6,7).
The FMS consists of a series of 7 fundamental movement tests designed to categorize functional movement patterns. The 7 movement tests use a variety of positions and movements closely related to normal growth and development. It is conceptualized that fundamental movements, such as those tested in the FMS, operate as the basis of more complex movement patterns used in common daily activities and sports. Preliminary data have established the relationship between an athlete's functional movement characteristics, as measured by the FMS, and injury risk in professional football players (14). However, there is currently no data examining the interrater reliability of the FMS.
The overall goal of this study is to establish the interrater reliability of the FMS by comparing individuals with different levels of training on the FMS. Our study will aim to compare the FMS test scores of expert raters who assisted in the development of the screening and novice raters who have completed a standardized training program in the FMS.
Experimental Approach to the Problem
The FMS is a novel testing tool that is growing in popularity in the clinical setting; however, reliability between raters for the FMS has yet to be established. This information is important for clinical settings that may use more than 1 clinician to score the FMS. To determine the interrater reliability of the FMS, while controlling for previous experience, 4 raters each independently scored the subjects performing each component of the FMS. The raters consisted of 2 experts and 2 novices. An expert is defined as an individual who was instrumental in the development of the FMS with over 10 years of experience with the tool. Novice individuals were defined as having taken the standardized introductory training course and have used the FMS less than a year.
The scores of the 2 experts were compared, as were the scores of the 2 novices. Finally, scores comparing paired expert and novice raters were evaluated. The standardized scoring criteria originally described were used for this study (8). For each test, the level of agreement was calculated between each pair of raters. In this way, the need to understand the reliability of the FMS among clinicians will be addressed to determine if current training is adequate for scoring the FMS.
Forty healthy college students (23 women, 17 men, average age 20.8, 13 varsity athletes) were recruited by word of mouth. By self-report, all subjects were free from injury and able to participate in desired physical activities. The purpose of the study was described to all potential subjects and each signed an informed consent approved by the University's Institutional Review Board. Participants qualified for the study if they were at least 18 years of age with no self-reported spinal or extremity pain and were not currently under the care of a medical professional for any musculoskeletal complaint. One subject's data were lost due to a video malfunction. The videos of the remaining 39 subjects were then viewed and scored by all the raters individually.
The FMS is designed so that the 7 movement patterns are considered together as a comprehensive cross section of functional movement. These 7 tests, used to assess overall functional movement ability, include the deep squat (Figure 1), the hurdle step (Figure 2), the in-line lunge (Figure 3), the shoulder mobility test (Figure 4), the active straight leg raise (ASLR) (Figure 5), the trunk stability push-up (Figure 6), and the rotary stability test (Figure 7). There are 3 clearing tests, each associated with one of the individual FMS tests, which check for pain accompanying shoulder internal rotation/flexion and end-range spinal flexion and extension pain (Figure 8). All subjects performed each of the 7 tests while being videotaped from both anterior and lateral views. Two Sony Handycam (Sony Electronics Inc., Tokyo, Japan) video camcorders were used to record the participants performing the FMS movements. The Dartfish Connect software (Dartfish, Fribourg, Switzerland) was used to record and organize the videos.
The FMS is scored on a 0-3 ordinal scale. A score of 3 represents the subject's ability to perform the functional movement pattern as described, a score of 2 indicates that some type of compensation is present when completing the pattern, and a score of 1 is given when the subject is unable to perform the movement pattern. A zero is recorded if there is pain associated with any portion of the test including the clearing tests.
The weighted Kappa statistic was calculated for each test between the 2 pairs of raters. The Kappa statistic is a measure of “true” agreement, beyond that which is expected by chance. It is a ratio of the proportion of time that raters agree, corrected for chance agreement, to the maximum proportion of times that the raters could agree (24). It takes the following form:
Weighted Kappa (κw) reflects the degree of disagreement between raters by attaching greater emphasis to large differences between ratings than to small differences (24). It takes the following form:
with Σwf_o being the sum of the weighted observed frequencies and wfc being the sum of the weighted frequencies predicted by chance. Quadratic weights were used for the frequencies, with the quadratic weight of no difference equaling 1, disagreement by 1 category equaling 0.89, and disagreement by 2 categories equaling 0.56. The frequency of each score combination in the contingency table was multiplied by its respective quadratic weight to indicate the more significant effect of larger disagreement (24).
The tests were analyzed by addressing the kappa values of both individual right and left sides and the final score for each of the 7 tests. The pair of novice raters demonstrated excellent agreement on 6 of the 17 test components, including the deep squat and shoulder mobility tests, and portions of the trunk stability push-up and ASLR tests (21,24). Substantial agreement was evident on 8 of the 17 test components. The right and left components of the lunge and the final component of the rotary stability test each demonstrated moderate agreement (Table 1) (21,24).
The pair of expert raters varied more in scoring, with excellent agreement on 4 of the 17 test components, including the shoulder mobility test and the final component of the ASLR. Substantial agreement was seen in 9 of the 17 test components. Two components of the lunge and 2 components of the rotary stability tests demonstrated moderate agreement (Table 2) (21,24).
When comparing the average scores of the paired novice and expert raters, 14 of the 17 tests demonstrated excellent agreement. Substantial agreement was evident in 1 component of the rotary stability test (kw = 0.74) and 2 components of the in-line lunge (κw = 0.74, κw = 0.79) (Table 3) (21,24).
These data indicate that the FMS has high interrater reliability and can confidently be applied by trained individuals when the standard procedure is used. The majority of the averaged tests were ranked in the category of excellent agreement according to Portney and Watkins (21). However, there were noticeable differences between the 2 pairs of raters and between different tests. The variance in these results may be due to the experience of the raters, testing protocol, or unclearly defined scoring criteria.
Neither pair of raters fell below a moderate level of agreement. The novice raters had excellent agreement on 2 more test components when compared with the expert raters (6 vs. 4), although the percent agreement was similar (89.6 and 86.7% for novice and expert raters, respectively). When the novice raters were compared with expert raters, 14 of the 17 tests had excellent agreement. These results suggest that reliable scores should be obtained by individuals who have been trained in the standardized FMS program.
Additional scoring variability may be attributable to the inherent movement that was assessed. Some movements may benefit from a 3-dimensional approach as opposed to the 2-dimensional approach used in this protocol. The tests demonstrating the lowest Kw, the lunge and rotary stability tests, are best scored by evaluating all 3 planes of motion. In this study, one camera captured a straight frontal plane view and the second camera recorded the sagittal plane. Due to the 2-dimensional limitations of the video setup, it was difficult to accurately assess the extent of a participant's extraneous movement in the transverse plane during these trials, and thus, a third camera may assist in completing the analysis of the movement. However, this protocol would be difficult to complete in the field setting and thus may not be practical.
A final component of the testing that may have contributed to the variation in scores may be associated with the scoring criteria. Some of the tests have less clearly defined descriptors of midrange performance. This is most appreciable in the lunge, hurdle step, and rotary stability tests. For these tests, the dichotomous extremes of performance are easily distinguishable; however, the division of the intermediate scores is less apparent. The results of this study are being used to review the current scoring criteria and determine if alterations are needed. The ability to clearly identify differential performance levels will assist coaches and trainers in improving interpretation of scores on the subsets to target specific areas of poor functional movement. Despite these limitations, the FMS remains a reliable measurement tool for functional movement analysis.
Future study designs should evaluate the reliability of real-time scoring of the FMS as compared with reviewing a video of the tests. Establishing the reliability of a real-time scoring protocol would allow for more rapid feedback on the test performance and reduce time spent on analysis. In the field setting, most professionals will not use video in administering and scoring the FMS. To provide efficient and immediate feedback to a large number of athletes, real-time analysis is most often used. This setting is an area for future research regarding the reliability of the FMS.
The FMS is growing in popularity but has yet to be assessed for interrater reliability. The test is commonly used to assess the movement patterns of athletes and to make decisions related to interventions for performance enhancement. The results of this study suggest that individuals who have undergone the standardized training protocol will score the FMS in a similar manner.
The researchers would like to thank the University of Evansville Honor's Program grant and the University of Evansville's College of Education and Health Science for funding the research project. The 2 expert raters were originally involved in the conception of the FMS. The results of the present study do not constitute endorsement by the authors or the National Strength and Conditioning Association.
1. Baechle, T and Earle, R. Essentials of Strength and Conditioning
. 2nd ed. Champaign, IL: Human Kinetics, 2000.
2. Bullock-Saxton, JE. Local sensation changes and altered hip muscle function following severe ankle sprain. Phys Ther
74: 17-28; discussion 28-31, 1994.
3. Bullock-Saxton, JE, Janda, V, and Bullock, MI. The influence of ankle sprain injury on muscle activation during hip extension. Int J Sports Med
15: 330-334, 1994.
4. Cholewicki, J, Greene, HS, Polzhofer, GK, Galloway, MT, Shah, RA, and Radebold, A. Neuromuscular function in athletes following recovery from a recent acute low back injury. J Orthop Sports Phys Ther
32: 568-575, 2002.
5. Cook, EG. Athletic Body in Balance; Optimal Movement Skills and Conditioning for Performance
. Champaign, IL: Human Kinetics, 2004.
6. Cook, EG, Burton, L, and Hogenboom, B. The use of fundamental movements as an assessment of function-Part 1. North Am J Sports Phys Ther
1: 62-72, 2006.
7. Cook, EG, Burton, L, and Hogenboom, B. The use of fundamental movements as an assessment of function-Part 2. North Am J Sports Phys Ther
1: 132-139, 2006.
8. Foran, B. High Performance Sports Conditioning
. Champaign, IL: Human Kinetics, 2001.
9. Giza, E, Silvers, H, and Mandelbaum, BR. Anterior cruciate ligament tear prevention in the female athlete. Curr Sports Med Rep
4: 109-111, 2005.
10. Herbert, RD and De Noronha, M. Stretching to prevent or reduce muscle soreness after exercise. Cochrane Database Syst Rev
4: CD004577, 2007.
11. Herbert, RD and Gabriel, M. Effects of stretching before and after exercise on muscle soreness and risk of injury: Systematic review. BMJ
325: 468, 2002.
12. Hewett, TE, Ford, KR, and Myer, GD. Anterior cruciate ligament injuries in female and male athletes: Part 2, a meta-analysis of neuromuscular interventions aimed at injury prevention
. Am J Sports Med
34: 490-498, 2006.
13. Kiesel, K, Burton, L, and Cook, EG. Mobility screening for the core. Athl Ther Today
9: 42-45, 2004.
14. Kiesel, K, Plisky, P, and Voight, M. Can serious injury in professional football be predicted by a preseason Functional Movement Screen? North Am J Sports Phys Ther
2: 147-158, 2007.
15. Nadler, SF, Malanga, GA, Bartoli, LA, Feinberg, JH, Prybicien, M, and Deprince, M. Hip muscle imbalance and low back pain in athletes: Influence of core strengthening. Med Sci Sports Exerc
34: 9-16, 2002.
16. Nadler, SF, Malanga, GA, Feinberg, JH, Prybicien, M, Stitik, TP, and Deprince, M. Relationship between hip muscle imbalance and occurrence of low back pain in collegiate athletes: A prospective study. Am J Phys Med Rehabil
80: 572-577, 2001.
17. Nadler, SF, Malanga, GA, Feinberg, JH, Ruanni, M, Moley, P, and Foye, P. Functional performance deficits in athletes with previous lower extremity injury. Clin J Sport Med
12: 73-78, 2002.
18. Nadler, SF, Moley, P, Malanga, GA, Rubbani, M, Prybicien, M, and Feinberg, JH. Functional deficits in athletes with a history of low back pain: A pilot study. Arch Phys Med Rehabil
83: 1753-1758, 2002.
19. Plisky, PJ, Rauh, MJ, Kaminski, TW, and Underwood, FB. Star Excursion Balance Test as a predictor of lower extremity injury in high school basketball players. J Orthop Sports Phys Ther
36: 911-919, 2006.
20. Pope, RP, Herbert, RD, Kirwan, JD, and Graham, BJ. A randomized trial of preexercise stretching for prevention of lower-limb injury. Med Sci Sports Exerc
32: 271-277, 2000.
21. Portney, L and Watkins, M. Foundations of Clinical Research: Applications to Practice
. 2nd ed. Upper Saddle River, NJ: Prentice Hall, 2000.
22. Silvers, HJ and Mandelbaum, BR. Anterior cruciate ligament tear prevention in the female athlete. Curr Sports Med Rep
4: 341-343, 2005.
23. Silvers, HJ and Mandelbaum, BR. Prevention of anterior cruciate ligament injury in the female athlete. Br J Sports Med
41(Suppl 1): i52-i59, 2007.
24. Sim, J and Wright, CC. The kappa statistic in reliability studies: Use, interpretation, and sample size requirements. Phys Ther
85: 257-268, 2005.
25. Vad, VB, Bhat, AL, Basrai, D, Gebeh, A, Aspergren, DD, and Andrews, JR. Low back pain in professional golfers: The role of associated hip and low back range-of-motion deficits. Am J Sports Med
32: 494-497, 2004.
26. Van Dillen, LR, Sahrmann, SA, Caldwell, CA, McDonnell, MK, Bloom, N, and Norton, BJ. Trunk rotation-related impairments in people with low back pain who participated in two different types of leisure activities: A secondary analysis. J Orthop Sports Phys Ther
36: 58-71, 2006.
27. Wainner, RS, Whitman, JM, Cleland, JA, and Flynn, TW. Regional interdependence: A musculoskeletal examination model whose time has come. J Orthop Sports Phys Ther
37: 658-660, 2007.