Research Review By Dr. Demetry Assimakopoulos©


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Date Posted:

November 2012

Study Title:

Using the Functional Movement Screen to Evaluate the Effectiveness of Training


Frost DM, Beach TAC, Callaghan JP & McGill SM

Author's Affiliations:

Department of Kinesiology, University of Waterloo, Waterloo ON; Faculty of Physical Education and Health, University of Toronto, Toronto ON.

Publication Information:

Journal of Strength and Conditioning Research 2012; 26(6): 1620-1630.

Background Information:

Many strength and conditioning specialists as well as various manual therapy professionals regard the body as a series of interconnected segments. This theory posits that each joint has an inherent quality of being either more stable or more mobile than other joints further along the kinetic chain. For instance, the hip is required to be mobile, while the lumbar spine and knee are required to be stable. If the hip is not mobile, this can lead to low back and/or knee dysfunction because these link-segments proximal and distal to the hip joint must increase their mobility to create sufficient movement quantity to allow the performance of functional tasks. Should this scenario exist, while movement quantity is not an issue anymore, movement quality is – issues with poor movement quality can lead to pain and dysfunction along the proximal or distal aspect of a particular kinetic chain.

Using non-contact ACL injuries as an example: many clinicians use link-segment audits to assess the risk of this injury, looking at factors such as dynamic knee valgus, which can be caused by subtalar overpronation and/or glute muscle inhibition. These clinicians use this information to create long term interventions in a preventive manner – this sort of approach has shown amazing results in preventing non-contact ACL injury. Many scientists and clinicians use these movement quality-based screens to expose “faulty” movement patterns that could potentially cause injury.

The Functional Movement Screen (FMS) is one method that has shown good reliability in predicting injury in some athletes (1, 2). The FMS utilizes 7 functional tasks which audit movement quality in various planes. Each task is graded on a 4-point scale (0-3), for a cumulative grade out of 21. Interrater and intrarater reliability scores are known to be quite high based on previously published data (3, 4). However, many researchers and field clinicians remain curious about how a client/patient may score on multiple days subsequent to an initial test. Additionally, the numerical scoring method leaves little for the practitioner to consider when prescribing patient-specific corrective exercises for their aberrant movement pattern; is grading someone 2/3 really the way to go? How do clinicians know which corrective exercises to give a client/patient if they’ve simply scored a 2/3? Is that really enough information?

Bearing these questions in mind, this investigation examined the utility of the FMS as a way of evaluating changes in individual movement patterns after an exercise intervention. Their hypothesis was that training would improve scores beyond changes realized by the control group and could therefore be utilized effectively as an intervention. Three scoring methods were examined and tested for their ability to reflect task performance. Their hypothesis in this case was that any differences found amongst intervention groups would become move obvious when different scoring methods were used.

Pertinent Results:

FMS Standard Scoring Method (0-3):

No significant difference was found between groups before training. There were no significant changes in the total FMS score found at the post-training data point for any group. However, some individuals from each group improved, but the amount post-training was not significant. Conversely, some individuals in each group got worse in their FMS score post-training. The squat, hurdle and lunge tests showed the fewest changes in the participants who received training.

The magnitude of the change seen in the CTL group was dependant on the individual’s initial score. Seventeen of the 26 individuals in the CTL group who increased their score post-training were given an initial grade of < 13. Funny enough, 14/17 individuals who had a decrease in their score post-training had baseline scores of > 13. No differences were found in the distribution of scores between the groups tested.

Scoring Method:

There was no difference between groups prior to training. The squat and lunge were the worst and best scored tasks, respectively. Surprisingly, no scoring method was significantly superior over any other (STD = 33, RES = 41, MOD = 44). Statistically significant between-day correlations were discovered among the CTL group in all 3 scoring methods.

Clinical Application & Conclusions:

While it was hypothesized that the FMS scores of the subjects in the experimental groups would exhibit changes that were greater and more consistent than the control group, the data collected during experimentation did not support this hypothesis. It was also hypothesized that training (most especially INT1) would improve their score beyond any of the changes visualized by the control group. Despite measures being taken to ensure each participant received no feedback and was unaware of the overall rationale of the test so as to discourage simply training for the test, FMS scores did not change after 12 weeks of training – there was no difference among the 3 groups upon first glance.

However, one unexpected result that was found with further and more complex analyses was that the control group, in fact, did change - just not in a systematic fashion that would be expected using the FMS scoring system. Eighty-five percent of the firefighters in the CTL group had a different FMS score after the 12 week intervention – up or down. With this being said, it is not possible to use the standard FMS ordinal scale to assess improvement in movement quality subsequent to training in this study. Thus, it remains unclear as to whether descriptors such as “2” or “14” provide the necessary information to make decisions about exercise prescription.

One primary issue with the FMS is the fact that a wide range of movement pattern dysfunctions can be categorized with the same ordinal score. This issue was accounted for in this study by adding 2 additional grading systems to evaluate movement quality using the FMS. Despite this, both modified scoring systems failed to tell the difference between the number of changes experienced by subjects receiving training and those in the control group.

The authors conclude that screening using the FMS could possibly expose individual issues in movement quality, thus proving a basis from which to make recommendations for exercise prescription. The problem is, many factors can influence the way in which a person moves (ex. verbal feedback, external constraints, individual adaptations to training, etc) – are these 7 tests telling you everything you need them to? Further questions related to implementation and interpretation need to be explored. Can the standard FMS implementation and interpretation lead to an exercise prescription that ensures consistency and effectiveness in removing the aberrant movement pattern, and result in sustainable optimal movement patterns? Only more research will tell.

Study Methods:

For a more detailed description of the on the FMS itself, please see Related Reviews linked below from RRS.

Sixty firefighters were recruited from the Pensacola Fire Department. All firefighters were free of MSK injury or pain at the time of testing and were on full active duty. Each firefighter was scored based on how they chose to perform the task (a self-selected movement pattern) – no coaching and/or feedback were provided.

Each subject was screened with approximately 50 job-specific and general tests; 7 of these tests comprised the FMS. Their FMS scores were taken before and after a 12-week training regimen. The FMS was scored by a certified FMS instructor. Four repetitions were performed by each person and the best test score was taken into consideration. Each participant was blinded to the test objectives, scoring criteria and results. Additionally, each exercise professional administering the personal training program suggested by each individual’s FMS score was blinded to the results of the FMS and instructed to not share the test objectives or scoring criteria with the subjects. Each person was video analyzed from the saggital and frontal planes.

Subjects were then allocated to 1 of 3 groups:
  • Intervention 1(INT 1 – n = 21): received three 1.5 hour training sessions each week and were coached by strength and conditioning professionals. They were instructed in a periodized fashion, with specific focus on whole-body coordination and control during the execution of tasks, rather than performance metrics (quality over quantity) so as to prevent injury. However, they also took into consideration strength, power and aerobic capacity development.
  • Intervention 2 (INT 2 – n = 19): received three 1.5 hour training sessions each week and were coached by strength and conditioning professionals. These individuals were made as fit as possible and to maximize performance and fitness outcomes. Exercise technique was monitored for safety purposes, but was not the primary emphasis (quantity over quality).
  • Control (CTL – n = 20): No feedback or guidance for exercise. They were asked to not change their physical activity habits.
The video recorded FMS was graded using 3 different methods: the FMS standard 0-3 scale (STD – see other RRS reviews for a detailed description); a modified 100-point scale where grades are assigned based on the number of compensations present (MOD), and a true 100-point scale which weighted specific compensations (research standard; RES).

In the MOD scoring method, each task was assigned one primary objective. The primary objectives for each task were: Deep squat – hips break parallel; hurdle step – no lumbar flexion; in-line lunge – no forward lean; shoulder mobility – fists are within one hand length away from one another; straight leg raise – malleolus lies between mid-thigh/ASIS; push-up – body is lifted as one unit; rotary stability – balanced ipsilateral. All other compensations were noted as secondary. If the test’s primary objective was met by the participant, the total task score was made equal to the total number of secondary compensations present (as if each compensation is worth one point). If the primary objective was not met, then the subject was scored 1 point over the maximum number of compensations possible (i.e. 7 for the squat), and each additional compensation was scored above that. So in the case of the squat, if the participant could not squat to parallel, failing the primary objective and thus the primary objective is not met, their best possible score would be 7 (rather than zero). For each additional compensation, 1 point was added to the best possible score (in this example 7+1 for a total of 8 as the score for the squat). Left and right sides were treated separately. The scores of each task were evenly weighted and added together, for a cumulative score out of 100, with zero being the best possible score.

In the case of the RES scoring system, the same identical scoring system as the STD was used, only specific compensations and tests were weighted, right and left sides were independently treated, and a best cumulative score out of 100 was given.

All FMS scoring methods were examined for normality. To examine significant changes post training, a Wilcoxon signed-rank test was used. Also, a one-way Chi-square test was performed to determine if between-group and between-method changes were significant. Additionally, Spearman Rank Order Correlations were performed to ensure between-day repeatability among the control group.

Study Strengths / Weaknesses:

  • The authors used a very creative strategy to examine the reliability and utility of the FMS. Scoring and interpreting the FMS may not be giving you the information you think it is!
  • Perhaps if more than 1 assessor got the same results detailed in the study, greater statistical power would have been provided, lending greater credence to the results. However, should the results have been different between the assessors, the fact that there was no difference between the scoring methods may have simply been an anomaly – maybe the assessor was not good enough to pick up minute changes in movement quality.

Additional References:

  1. Kiesel, K, Plisky, P, and Kersey, P. Functional Movement Test Score as a Predictor of Time-Loss During a Professional Football Team’s Pre-Season. Indianapolis, IN: Presented at the 55th Annual Meeting of the American College of Sports Medicine, 2008.
  2. Kiesel, K, Plisky, PJ, and Voight, ML. Can serious injury in professional football be predicted by a preseason functional movement screen? N Am J Sports Phys Ther. 2007; 2: 147–158.
  3. Cook, G, Burton, L, and 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: 62–72.
  4. Cook, G, Burton, L, and 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: 132–139.