Research Review By Dr. Demetry Assimakopoulos©

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Date Posted:

September 2012

Review Title:

Functional Movement Screen: Reliability & Normative Data

Publication Information:

  1. Teyhen DS, Shaffer SW, Lorenson CL et al. The Functional Movement Screen: A Reliability Study. Journal of Orthopaedic & Sports Physical Therapy 2012; 42(6): 530-540.
  2. Perry F & Koehle MS. Normative Data for the Functional Movement Screen In Middle Aged Adults. Journal of Strength and Conditioning Research 2012; [Epub ahead of print].

Background Information:

The Functional Movement Screen (FMS) is a clinical tool enabling clinicians to assess and critique the efficiency and quality with which a patient/client performs multiple movements that emulate the demands of daily and sporting tasks (for more information on FMS - CLICK HERE). It was designed to uncover movement deficits and asymmetries that could, in theory, predict the occurrence of musculoskeletal injuries in athletes and the general population.

The FMS consists of 7 movement tests, each scored by an examiner between 0-3 points. These individual scores generate a sum or composite score, ranging from 0-21 points. The movements include:
  1. Deep squat;
  2. In-line lunge;
  3. Hurdle step;
  4. Shoulder mobility;
  5. Trunk stability push up;
  6. Active straight leg raise; and
  7. Quadruped rotary stability.
Five of the 7 are designed to assess for the presence of asymmetry by performing the tests bilaterally, while the remaining 3 are designed to determine the presence or absence of pain (the specifics of which are beyond the scope of this article). Should asymmetries be found, the lower of the 2 scores is included in the composite score. Each test is scored on a 0-3 ordinal scale, with 3 being the maximum. Should pain be elicited in any of the tests, it is given a score of zero. If the subject could not remain in the proper position throughout the movement or lost balance, they are given a score of 1. A score of 2 indicates the participant compensated for the movement in some way, and did not perform the movement adequately. A score of 3 is given to the patient when they perform a perfect test.

Recent studies on the FMS have shown a high specificity with low sensitivity for detecting risk of injury (1-2). Overall, this growing body of literature has universally concluded that FMS scores ≤ 14 suggest greater injury risk. However, scores ≥ 14 do not rule out the chance of future injury. Despite this, many questions remain unanswered, such as: which populations of sport professionals are optimally screened by the FMS for predicting injury risk, and which types of injuries are predicted by scores ≤ 14?

The overarching goal of the FMS is to find dysfunction and implement individualized corrective exercises in an effort to mitigate the chance of injury. However, studies examining the interpretation and reliability of FMS scores are scant. It is the mission of one of the reviewed articles below to determine the reliability of the FMS in a young-to-middle aged, active military population.

The second of the two studies featured here explored the generalizability of the FMS beyond the military, professional and collegiate athletes, and students, by reporting normative reference values for healthy, middle aged adults (which is very important for clinical practice). In addition to this, the authors also endeavored to identify how one’s age, body mass index (BMI), physical activity participation and balance can affect an individual’s FMS score.

Study Summaries:

The reliability study (#1 above) demonstrated moderate-to-excellent inter-rater agreement. The test-retest (intra-rater) agreement scores at 48-72 hours after the initial assessment showed substantial agreement on the trunk stability push-up, shoulder mobility, ASLR, deep squat and in-line lunge tests, while also showing moderate agreement on the hurdle step, and poor agreement on the quadruped rotary stability test. The inter-rater reliability score (same day) of the composite FMS scores resulted in an intraclass coefficient score of 0.76, indicating good reliability, while the intra-rater rating (48-72 hours later) showed an intraclass coefficient score of 0.74, indicating moderate reliability.

The normative data study (#2 above) showed that each of the variables described above contribute a significant predictive value. Individuals with greater age and/or body mass indexes were found to score lower on the FMS, indicating a greater chance of future injury. Conversely, individuals who scored a lower body mass index tend to achieve higher FMS scores, indicating a lesser chance of future injury. Additionally, higher scores on the Healthy Physical Activity Participation Questionnaire (HPAPQ) generally predicted higher FMS scores. The Balance Error Scoring Scale (BESS) was not shown to affect the FMS scores. The positive score that can occur from a high HPAPQ score is not modified by advancing age or body mass index. Only 10 participants of the reliability study were identified as being at risk for injury based on previously published values.

Clinical Application & Conclusions:

  • The FMS composite score, among novice raters, demonstrated good-to-moderate inter-rater and intra-rater reliability with an acceptable level of measurement error.
  • The inter-rater reliability was excellent-to-good for the push up, quadruped rotary stability test, shoulder mobility, SLR, squat, hurdle and lunge.
  • The normative data study showed that a number of variables can affect a composite FMS score, and is one of the first studies to prove its utility in a general, middle-aged population.
  • Advancing age and higher BMI scores negatively affect the FMS score, while higher levels of physical activity positively affect the score. It is important to note that if you have an overweight/obese individual or an older person as a patient/client, their FMS score may be lower normally.
  • They also proved that it is possible to have a higher FMS score irrespective of age and/or BMI if the patient/client performs regular (most days of the week; at least moderate intensity) physical activity.

Study Methods:

The reliability study (#1 above) included individuals from the Fort Sam Texas Military Base between the ages of 17-35. Subjects were excluded if they had a previous complaint of lower extremity pain, back pain, or medical or neuromuscular disorders that limited them in the last 6 months. They were also excluded if they had a previous history of fracture of the femur, pelvis, tibia, fibula or calcaneus or were known to be pregnant.

Eight physical therapy students participated as examiners. All examiners underwent 20 hours of FMS training led by 4 physical therapists and 1 research assistant. Four of the 8 were randomly assigned to assess intra-rater test-retest reliability by assessing the FMS on day 1 and day 2. The other 4 students were randomly assigned to view the subjects’ movement simultaneously with the first set of 4 examiners to conduct the inter-rater reliability assessment on day 2. To minimize bias, examiners were randomly assigned and those randomized to day 2 were blinded to the findings of those randomized to day 1.

The reliability study utilized kappa statistics to determine agreement between components (excellent agreement = > 80%; substantial agreement = 79.9-60%; moderate agreement = 59.9%-40%; poor to fair agreement = ? 40%). Reliability of the composite test scores were analyzed using intraclass correlation coefficients (ICC: good reliability = > 0.75; moderate reliability = 0.74 – 0.50; poor reliability = < 0.50).

The FMS normative data study (#2 above) included a number of variables that could potentially raise or lower with FMS scores and theoretically, prediction of future injury. The BESS, a static balance measurement, characterized by postural sway, and the HPAPQ, a form designed to quantify the frequency and intensity of one’s physical activity, were included. Additionally, age and body mass index were factored in as variables. Their study was performed on individuals from the general population, with an average age of 50 years. Partial correlations were conducted for the FMS scores and variables. Linear regression analyses were performed to evaluate the predictive value of all the variables.

Study Strengths / Weaknesses:

Strengths:
  • The normative data study attempted to understand how different variables affected FMS scores in the middle-aged population. This adds a real-life understanding of the FMS – it allows the clinician or trainer to understand why/how certain scores were attained, in addition to having MSK dysfunction. In addition to training silent dysfunctions, you can also council your client or patient to be more physically active or to lose weight thus theoretically leading to a higher overall score (this has yet to be determined experimentally).
Weaknesses:
  • The normative data study only provided a mean score for any given age group, along with the corresponding standard deviation. To assess quickly and efficiently, it may have been more effective to provide the reader with a range of scores for each age group.
  • The reliability study used inexperienced students as the assessors.

Additional References:

  1. 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; 2:147-158.
  2. O’Connor FG et al. Functional movement screening: predicting injuries in officer candidates. Med Sci Sports Exerc. 2011; 43: 2224-2230