Research Review By Erin Haske©

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Date Posted:

March 2012

Study Title:

Functional Movement Screening: Predicting Injuries in Officer Candidates

Authors:

O’Connor FG, Deuster PA, Davis J et al.

Author's Affiliations:

Uniformed Services University, Consortium for Health and Military Performance, Bethesda, MD; Department of Family Medicine, Womack Army Community Hospital, Fort Bragg, NC; Public Health Command (Prov), Aberdeen Proving Grounds, MD

Publication Information:

Medicine and Science in Sports and Exercise 2011; 43(12): 2224-2230.

Background Information:

Musculoskeletal injuries are among the leading causes of morbidity and disability in both civilian and military populations. In a military population, musculoskeletal injury leads to lost duty and training days, early attrition from service, and decreased combat effectiveness. Often researched, this population shows similar factors associated with injury when compared to civilian populations – low levels of daily activity and physical fitness, previous injury history, high running mileage, and cigarette smoking, for example.

It is theorized that functional movement and core stability programs may improve fitness and performance and assist in injury prevention. The Functional Movement Screen (FMS) is a series of movements designed to assess the quality of fundamental movement patterns through a series of functional movements and core stability exercises, and presumably identify functional limitations and asymmetries that may lead to injury. Previous studies investigating the FMS have shown that low FMS scores are associated with injury, and that scores can be improved with intervention.

This study’s purpose was to document the distribution of FMS scores within a military population, and to assess the predictive value of the FMS by comparing entry scores with subsequent injury during Officer Candidate School training. Subjects were chosen from two pools of candidates: those completing a six-week short cycle program (SC) and those completing a 10-week long cycle program (LC).

Pertinent Results:

Subjects were screened using a military physical fitness test and the FMS test.

The predictive value of the FMS scores was initially evaluated based on dichotomized data; one group contained subjects scoring ≤ 14, the other contained subjects scoring >14. Each group contained candidates from the SC and LC programs.
  • Candidates in the LC group with scores ≤ 14 were 1.65 times more likely to sustain an injury than those in the same group with scores >14 (95% confidence interval (CI) = 1.05-2.59, P = 0.03).
  • Candidates in the SC group with scores ≤ 14 were 1.91 times more likely to sustain an injury than those in the same group with scores >14 (95% CI = 1.21-3.01, P < 0.01).
  • In the LC and SC groups combined, subjects with scores  ≤ 14 were 1.5 times more likely to sustain an injury than those with scores >14 (P = 0.003).
  • Overall, 45.8% of subjects with scores ≤ 14 sustained some type of injury compared to 30.6% of those with scores >14.
In addition to the dichotomized data set, researchers also noticed a bimodal distribution to the data, where scores ≥ 18 were associated with higher cumulative injury incidences in addition those with scores ≤ 14. Injury risk was therefore evaluated in LC and SC groups scoring ≥ 18, 15-17, and ≤ 14.
  • In the LC group, scores ≥ 18 were associated with a cumulative injury incidence of 44.4% (risk ratio (RR) = 1.61).
  • In the SC group, scores ≥ 18 were associated with a cumulative injury incidence of 28.9% (RR = 1.32).
  • In the LC group, scores 15-17 were associated with a cumulative injury incidence of 29.3% (RR = 1.0).
  • In the SC group, scores 15-17 were associated with a cumulative injury incidence of 22.2% (RR = 1.0).
  • In the LC group, scores ≤ 14 were associated with a cumulative injury incidence of 52.8% (RR = 1.76).
  • In the SC group, scores ≤ 14 were associated with a cumulative injury incidence of 40.4% (RR = 1.88).
The relationship between FMS scores and physical fitness scores was also analyzed. Physical fitness scores were dichotomized into a high fitness group and a moderate fitness group; subjects in the moderate fitness group were 2.2 times more likely to have FMS scores ≤ 14 and significantly more likely to sustain an injury during the training period.

Receiver operating characteristic (ROC) curves were developed for any injury and overuse injuries for both physical fitness testing and FMS testing.
  • The area under the FMS ROC curve for any type of injury was 0.58. The odds ratio predicting risk of any type of injury was 2.0.
  • The area under the physical fitness testing ROC curve for any type of injury was 0.57. The odds ratio predicting risk of any type of injury was 2.1.
  • The area under the FMS ROC curve for overuse injuries was 0.52. The odds ratio predicting risk of overuse injuries was 1.4.
  • The area under the physical fitness testing ROC curve for overuse injures was 0.52. The odds ratio predicting risk of overuse injuries was 2.4.
Neither the FMS nor physical fitness testing curves provided a point that maximized specificity and sensitivity.

Clinical Application & Conclusions:

The results of this study show that in a homogenous cohort, FMS testing scores of ≤ 14 were associated with an increased risk of injury when compared to subjects scoring >14 on the FMS. Previous studies found FMS scores of ≤ 14 predicted serious injury, with injury rates 11.7x higher when compared to those with scores >14 (1).

It should also be considered that the physical fitness testing undertaken by the subjects was equally predictive of injury rates within the cohort. Due to the homogenous population volunteering for this study, it is difficult to extrapolate these results to a general population.

Additional review of the data revealed that subjects scoring ≥ 18 on the FMS were also at higher risk of injury during training. The authors suggest further study to address this result, and that future studies of this type be undertaken with a more heterogeneous population. Lastly, this study demonstrates the successful inclusion of the FMS test into a military medical in-processing.

Study Methods:

This study was a prospective cohort study completed with the informed consent of 874 male subjects, ages 18-30 years old. Subjects were enrolled in an officer candidate training program as part of a short cycle training program lasting six weeks, or a long cycle training program lasting 10 weeks.

All candidates underwent a briefing, and volunteering subjects underwent a medical screening, including a survey on health and exercise habits. They also completed an FMS screening and physical fitness test within one week of starting the training program.

Injury data was collected daily at one medical facility and were grouped by participating medical staff into several “types” including any injury and overuse injuries.

Survey data, physical fitness testing scores, injury data, and FMS scores were analysed using Statistical Package for Social Sciences (SPSS). Comparisons between LC and SC subjects were made using t-tests for continuous variables or χ2 for ordinal, nominal or discrete values. ROC curves were calculated by pairing FMS and PT scores with injury groups, i.e. any, overuse. χ2 statistics were used to evaluate differences in injury risk among those with FMS scores above and below cutoff (score of 14) and by physical fitness test scores. Associations between FMS scores and injury were evaluated separately in LC and SC groups due to differences in exposure and slight differences in training program.

Study Strengths / Weaknesses:

Strengths:
  • The study used a large cohort (n = 874); LC and SC groups were fairly well matched in size (n = 427 and n = 447, respectively).
  • FMS interrater reliability was maximized by certifying all members of the research team in the FMS prior to participating in the project
Weaknesses:
  • The cohort participating in this study was a relatively homogenous population of highly fit young men. This may result in a different distribution of FMS scores when compared to a more heterogeneous or general population.
  • The LC and SC groups, despite having comparable training volumes and intensities, had inherent differences in their training programs. The LC group had greater exposure time, while the SC group training is considered somewhat more condensed and intensive.

Additional References:

  1. Kiesel K, Plisky P, Voight M. Can serious injury in professional football be predicted by a preseason functional movement screen? N Am J Sports Phys Ther. 2007;2(3):147–50.
  2. Cook G, Burton L, Hogenboom B. The use of fundamental movements as an assessment of function – part 1. N Am J Sports Phys Ther. 2006;1(2):62–72.
  3. Cook G, Burton L, Hogenboom 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):132–9.
  4. Minick KI, Kiesel KB, Burton L, Taylor A, Plisky P, Butler RJ. Interrater reliability of the functional movement screen. J Strength Cond Res. 2010;24(2):479–86.