RESUMO
BACKGROUND: The Functional Movement Screen (FMS™) is a popular test used by sports medicine professionals to identify dysfunctional movement patterns by analyzing mobility and stability during prescribed movements. Although the FMS™ has been a popular topic of research in recent years, normative data and asymmetries in college-aged students have not been established through research. PURPOSE: The objective was to determine normative FMS™ scores, report frequency counts for FMS™ asymmetries, and determine if the number of sports seasons and number of different sports an individual participated in during high school varied between university students that showed FMS™ identified asymmetries. STUDY DESIGN: Cross-sectional Study. METHODS: One hundred university students completed the FMS™ and an associated survey to determine which sport(s) and for how many seasons they participated in each sport(s) during high school. Total FMS™ scores were assessed as well as identifying the presence of an asymmetry during a FMS™ screen. An asymmetry within the FMS™ was defined as achieving an unequal score on any of the screens that assessed right versus left movements of the body. DATA ANALYSIS: Data analysis included descriptive statistics, Pearson correlation was utilized to investigate the relationship between number of sports played and number of sport seasons. Shapiro Wilk test for normality, and Mann Whitney U test was employed to investigate group differences in number of sports played. All analyses were conducted using SPSS software. RESULTS: Statistically significant correlations (r = .286, r2 = .08, p < 0.01) were found for both number of sport seasons and number of sports with FMS™ total score. In addition, participants without FMS™-detected asymmetries played significantly more seasons and more sports than their peers that presented asymmetries (U = 946.5, z = -1.98, p = 0.047). Finish with the actual p-value in parenthesis. CONCLUSION: Participating in multiple sports and multiple sport seasons during high school was associated with higher FMS™ total scores. Results suggest that participating in multiple sports and multiple sport seasons was associated with fewer asymmetries, which may decrease subsequent injury risk. LEVEL OF EVIDENCE: 3b.
RESUMO
CONTEXT: The Functional Movement Screen (FMS) is an assessment tool for quality of human movement. Research reports a significant difference between FMS scores of subjects who later experienced injury and those who remain uninjured. OBJECTIVE: To systematically review literature related to predictive validity of the FMS. From the aggregated data, a meta-analysis was conducted to determine the prognostic accuracy of the FMS. DATA SOURCES: PubMed, Ebscohost, Google Scholar, and the Cochrane Review databases were searched between 1998 and February 20, 2014. STUDY SELECTION: Identified studies were reviewed in full detail to validate inclusion criteria. Seven of the 11 identified studies were included. Articles were reviewed for inclusion criteria, then bias assessment and critical analysis were conducted. STUDY DESIGN: Systematic review and meta-analysis. LEVEL OF EVIDENCE: Level 3. DATA EXTRACTION: Extracted data included the following: study type, methodology, study subjects, number of subjects, injury classification definition, FMS cut score, sensitivity, specificity, odds ratios, likelihood ratios (LR), predictive values, receiver operator characteristic (ROC) analysis, and area under the curve (AUC). RESULTS: Overall bias for the included 7 studies was low with respect to patient selection. Quality assessment scored 1 study 5 of a possible 7, 2 studies were scored 3 of 7, and 4 studies were scored 2 of 7. The meta-analysis indicated the FMS was more specific (85.7%) than sensitive (24.7%), with a positive predictive value of 42.8% and a negative predictive value of 72.5%. The area under the curve was 0.587 (LR+, 1.7; LR-, 0.87; 95% CI, 0.6-6.1) and the effect size was 0.68. CONCLUSION: Based on analysis of the current literature, findings do not support the predictive validity of the FMS. Methodological and statistical limitations identified threaten the ability of the research to determine the predictive validity of FMS.
