Evaluation of the Functional Movement Screen as an Injury Prediction Tool Among Active Adult Populations: A Systematic Review and Meta-analysis
Two articles on PainSci cite Dorrel 2015: 1. Sports Injury Prevention Tips 2. The Functional Movement Screen (FMS)
PainSci commentary on Dorrel 2015: ?This page is one of thousands in the PainScience.com bibliography. It is not a general article: it is focused on a single scientific paper, and it may provide only just enough context for the summary to make sense. Links to other papers and more general information are provided wherever possible.
The first review of the predictive validity of The Functional Movement Screen (FMS), with a predictably and resoundingly negative result based on mediocre data from 7 studies: “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.”
~ Paul Ingraham
original abstract †Abstracts here may not perfectly match originals, for a variety of technical and practical reasons. Some abstacts are truncated for my purposes here, if they are particularly long-winded and unhelpful. I occasionally add clarifying notes. And I make some minor corrections.
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.
- “Why screening tests to predict injury do not work-and probably never will … : a critical review,” Bahr, British Journal of Sports Medicine, 2016.
- “Predicting sport and occupational lower extremity injury risk through movement quality screening: a systematic review,” Whittaker et al, British Journal of Sports Medicine, 2016.
This page is part of the PainScience BIBLIOGRAPHY, which contains plain language summaries of thousands of scientific papers & others sources. It’s like a highly specialized blog. A few highlights:
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