Predictive Value of Functional Movement Screening Combined with Physical Performance Measures for Musculoskeletal Injury Prevention in College Students: A 12-Month Prospective Cohort Study

Abstract

Background: Musculoskeletal Injuries (MSKIs) significantly impact the functional independence and academic consistency of college students. While the Functional Movement Screen (FMS) is widely deployed to identify movement dysfunctions, its isolated prognostic utility remains highly controversial.

Objective: To determine whether combining the FMS with targeted physical performance measures improves the predictive accuracy for non-contact MSKIs in college students over a 12-month prospective timeline.

Methods: A prospective cohort study evaluated 384 healthy, physically active college students (aged 18-25 years). Baseline assessments included the FMS, Lower Extremity Y-Balance Test (YBT), core endurance tests (flexor, extensor, side planks), isometric hip abductor strength via hand-held dynamometry, ankle dorsiflexion Range Of Motion (ROM) using the weight-bearing lunge test, and single-leg hop test distance. Non-contact MSKIs tracking occurred weekly across 12 months. Multivariable logistic regression and Receiver Operating Characteristic (ROC) curve analysis evaluated predictive models.

Results: Over the 12-month tracking period, 98 participants (25.5%) sustained a verified noncontact MSKI. An isolated baseline composite FMS score ≤14 demonstrated poor discriminative capacity (AUC=0.58, Sensitivity=54.1%, Specificity=61.2%). The integrated multivariable prediction model comprising the FMS deep squat component (aOR=2.14), YBT anterior asymmetry (aOR=1.88), reduced core extensor endurance (aOR=1.05), and restricted ankle dorsiflexion (aOR=1.42) adjusted for prior injury history-demonstrated excellent discriminative performance (AUC=0.83, Sensitivity=81.6%, Specificity=78.3%).

Conclusion: Standalone FMS scores are insufficient for identifying musculoskeletal injury vulnerability in college students. Incorporating specific localized metrics of dynamic balance, joint mobility, and core endurance within a multi-factorial screening matrix yields a highly sensitive and clinically predictive injury-risk algorithm.

Keywords: Biomechanics; Injury Risk Stratification; Physical Therapy; Prehabilitation; Surface Electromyography

Citation

Panneerselvam P, Muthukrishnan P, Chellappa J, Suganya M. Predictive Value of Functional Movement Screening Combined with Physical Performance Measures for Musculoskeletal Injury Prevention in College Students: A 12-Month Prospective Cohort Study. WebLog J Phys Ther Rehabil. wjptr.2026.i0201. https://doi.org/10.5281/zenodo.22538240