Functional Movement Screening as a Predictor of Mechanical Loading and Performance in Dancers

Area of Science:

• Sports Medicine
• Biomechanics
• Dance Science

Background:

• Effective functional movement is crucial for injury prevention in dance.
• Understanding biomechanical responses during performance is vital for dancer health.
• The Functional Movement Screening (FMS) assesses fundamental movement patterns.

Purpose of the Study:

• To evaluate the efficacy of the FMS in predicting mechanical loading during the Dance Aerobic Fitness Test (DAFT).
• To identify specific FMS components that predict mechanical load in dancers.
• To inform dance performance optimization and injury prevention strategies.

Main Methods:

• Twenty-five university dancers underwent FMS assessment.
• Participants completed the DAFT while wearing a GPS-mounted triaxial accelerometer.
• Accelerometry data were analyzed to calculate PlayerLoad metrics (total, medial-lateral, anterior-posterior, vertical).
• Linear regression and stepwise hierarchical modeling were employed to correlate FMS scores with mechanical loading.

Main Results:

• The Deep Squat (DS) significantly predicted PlayerLoad vertical (PLv) and PlayerLoad anterior-posterior (PLap).
• The non-dominant Hurdle Step (HS) significantly predicted PLap.
• The FMS composite score predicted PLv.
• DS was the sole predictor for PLv and primary for PLap; non-dominant HS was primary for PLap.

Conclusions:

• The Deep Squat (DS) and non-dominant Hurdle Step (HS) can predict mechanical loading during the DAFT.
• The FMS composite score also predicts mechanical loading, offering a holistic measure.
• These findings support using FMS for injury risk assessment and performance enhancement in dancers.