Training Load, Pain Intensity, and Functioning Can Explain Injuries in Dancers: A Classification and Regression Tree...

Area of Science:

• Dance science
• Sports medicine
• Biopsychosocial health

Background:

• Dancer injuries pose significant challenges to artistic careers and well-being.
• Understanding the multifactorial nature of these injuries is crucial for effective prevention and management.

Purpose of the Study:

• To identify biopsychosocial factors contributing to injuries in dancers.
• To utilize Classification and Regression Tree (CART) analysis for injury prediction.

Main Methods:

• A cross-sectional study involving 61 dancers across various genres.
• Assessment of sociodemographic data, pain intensity (NPRS), anxiety (BAI), and functioning (WHODAS 2.0).
• CART analysis to determine injury predictors, adjusted for BMI.

Main Results:

• Training load emerged as the primary injury predictor, explaining 52.4% of injuries at >11.5 hrs/wk.
• Combined high training load and pain intensity (NPRS > 6.5) explained 100% of injuries.
• Lower training load (<11.5 hrs/wk) and better functioning (WHODAS < 68.0) were associated with no injury.

Conclusions:

• Training load, functioning, and pain intensity are significant factors associated with dancer injuries.
• Established cutoff points for these factors aid in injury risk assessment.
• Incorporating functioning (structure, activity, social participation) emphasizes patient-centered care in dance medicine.