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

Objective: To identify the biopsychosocial factors that explain injuries in dancers through use of a Classification and Regression Tree (CART) analysis.

Methods: Cross-sectional study performed with dancers over 18 years of age from dance schools in Brazil. Sociodemographic factors, pain intensity (numerical pain rating scale, NPRS), anxiety (Beck anxiety inventory, BAI), and functioning (WHO Disability Assessment Schedule 2.0, WHODAS) were assessed. We used a classification and regression tree (CART) analysis considering the occurrence of injury as a dependent variable, and the independent variables included age, training load, BAI, pain level, and WHODAS 2.0 score, adjusted for body mass index.

Results: The sample included 61 dancers (ballet, jazz, contemporary, tap, and urban dance), and they were mainly women (72.1%) with a mean age of 25.6 (± 5.79) years. Thirty-three percent presented dance-related musculoskeletal injuries in the last 12 months. The CART analysis showed that training load was the main associated factor, explaining 52.4% of injuries in dancers with a workload > 11.5 hrs/wk (p=0.05). When NPRS > 6.5 is added to the high load of training, these two variables explain 100% of the cases of injury (p=0.02). Training load < 11.5 hrs/wk and WHODAS 2.0 score < 68.0 were associated factors for no injury in dancers (80%; p=0.03).

Conclusions: Our results demonstrated that training load, functioning, and pain intensity were factors associated with injury in dancers, and we established cutoff points. The inclusion of functioning in the algorithm suggests the influence of structure, function, activity, and social participation on injury in dancers and strengthens the patient-centered care.