Health Problems of Professional Ballet Dancers: an Analysis of 1627 Weekly Self-Reports on Injuries, Illnesses and Mental Health Problems During One Season
Bibliographic record
Abstract
BACKGROUND: Several studies have investigated injuries of (pre-)professional ballet dancers, however most used a medical-attention and/or time-loss definition and did not analyse the prevalence of all health problems. The aim was to analyse the frequency and characteristics of all self-reported physical and mental health complaints (i.e. injuries, illnesses and mental health problems) of professional ballet dancers during one season. METHODS: Three professional ballet companies were prospectively monitored weekly during one season with the Performing artist and Athlete Health Monitor (PAHM). Numerical rating scales (ranging 0-10) were used for severity of musculoskeletal pain, all health problems and impairment of the ability to dance at full potential in the previous seven days. If dancers rated the severity of their health problems or their impairment greater than 0, they were asked to answer specific questions on the characteristics of each health problem. RESULTS: Over a period of 44 weeks, 57 dancers (57.9% female) filled in 1627 weekly reports (response rate of 64.9%), in which 1020 (62.7%) health problem were registered. The dancers reported musculoskeletal pain in 82.2% of the weeks. They felt that their ability to dance at their full potential was affected due to a health problem in about every second week (52.6%) or on at least 29.1% of the days documented in the weekly reports. Almost all dancers (96.5%) reported at least one injury, almost two thirds (64.9%) an illness and more than a quarter (28.1%) a mental health problem. On average, every dancer reported 5.6 health problems during the season. Most of the 320 health problems were injuries (73.1%), 16.9% illnesses and 10.0% mental health problems. Injuries affected mainly ankle, thigh, foot, and lower back and were mostly incurred during rehearsal (41.6%) or training (26.1%). The most frequent subjective reasons of injury were "too much workload" (35.3%), "tiredness/exhaustion" (n = 22.4%) and "stress/overload/insufficient regeneration" (n = 21.6%). CONCLUSION: Preventive interventions are urgently required to reduce the prevalence of health problems and especially injuries of professional dancers. Injury prevention measures should regard the balance of the load capacity of professional dancers and the workload in training, rehearsals and performances.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".