Association Between Previous Injury and Risk Factors for Future Injury in Preprofessional Ballet and Contemporary Dancers
Bibliographic record
Abstract
OBJECTIVES: To determine the prevalence of self-reported 1-year injury history and examine its association with preparticipation evaluation components aimed at predicting future injury risk (PPE-IP) among preprofessional ballet and contemporary dancers. DESIGN: Cross-sectional study. SETTING: Preprofessional ballet school, university contemporary dance program. PARTICIPANTS: Full-time preprofessional ballet and contemporary dancers. ASSESSMENT OF RISK FACTORS: Preparticipation evaluation consisted of the Athletic Coping Skills Inventory-28, body mass index, total bone mineral density, ankle range of motion, active standing turnout, lumbopelvic control, unipedal dynamic balance, and Y-Balance test. MAIN OUTCOME MEASURE: Self-reported 1-year history of dance-related medical attention and/or time-loss injury. RESULTS: A total of 155 ballet [n = 90, 80 females, median age 15 years (range 11-19)] and contemporary [n = 65, 63 females, median age 20 years (range 17-30)] dancers participated. Forty-six percent (95% confidence interval (CI), 38.4-54.6) reported a 1-year injury history. Self-reported injury history was not associated with any PPE-IP, however, an influence of age and psychological coping skills on the relationship between 1-year injury history and PPE-IP was identified. Multivariable analyses revealed that prevalence of 1-year injury history did not differ by age [referent group <15 years; 15-18 years: odds ratio (OR) 0.80 (95% CI, 0.35-1.79); >18 years: OR 0.69 (95% CI, 0.30-1.56)], or level of psychological coping skills [OR 1.35 (95% CI, 0.61-2.94)]. CONCLUSIONS: The prevalence of self-reported 1-year injury history among preprofessional ballet and contemporary dancers is high. Although measures of PPE-IP did not differ based on injury history, it is important that age and psychological coping skills are considered in future dance injury prevention and prediction research. LEVEL OF EVIDENCE: Level 3 evidence.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".