Relationships Between Common Preseason Screening Measures and Dance-Related Injuries in Preprofessional Ballet Dancers
Bibliographic record
Abstract
OBJECTIVE: To examine modifiable and nonmodifiable factors for associations with dance-related injury among preprofessional ballet dancers over 5 academic years. DESIGN: Prospective cohort study. METHODS: Full-time preprofessional ballet dancers (n = 452; 399 female; median age [range], 15 years [11-21]) participated across 5 academic years at a vocational school. Participants completed baseline screening and online weekly injury questionnaires including dance exposure (hours/week). Zero-inflated Poisson regression models were used to examine associations between potential risk factors measured at baseline and self-reported dance-related injury. RESULTS: In count model coefficients, left one leg standing score (log coefficient estimate, −0.249 [95% CI: −0.478, −0.02]; P = .033) and right unipedal dynamic balance time (log coefficient estimate, −0.0294 [95% CI: −0.048, −0.01]; P>.001) carried a protective effect with increased years of training when adjusted for Athletic Coping Skills Inventory (ACSI) score. A significant association was found for left unipedal dynamic balance time and dance-related injury (log coefficient estimate, 0.013 [95% CI: 0.000, 0.026]; P = .045) when adjusted for years of training and ACSI score. There were no significant associations between dance-related injury and ankle and hip range of motion, active straight leg raise, or Y Balance Test measures. CONCLUSION: When adjusted for years of previous dance training and psychological coping skills, there was a significant association between limb-specific lumbopelvic control and dynamic balance tasks, as well as self-reported dance-related injury in preprofessional ballet. J Orthop Sports Phys Ther 2023;53(11):703-711. Epub 3 October 2023. doi:10.2519/jospt.2023.11835
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".