126 Association between baseline factors and risk of injury amongst pre-professional dancers
Bibliographic record
Abstract
Background Few investigations utilize evidence-informed pre-participation evaluation, inclusive injury definitions, and prospective surveillance to identify risk factors for dance-related injury. Objective To identify baseline injury risk factors that may be associated with dance-related musculoskeletal (MSK) complaints in pre-professional dancers. Design Prospective cohort study. Setting Pre-professional ballet school; university dance program. Participants Dancers registered in full-time ballet [n=85, 77 females, median (range) age 15 years (11–19)] and contemporary [n=60, 58 females, 19 years (17–30)] training. Assessment of Risk Factors Pre-participation evaluation comprised of one-year injury history (yes/no), previous training (years), Athletic Coping Skills Inventory-28 (ACSI;score), body mass index (BMI;kg/m2), total bone mineral density (g/cm2), ankle plantar/dorsiflexion (degrees), active standing turnout (degrees), three lumbopelvic control tasks (high/low risk), unipedal dynamic balance (seconds), Y-Balance Test (cm). Weekly dance hours were self-reported throughout one academic year. Main Outcome Measurements Self-reported MSK complaints (any physical complaint leading to difficulties participating in dance, regardless of consequences) were captured weekly by online modified Oslo Sports Trauma Research Centre’s Questionnaire on Health Problems during academic year. MSK complaints were recorded (yes/no) for each participant for each week. Results Response rate was 99%, with 81% (117/145) of dancers reporting at least one MSK complaint. Of the 1521 complaints (19% first-time, 81% recurrent), ankle (22%), knee (21%), and foot (12%) accounted for majority. Potential factors were identified through systematic review and a generalized linear mixed model was used to analyze the binary outcome measure. Injury history [Odds Ratio (OR) 7.37; 95% CI (3.41, 15.91)] and previous week’s dance hours [OR 1.02; 95% CI (1.01, 1.03)] were significantly associated with MSK complaint. Conclusions Prevalence of MSK complaints amongst pre-professional ballet and contemporary dancers is high and significantly associated with injury history and training volume. Future studies implementing injury prevention should incorporate training load monitoring to address the dynamic, recursive nature of dance injury etiology.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".