The Influence of Injury Definition on Injury Burden in Preprofessional Ballet and Contemporary Dancers
Bibliographic record
Abstract
Study Design Cohort study. Background Multiple operational definitions of injury exist in dance research. The influence that these different injury definitions have on epidemiological estimations of injury burden among dancers warrants investigation. Objective To describe the influence of injury definition on injury prevalence, incidence, and severity in preprofessional ballet and contemporary dancers. Methods Dancers registered in full-time preprofessional ballet (n = 85; 77 female; median age, 15 years; range, 11-19 years) and contemporary (n = 60; 58 female; median age, 19 years; range, 17-30 years) training completed weekly online questionnaires (modified Oslo Sports Trauma Research Centre questionnaire on health problems) using 3 injury definitions: (1) time loss (unable to complete 1 or more classes/rehearsals/performances for 1 or more days beyond onset), (2) medical attention, and (3) any complaint. Physical therapists completed injury report forms to capture dance-related medical attention and time-loss injuries. Percent agreement between injury registration methods was estimated. Injury prevalence (seasonal proportion of dancers injured), incidence rates (count of new injuries per 1000 dance-exposure hours), and severity (total days lost) were examined across each definition, registration method, and dance style. Results Questionnaire response rate was 99%. Agreement between registration methods ranged between 59% (time loss) and 74% (injury location). Depending on definition, registration, and dance style, injury prevalence ranged between 9.4% (95% confidence interval [CI]: 4.1%, 17.7%; time loss) and 82.4% (95% CI: 72.5%, 89.8%; any complaint), incidence rates between 0.1 (95% CI: 0.03, 0.2; time loss) and 4.9 (95% CI: 4.1, 5.8; any complaint) injuries per 1000 dance-hours, and days lost between 111 and 588 days. Conclusion Time-loss and medical-attention injury definitions underestimate the injury burden in preprofessional dancers. Accordingly, injury surveillance methodologies should consider more inclusive injury definitions. J Orthop Sports Phys Ther 2018;48(3):185-193. Epub 13 Dec 2017. doi:10.2519/jospt.2018.7542 Level of Evidence Symptom prevalence study, level 1b.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".