Musculoskeletal Injuries Among Young, Recreational, Female Dancers Before and After Dancing in Pointe Shoes
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to determine the prevalence, number, and distribution of musculoskeletal injuries among young, recreational, female dancers before and after dancing in pointe shoes and to explore possible risk factors. METHODS: Thirty-one female, nonprofessional ballet dancers, eight to 20 years of age, were recruited from two dance studios in London, Ontario. Participants completed a descriptive questionnaire and reliable examiners performed stress, stability, and laxity tests. RESULTS: The prevalence of instability for nonpointe and pointe groups was 0% and 8% for the knee and 17% and 3% for the ankle, respectively (a nonsignificant difference). The mean number of painful sites was 1.3 (SD = 1.9) and 2.9 (SD = 2.1) for nonpointe and pointe groups, respectively (p = 0.04). The only variable that, in part, predicted the number of painful sites was the number of years of having danced ballet. CONCLUSIONS: The generalizability of these results is limited by the small sample size. Additional prospective research with larger samples, inclusion of dancers who are just beginning to dance in pointe shoes, and consideration of level of exposure and the intensity of both dancing and other physical activity is indicated before prevention programs can be planned and tested.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".