Lifetime history of sexual and physical abuse among competitive athletics (track and field) athletes: cross sectional study of associations with sports and non-sports injury
Bibliographic record
Abstract
OBJECTIVE: To examine associations between lifetime sexual and physical abuse, and the likelihood of injury within and outside sport in athletes involved in competitive athletics. METHODS: A cross sectional study was performed among the top 10 Swedish athletics athletes using 1 year prevalence of sports and non-sports injuries as the primary outcome measure. Associations with sociodemographic characteristics, lifetime abuse history and training load were investigated. Data were analysed using simple and multiple logistic regression models. RESULTS: 11% of 197 participating athletes reported lifetime sexual abuse; there was a higher proportion of women (16.2%) than men (4.3%) (P=0.005). 18% reported lifetime physical abuse; there was a higher proportion of men (22.8%) than women (14.3%) (P=0.050). For women, lifetime sexual abuse was associated with an increased likelihood of a non-sports injury (OR 8.78, CI 2.76 to 27.93; P<0.001). Among men, increased likelihood of a non-sports injury was associated with more frequent use of alcoholic beverages (OR 6.47, CI 1.49 to 28.07; P=0.013), while commencing athletics training at >13 years of age was associated with a lower likelihood of non-sports injury (OR 0.09, CI 0.01 to 0.81; P=0.032). Lifetime physical abuse was associated with a higher likelihood of sports injury in women (OR 12.37, CI 1.52 to 100.37; P=0.019). Among men, athletes with each parents with ≤12 years formal education had a lower likelihood of sustaining an injury during their sports practice (OR 0.37, CI 0.14 to 0.96; P=0.040). CONCLUSIONS: Lifetime sexual and physical abuse were associated with an increased likelihood of injury among female athletes. Emotional factors should be included in the comprehension of injuries sustained by athletes.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".