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 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 | 0.001 | 0.002 |
| 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 | 0.000 | 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 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".