Lifetime Prevalence of Verbal, Physical, and Sexual Abuses in Young Elite Athletics Athletes
Bibliographic record
Abstract
To examine prevalence of verbal, physical, and sexual abuses in young elite athletes, a cross sectional questionnaire-based survey was conducted during the World Athletics under 20 World Championships. This questionnaire aimed at distinguishing between abuses perpetrated in the context of Athletics from those which were unrelated to Athletics. Four hundred and eighty athletes (52.3%, male) from North America, South America, Europe, Africa, Asia, and Oceania took part in the electronic anonymous survey. Outside Athletics setting, no gender difference was found for the prevalence of verbal, physical, and sexual abuses. However, 45 males (18% of the male population) and 34 females (15% of the female population) athletes reported sexual abuse. Asian athletes reported a slightly higher rate of sexual abuse; three quarters of them being non-touching abuses. Inside Athletics setting, no gender difference was found for the prevalence of verbal, physical, and non-touching sexual abuses. However, 58 males (23%) and 47 females (21%) reported verbal abuses. Thirty-one males (12%) and 20 females (9%) reported physical abuses, whereas 30 males (12%) and 17 females (7%) reported sexual abuses. Physical abuses were slightly more frequent in Asia and in Africa and less frequent in South America. Sexual abuses inside Athletics also differed over regions, and were unexpectedly twice more frequent than expected in Asia and slightly less frequent than expected in Europe. Friends and partners were identified as the more frequent (>50%) abusers outside or inside the Athletics settings, whereas outside Athletics and inside Athletics, coaches were identified as sexual abuse perpetrators in 8 and 25% of cases, respectively. The prevalence of verbal, physical, or sexual abuses is high but consistent with what has been reported in United Kingdom, Norway, Canada, and Sweden at national level in recreational or elite athletes. Sexual abuse, including touching or penetrative abuses, occurred significantly more often in male athletes when compared to female athletes. This finding invites healthcare and social workers, and policymakers to also consider the risk of sexual abuse of young male athletes in Athletics. These results also call for longitudinal studies on young elite athletes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".