Bringing reproductive, pelvic and breast health to light: insights from the Health of Elite Retired Australian female athletes survey (HER-Aus)
Bibliographic record
Abstract
OBJECTIVES: To describe the reproductive, pelvic and breast health of retired elite Australian female athletes. METHODS: Data were collected as part of a larger online cross-sectional survey that was cocreated with female athletes and disseminated to Australian retired elite (international-level and national-level) female athletes aged ≥18 years old and retired from elite competition ≥2 years. RESULTS: 199 retired female athletes (mean (SD) age 44 (10) years; retired for 16 (9) years; competed for 10 (5) years) across 31 different sports responded to the survey. 23% (46/199) experienced primary amenorrhoea, and 48% (95/197) reported ever experiencing secondary amenorrhoea. Of athletes with pregnancy difficulties (n=45), 42% reported menstrual cycle irregularity during their career. Of athletes who gave birth (n=98), 19% had difficulties conceiving, requiring fertility treatments. The majority of athletes reported current symptoms of urinary incontinence (70% (140/198)) and faecal incontinence (54% (106/197)). 18% (33/188) reported that they currently experience exercise-related breast pain; however, 87% (164/188) reported that breast pain never negatively impacts their current physical activity. CONCLUSIONS: A high prevalence of reported menstrual irregularities, pelvic floor dysfunction and fertility issues highlights the need for early prevention and intervention measures to address long-term health and the unique challenges faced by female athletes during and after their sporting careers.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".