Inequities in the Training Environment and Health of Female Golfers Participating in the 2022 International Golf Federation World Amateur Team Championships
Bibliographic record
Abstract
OBJECTIVE: To assess health problems and training environment of female golfers participating in the 2022 World Amateur Team Championships (WATC) and to compare golfers (a) with and without health problems prior the WATC and (b) living and training in countries ranking in the upper versus lower 50% of the team results at the 2022 WATC. DESIGN: Cross-sectional cohort study using an anonymous questionnaire. SETTING: International Golf Federation WATC. PARTICIPANTS: One hundred sixty-two female golfers from 56 countries. INTERVENTIONS: N/A. MAIN OUTCOME MEASURES: Golfers' answers on the presence and characteristics of health problems, their training environment, and to the Oslo Sport Trauma Research Centre Questionnaire. RESULTS: Almost all golfers (n = 162; 96%) answered the questionnaire. In the 4 weeks before the WATC, 101 golfers (63.1%) experienced 186 musculoskeletal complaints, mainly at the lumbar spine/lower back, wrist, or shoulder. Just half of the golfers (50.6%) performed injury prevention exercises always or often. More than a third (37.4%) of the golfers reported illness complaints and 32.5% mental health problems in the 4 weeks preceding the WATC. General anxiety, performance anxiety, and low mood/depression were the most frequent mental health problems. Golfers with injury complaints rated their daily training environment poorer. Golfers ranking in the lower 50% at the WATC had significantly less support staff, rated their training environment poorer, and had a higher prevalence of illness complaints and mental health problems. CONCLUSIONS: Effective illness and injury prevention programs should be implemented and better access to education and health support in the daily training environment provided.
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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 | 0.008 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".