‘Mental heAlth and well-being in rUgby pLayers’ (MAUL) study: an online survey of diverse cohorts of rugby union players internationally
Bibliographic record
Abstract
Introduction: Mental health and well-being is a relatively under-researched area in rugby, especially outside the elite men's game. Evidence suggests that physical activity and sports benefit mental health and well-being, and rugby provides health-enhancing moderate-to-vigorous physical activity. Objective: This cross-sectional study used an online approach and engaged national rugby governing bodies to understand adult rugby players' mental health and well-being and increase the diversity of the current evidence base. Results: 500 rugby players completed an online survey. 44% of participants identified as female, and 55% as male. The UK (67%), Ireland (15%) and South Africa (12%) were the countries with the highest representation. 71% of participants were amateur players, with elite players making up 20% of the population. 87% of players participated in contact forms of the game, with 9% predominantly playing non-contact rugby. Over 50% of participants reported that rugby impacted 'extremely' positively on both their mental health and well-being. Based on the Kessler psychological distress scale (K10), 57.8% of all respondents belonged to the 'psychologically well' group. Males were more likely to belong to this group than females (p=0.01). Non-contact and amateur players had lower scores of psychological distress than contact and professional players (p=0.001 and p=0.006), respectively. Non-contact players had higher well-being (Short Warwick-Edinburgh Mental Well-being Scale) scores than contact players (p<0.001). Conclusion: This study provides new insights into the mental health and well-being of a diverse group of rugby players.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".