Resilience, well-being, depression symptoms and concussion levels in equestrian athletes
Bibliographic record
Abstract
Purpose This paper aims to conduct the first cross-sectional survey on depression, Resilience, well-being, depression symptoms and concussion levels in equestrian athletes and to assess whether past concussion rates were associated with depression, resilience and well-being. Design/methodology/approach In total, 511 participants from Canada, Republic of Ireland, UK, Australia and USA took part in an international cross-sectional, online survey evaluating concussion history, depression symptoms, resilience and well-being. Findings In total, 27.1% of athletes met clinically relevant symptoms of major depressive disorder. Significant differences were shown in the well-being and resilience scores between countries. Significant relationships were observed between reported history of concussion and both high depression scores and low well-being scores. Practical implications Findings highlight the need for mental health promotion and support in equestrian sport. Social implications Results support previous research suggesting a need for enhanced mental health support for equestrians. There is reason to believe that mental illness could still be present in riders with normal levels of resilience and well-being. Originality/value This study examined an understudied athlete group: equestrian athletes and presents important findings with implications for the physical and mental health of this population.
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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 | 0.002 | 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 | 0.001 |
| 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".