Ice Hockey Coaches’ Perceptions of Their Role in Supporting Athlete Mental Health
Bibliographic record
Abstract
Many coaches have reported not feeling well equipped to support and discuss mental health issues with their athletes. The purpose of this study was to understand elite ice hockey coaches’ perceptions of their role in supporting athlete mental health, along with their experiences in taking part in a mental health and suicide awareness program. Five coaches of elite 16- to 20-year-old ice hockey players who had taken part in a mental health and suicide awareness program for at least one season each participated in an individual, semistructured, open-ended interview. Data were analyzed using a reflexive thematic analysis. Results revealed that coaches perceived their role to entail integrating mental health considerations into their daily coaching practices, paying attention to signs of player distress, assessing risk in various situations, and referring players to health professionals when necessary. Overall, our findings offered insight into coaches’ perceived role in providing mental health support to athletes, as well as helping to identify strengths and areas to improve the mental health and suicide awareness program. Consequently, coaches are primed to be key players in helping to create a sport climate in which well-being is prioritized and is perceived as a catalyst to performance.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".