Elite Ice Hockey Players’ Well-Being: A Scoping Review
Bibliographic record
Abstract
As mental health has gained prominence in recent years, elite ice hockey players have shared their experience of psychological problems, including adverse alcohol use, anxiety, depression, distress, eating disorders, and sleep disturbances. Mental health remains a sensitive issue for ice hockey players, as stigma, a strong hockey culture, lack of mental health literacy, and negative past experiences with seeking help constitute barriers to seeking support. This scoping review aims to identify the psychological factors contributing to elite ice hockey players' well-being. After screening the titles and abstracts of three databases within a 2002-2025 timeframe, a total of 517 articles were retrieved. Seventeen articles targeting ice hockey athletes over 14 years of age competing at an elite level were selected. Three main categories emerged from the included studies: anxiety and depressive symptoms, motivational variables, and coping strategies at different career stages. Factors such as retirement, concussions, social support, parenting style, task-approach goals, and task-oriented behavior were influential components to the well-being and mental health of elite ice hockey players. Using the Lazarus and Folkman model, the identified psychological factors may help athletes and various actors surrounding them to better understand athletes' well-being.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
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; both teacher heads agree on what is shown here.
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".