Olympic and Paralympic athletes’ perceptions of the Canadian sport environment and mental health
Bibliographic record
Abstract
While athletes can experience poor mental health, researchers often focuses on the personal factors that impact an athlete’s mental health. Such a narrow focus neglects the broader contextual factors, such as involvement within sport systems, that can impact athlete mental health. Purpose: The purpose of this project was to understand how elite sport training environments in Canada impact the mental health of athletes. Methods: Team Canada Olympic and Paralympic athletes (n = 32) from team and individual sports (water polo, basketball, rowing, athletics, swimming, gymnastics, and field hockey) each participated in one semi-structured interview. Data were analysed using thematic analysis. Results: Athletes identified environmental features that supported and detracted from their mental health, including: the provision of resources, social support, performance pressure, communication, language, and coaching. These features impacted athletes’ mental health experiences by influencing their perceptions of stigma, their perceptions of mental health as an organisational priority, their help-seeking behaviours, and the minimisation of their personal experiences. Discussion: Uncertainty and a lack of control were common features of the environment contributing to athletes’ perceptions of stress and negatively impacted their wellbeing, as did a lack of trust in support providers and negative coaching practices. While some environmental features impacted athletes’ mental health directly, many had an indirect impact on athletes’ mental health (e.g. led to the minimisation of personal mental health challenges). Identifying ways to enhance athlete autonomy and educate coaches about mental health and supportive coaching practices are important directions for future research and practice.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".