Job stressors, strain, and psychological wellbeing among women sports coaches
Bibliographic record
Abstract
Despite a globally recognised need for inclusive diversity among sport workforces, women are underrepresented in the inherently stressful profession of sports coaching. This study aimed to work with women sports coaches to answer the following research questions: 1) What demographic and contract-related factors are associated with job stressors? 2) What associations exist between job stressors, strain, and psychological wellbeing (PWB) at work? Women coaches (n = 217) volunteered to complete the revised version of An Organizational Stress Screening Tool (ASSET). Path analyses identified several groups of coaches (head coaches, “other” coaches, disabled coaches) who experienced more job stressors related to their coaching work. They also highlighted the importance of workload stressors and their detrimental relationship with psychological and physical strain but positive relationship with sense of purpose (i.e., eudaimonic wellbeing). Collectively, these findings offer the first assessment of women coaches’ job stressors, strain, and PWB, and offer insight to factors that may influence coaches’ engagement with the profession. They also highlight intervention foci for national governing bodies that are seeking to protect the health and wellbeing of the women coaches within their workforce.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".