Can Learning Self-Regulatory Competencies Through a Guided Intervention Improve Coaches’ Burnout Symptoms and Well-Being?
Bibliographic record
Abstract
While coaches are considered at risk of experiencing burnout, there is an absence of intervention studies addressing this syndrome. The purpose of this qualitative study was to conduct a self-regulation intervention with five Canadian developmental ( n = 2) and elite ( n = 3) sport coaches (three men, two women) experiencing moderate to high levels of burnout and examine the perceived impact of this intervention on their self-regulation capacity and experiences of burnout and well-being. The content analysis of the coaches’ outtake interviews and five bi-weekly journals revealed that all five of them learned to self-regulate more effectively by developing various competencies (e.g., strategic planning for their well-being, self-monitoring) and strategies (e.g., task delegation, facilitative self-talk). Four of the coaches also perceived improvements in their symptoms of burnout and well-being. Sport psychology interventions individualized for coaches are a promising means for helping them manage burnout and enhance their overall functioning.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".