Thriving, Depleted, and At-Risk Canadian Coaches: Profiles of Psychological Functioning Linked to Self-Regulation and Stress
Bibliographic record
Abstract
The purposes of this study were to (a) identify profiles of psychological functioning based on burnout and well-being indices within a sample of 250 Canadian developmental and high performance sport coaches, and (b) investigate whether coaches in these profiles differed in their capacity to self-regulate and their perceptions of stress. Using a two-stage cluster analysis, three profiles of psychological functioning were identified: (a) thriving (n = 135, characterized by relatively low burnout and relatively high well-being), (b) depleted (n = 36, characterized by relatively high burnout and relatively low well-being), and (c) at-risk (n = 79, characterized by relatively high burnout and moderate well-being). Follow-up analyses revealed that coaches within the thriving profile reported significantly higher self-regulation capacity and lower perceived stress than coaches in the at-risk and depleted profiles, while depleted coaches reported significantly higher perceived stress than at-risk coaches. Moreover, longer coaching hours and remuneration for one’s coaching also differentiated depleted from thriving coaches. Findings are discussed in light of the dual-continua model of mental health and practical recommendations are put forth to help coaches strengthen their capacity to self-regulate and manage their perceptions of stress to optimize psychological functioning.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".