Exploring the relationship between coach-initiated motivational climate and athlete well-being, resilience, and psychological safety in competitive sport teams
Bibliographic record
Abstract
The purpose of this study was to investigate coach-initiated motivational climate and its relationship with athlete well-being, resilience, and psychological safety in competitive sport. In addition to independent relationships between task- and ego-related climates and the study outcomes, this research also explored the potential additive effects of task and ego climate together to understand if a task climate can buffer against the negative impacts of an ego climate. Self-report survey data were collected from competitive soccer players across Ontario, Canada ( N = 298; M age = 20.38; 58.72% male). Using multiple linear regression, a perceived task-related climate was a significant positive predictor of well-being ( ß = .33), resilience ( ß = .31), and psychological safety ( ß = .54, all ps < .001). A higher perceived ego-related climate was a significant negative predictor of psychological safety ( ß = −.23, p < .001), and not significantly related to well-being and resilience. Partial support for the additive effect of task- and ego-related climate together was found for psychological safety, but not well-being or resilience. Specifically, athletes in the latent profile characterized by average task and higher ego scored higher on psychological safety compared with lower task and higher ego climate perceptions. The increase in psychological safety between these two profiles was observed despite both having higher ego-related climates. Although future research is required, the findings offer meaningful contributions to theory and practice in the context of competitive soccer teams.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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".