Moving to Action: The Effects of a Self-Regulation Intervention on the Stress, Burnout, Well-Being, and Self-Regulation Capacity Levels of University Student-Athletes
Bibliographic record
Abstract
Background: The purpose of this study was to implement and assess the impact of a person-centered, feel-based self-regulation intervention on the stress, burnout, well-being, and self-regulation capacity of eight university student-athletes experiencing burnout. This was warranted given the negative outcomes associated with athlete burnout, the scarcity of burnout research focusing on student-athletes, and the lack of intervention research addressing burnout in sport. Method: A mixed methods design including questionnaires administered at four time points during the athletic season, pre- and postintervention interviews, and multiple intervention sessions was used. Results: Repeated-measures ANOVAs revealed that stress and burnout levels significantly decreased, and well-being and self-regulation capacity levels significantly increased as the intervention progressed. The qualitative data supported these findings. Conclusion: It appears that university student-athletes participating in this type of intervention can learn to effectively manage themselves and their environment to reduce adverse symptoms and improve optimal 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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".