Emotion dysregulation, performance concerns, and mental health among Canadian athletes
Bibliographic record
Abstract
Competitive athletes report symptoms of depression and anxiety at rates similar to or higher than the general population. There is some initial evidence that difficulties in emotion regulation are positively associated with depression, anxiety, and stress among university student-athletes; however, research on emotion dysregulation in sport contexts is limited. Therefore, the purpose of the current study was to examine the associations between emotion dysregulation, sport performance concerns, and symptoms of depression and anxiety among competitive athletes. We hypothesized that: H1) emotion dysregulation and H2) sport performance concerns would be positively associated with symptoms of depression and anxiety; and H3) performance concerns would moderate the association between emotion dysregulation and symptoms of depression and anxiety. Competitive athletes (n = 272) completed online measures of emotion dysregulation, sport performance satisfaction, and symptoms of depression and anxiety. Emotion dysregulation and sport performance concerns were directly positively associated with symptoms of depression and anxiety, supporting H1 and H2. The association between emotion dysregulation and mental health symptoms was not reliably moderated by sport performance concerns; thus, H3 was only partially supported. The results suggest that emotion dysregulation is linked to mental health symptoms and may be a useful target for intervention among competitive athletes.
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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 | 0.001 | 0.001 |
| 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) | 0.003 | 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".