The impact of leisure coping beliefs and strategies on adaptive outcomes
Bibliographic record
Abstract
Despite the recent growth of leisure coping research, it is not entirely clear: what aspects of leisure best contribute to coping with stress, and how the mechanisms that link leisure to adaptive outcomes operate. Another limitation of this research has been a tendency to examine leisure coping independent of general coping - coping not directly associated with leisure (e.g., problem-focused coping). To help overcome these limitations, the purpose of this study was to test two models of leisure and coping: (a) an independent model and (b) a buffer model, when the effects of general coping were taken into account. The findings of the study using police and emergency response service workers suggest that the effects of leisure on adaptive outcomes differ depending on the type of leisure coping used. Situation-specific leisure coping strategies (i.e., actual coping behaviors and cognitions available through leisure) were significantly associated with effectiveness of coping, satisfactory coping outcomes, and stress reduction (i.e., immediate adaptive outcomes), whereas enduring leisure coping beliefs (i.e., personality dispositions and beliefs about the role of leisure as a means of managing stress) significantly predicted better physical health (as a long-term outcome), irrespective of the level of stress experienced. Both types of leisure coping had significant 'main effects' supporting the independent model. Also, evidence of the buffer model was found for the effects of leisure coping strategies on moderating the detrimental impact of stress on physical health. Implications of leisure coping research for health promotion and lifestyle intervention are discussed.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".