The role of coping humor in the physical and mental health of older adults
Bibliographic record
Abstract
OBJECTIVES: This study examined the associations among coping humor, other personal/social factors and the health status of community-dwelling older adults. METHOD: Survey questionnaires were completed with 73 community-dwelling older adults. Included were measures of coping humor, spirituality, self-efficacy, social support and physical and mental health status. RESULTS: Correlations across all variables showed coping humor to be significantly associated with social support, self-efficacy, depression and anxiety. Forward stepwise regression analyses showed that coping humor and self-efficacy contributed to outcome variance in measures of mental health status. Contrary to expectation, neither social support nor spirituality contributed to the total outcome variance on any of the dependent measures. CONCLUSION: The importance of social support, self-efficacy and spirituality in determining the quality of life of older adults is well supported in the literature. Coping humor as a mechanism for managing the inevitable health stresses of aging has received less attention. This study shows that coping humor and self efficacy are important factors for explaining health status in older adults. Correlations among coping humor, self efficacy and social support suggest that a sense of humor may play an important role in reinforcing self-efficacious approaches to the management of health issues.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".