Coping strategies and distress reduction in psychological well-being? A structural equation modelling analysis using a national population sample
Bibliographic record
Abstract
BACKGROUND: Little is understood about of the role of coping strategies in psychological well-being (PWB) and distress for the general population and different physical and psychiatric disease groups. A thorough examination of these relationships may provide evidence for the implementation of public mental health promotion and psychiatric disease prevention strategies aimed at improving the use of positive coping approaches or addressing the causes and maintainers of distress. The present study using a structural equation modelling (SEM) approach and nationally representative data on the Canadian population investigates the relationships among PWB, distress and coping strategies and identifies major factors related to PWB for both the general population and diverse-specific disease groups. METHODS: Data examined were from the Canadian Community Health Survey of Mental Health and Well-being (CCHS 1.2), a large national survey (n = 36 984). We applied exploratory factor analysis (EFA), confirmatory factor analysis and SEM to build structural relationships among PWB, distress and coping strategies in the general population. RESULTS: Both SEM measurement and structure models provided a good fit. Distress was positively related to negative coping and negatively related to positive coping. Positive coping indicated a higher level of PWB, whereas negative coping was associated with a lower level of PWB. PWB was negatively related to distress. These same relationships were also found in the population subgroups. For the population with diseases (both physical and psychiatric diseases, except agoraphobia), distress was the more important factor determining subjective PWB than the person's coping strategies, whereas, negative coping had a major impact on distress in the general population. Strengths and limitations were also discussed. CONCLUSIONS: Our findings have practical implications for public psychiatric disease intervention and mental health promotion. As previously noted positive/adaptive coping increased the level of PWB, whereas negative/maladaptive coping was positively related to distress and negatively related to PWB. Distress decreased the level of PWB. Our findings identified major correlates of PWB in both the general population and population subgroups. Our results provide evidence for the differential use of intervention tactics among different target audiences. In order to improve the mental health of the general population public mental health promotion should focus on strategies that reduce negative coping at a population level, whereas clinicians treating individual clients should make the reduction of distress their primary target to maintain or improve patients' PWB.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".