The Associations of Dyadic Coping and Relationship Satisfaction Vary between and within Nations: A 35-Nation Study
Bibliographic record
Abstract
OBJECTIVE: Theories about how couples help each other to cope with stress, such as the systemic transactional model of dyadic coping, suggest that the cultural context in which couples live influences how their coping behavior affects their relationship satisfaction. In contrast to the theoretical assumptions, a recent meta-analysis provides evidence that neither culture, nor gender, influences the association between dyadic coping and relationship satisfaction, at least based on their samples of couples living in North America and West Europe. Thus, it is an open questions whether the theoretical assumptions of cultural influences are false or whether cultural influences on couple behavior just occur in cultures outside of the Western world. METHOD: In order to examine the cultural influence, using a sample of married individuals (N = 7973) from 35 nations, we used multilevel modeling to test whether the positive association between dyadic coping and relationship satisfaction varies across nations and whether gender might moderate the association. RESULTS: RESULTS reveal that the association between dyadic coping and relationship satisfaction varies between nations. In addition, results show that in some nations the association is higher for men and in other nations it is higher for women. CONCLUSIONS: Cultural and gender differences across the globe influence how couples' coping behavior affects relationship outcomes. This crucial finding indicates that couple relationship education programs and interventions need to be culturally adapted, as skill trainings such as dyadic coping lead to differential effects on relationship satisfaction based on the culture in which couples live.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".