Longitudinal effects of pandemic stressors and dyadic coping on relationship satisfaction during the <scp>COVID</scp>‐19 pandemic
Bibliographic record
Abstract
Abstract Objective This study examined changes in relationship satisfaction during the COVID‐19 pandemic and the moderating roles of financial strain, perceived threat of COVID‐19, and dyadic coping. Background The systemic‐transactional model of dyadic coping posits that relationship satisfaction varies as a function of the stressors partners face and their engagement in dyadic coping. Method About 188 partnered adults completed questionnaires at three time points during the initial confinement period of the COVID‐19 pandemic and at a 20‐month follow‐up. Results Relationship satisfaction increased during the first confinement period and returned to its baseline level at the 20‐month follow‐up. Greater financial strain and perceived threat of COVID‐19 were associated with poorer relationship satisfaction over time. Dyadic coping buffered the negative impact of financial strain on relationship satisfaction during the initial confinement period, but not 20 months later. Conclusions Most individuals were resilient to the effect of pandemic stressors on relationship satisfaction. The buffering effect of dyadic coping was observed during the initial confinement period when access to support resources outside the family unit was curtailed. Implications Intervention efforts to promote dyadic coping and financial well‐being for couples may be especially helpful in the context of strict confinement measures.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".