The Influence of Dyadic Coping on Inflammation in the Context of Chronic Parenting Stress
Bibliographic record
Abstract
Social relationships are postulated to benefit health through direct and stress-buffering effects. Positive dyadic coping, a spousal support process in which a couple works together to cope with the stressors that one or both partners are facing, is associated with reduced psychological distress. The goal of the present study was to evaluate the association between dyadic coping and inflammation, which is elevated under chronic stress and increases risk for health threats. It was hypothesized that positive dyadic coping would buffer the impact of chronic stress on perceived stress, and in turn reduce inflammation. Forty-four parents of children with an Autism Spectrum Disorder completed questionnaires that assessed relationship satisfaction, social support, and dyadic coping. Daily diaries assessed the occurrence of child behavior problems. Circulating C-reactive protein (CRP) was assessed using ELISA on dried blood spots. Hierarchical linear regression models evaluated the main and interactive effects of child behavior problems, and positive and negative dyadic on circulating CRP. Moderated mediation analyses evaluated the conditional indirect effect of dyadic coping on circulating CRP through perceived caregiving burden. Positive dyadic coping, but not negative dyadic coping, was uniquely associated with circulating CRP. Positive dyadic coping, but not negative dyadic coping buffered the impact of chronic stress on perceived caregiving burden. However, perceived stress did not explain the association between positive dyadic coping and inflammation. These data suggest that positive dyadic coping is a unique interpersonal process that reduces psychological distress and inflammation. Future research should evaluate interventions aimed at improving positive dyadic coping and inflammation among couples experiencing chronic stress.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".