Marital quality and inflammation: The moderating role of early life adversity.
Bibliographic record
Abstract
OBJECTIVE: Although positive marital quality is usually associated with lower chronic low-grade inflammation, not everyone benefits equally from spousal support. Exposure to early life adversity (ELA) has been proposed as a factor that may impede the social buffering effect of positive social relationships. The goal of this study was to test whether ELA would moderate the impact of marital quality on inflammation. METHOD: This cross-sectional study examined 168 partnered middle-aged women who either were experiencing a current chronic caregiving stressor, raising an adolescent with an autism spectrum disorder or intellectual disability, or who had the normative parenting experience of raising a typically developing adolescent. Participants completed self-report questionnaires on marital satisfaction, dyadic coping, and perceived partner responsiveness to create a composite index of marital quality, and they filled out the Childhood Trauma Questionnaire to assess ELA exposure. Participants also provided plasma samples for the assessment of interleukin-6, tumor necrosis factor-α, and C-reactive protein, three circulating biomarkers of inflammation. RESULTS: ELA moderated the association between marital quality and inflammation. Among individuals who endorsed lower ELA exposure, there was a significant, negative association between marital quality and interleukin-6 and tumor necrosis factor-α levels. However, this association was attenuated and not statistically significant among participants who reported higher ELA exposure. This effect was independent of current chronic stress. CONCLUSIONS: These findings suggest that ELA may impair the social buffering effect of marital quality on inflammation. This impaired social buffering effect may be another mechanism through which ELA promotes sustained elevations in inflammation over time. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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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 | 0.000 | 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 | 0.001 |
| 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".