The Buffering Effect of Social Support on Hypothalamic-Pituitary-Adrenal Axis Function During Pregnancy
Bibliographic record
Abstract
OBJECTIVE: Recent studies suggest that effective social support during pregnancy may buffer adverse effects of maternal psychological distress on fetal development. The mechanisms whereby social support confers this protective advantage, however, remain to be clarified. The aim of this study was to assess whether individual differences in social support alter the covariation of psychological distress and cortisol during pregnancy. METHODS: Eighty-two pregnant women's psychological distress and cortisol were prospectively assessed in all three trimesters using an ecological momentary assessment strategy. Appraisal of partner social support was assessed in each trimester via the Social Support Effectiveness questionnaire. RESULTS: In multilevel analysis, ambulatory assessments of psychological distress during pregnancy were associated with elevated cortisol levels (unstandardized β = .023, p < .001). Consistent with the stress-buffering hypothesis, social support moderated the association between psychological distress and cortisol (unstandardized β = -.001, p = .039), such that the covariation of psychological distress and cortisol increased with decreases in effective social support. The effect of social support for women with the most effective social support was a 50.4% reduction in the mean effect of distress on cortisol and a 2.3-fold increase in this effect for women with the least effective social support scores. CONCLUSIONS: Pregnant women receiving inadequate social support secrete higher levels of cortisol in response to psychological distress as compared with women receiving effective social support. Social support during pregnancy may be beneficial because it decreases biological sensitivity to psychological distress, potentially shielding the fetus from the harmful effects of stress-related increases in cortisol.
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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 | 0.000 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".