Observed Support in Marriage: The Roles of Support Seeking Behaviour and Stress Reactivity
Bibliographic record
Abstract
Whether and how spouses seek and provide support in marital discussions is not clearly understood, and stress reactivity (e.g., tension or irritability) may interfere with effective support behaviours.ln a sample of newlywed couples (N = 145), path analyses indicated negative within-spouse associations between positive and negative helpee (e.g., appropriately or inappropriately requesting help) and helper behaviours (e.g., expressing empathy or criticism).Helpee positive behaviours positively predicted helper positive behaviours, and helpee negative behaviours positively predicted helper negative behaviours.Invariance analyses indicated that in comparison to helper wives, helper husbands were more likely to reciprocate positive wife helpee behaviours and less likely to reciprocate negative wife helpee behaviours.As expected, spouses' stress reactivity predicted husbands' and wives' negative behaviours, but only when couples discussed wives' worries.Contrary to prediction, wives' stress reactivity was less strongly associated with negative helpee behaviours when husbands were more tense or irritable; but, as expected, any negative wife helpee behaviour was more likely to be met with negative helper behaviours from their more tense or irritable husbands.Results suggest that husbands may be more appropriately responsive, and more likely to inhibit negative responses, than wives.ln addition, tense or irritable wives may be more likely to inhibit criticism or demands for support with their tense husbands.However, when wives do criticize or demand help, they are more likely to be met with contempt or defensiveness from their tense or irritable husbands.Overall, this study demonstrates the importance of examining spousal support within a dyadic framework, focusing on the roles spouses play in support discussions, and identifying when physical and emotional reactions to stress may be important factors in spousal support.
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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 | 0.002 | 0.009 |
| 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".