Longitudinal change in spousal similarities in mental health: Between-couple and within-couple perspectives.
Bibliographic record
Abstract
Research based on between-couple perspectives indicate that spouses share similarities in a range of psychosocial characteristics. In this study, the authors add to existing research by examining spousal similarities in mental health and its time-related change from both between-couple and within-couple perspectives. The authors apply latent growth models to 9-wave annual longitudinal data obtained from 3,410 adult couples in the Household, Income and Labor Dynamics in Australia Survey (HILDA; Mage wives = 48 years, Mage husbands = 50 years). In a first step, the authors corroborate extant findings from a between-couple perspective that spouses show considerable similarities in levels of and changes in mental health. In a second step, they calculate a within-couple similarity index (i.e., using absolute difference scores calculated based on the 2 partners' mental health). The authors show that mental health ratings between partners within a given spousal unit differed considerably (0.88 SD) and that these differences remained relatively stable over time. Examining between-couple differences in within-couple similarity revealed that larger discrepancies were associated with lower mental health (of individual partners), chronic health conditions, less marital satisfaction, and elevated risks for dissolution of the partnership. The authors discuss ways to integrate this counterintuitive set of findings with research originating from between-couple and within-couple perspectives, argue that a certain degree of spousal differences-if kept within certain bounds-can be adaptive serving developmental and relationship functions, and suggest routes for future inquiry on spousal similarities.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".