Changes in well-being and relationship satisfaction in the years before and after marriage in a sample of New Zealand adults
Bibliographic record
Abstract
The well-being literature reveals that individuals experience increases in well-being leading up to marriage, followed by a return to pre-marriage levels shortly after marriage. In contrast, the relationship/marriage literature suggests that relationship satisfaction may steadily decline across time. However, it is unclear at what point relationship satisfaction may begin to decline. In the current study, we drew data from a nationally representative sample of diverse-aged adults to examine changes in well-being and relationship satisfaction prior to marriage, shortly after marriage, and post marriage. Data were utilized from 14-years of the New Zealand Attitudes and Values Study ( N = 1,520). Participants received annual surveys and reported their well-being (life satisfaction, subjective well-being, belonging) and relationship satisfaction. We examined whether getting married was associated with average within-person changes in well-being and relationship satisfaction across the years before marriage, shortly after marriage, and across the years following marriage. Event-aligned piecewise latent growth models found similar patterns of change across marriage for well-being (life satisfaction, subjective well-being) and relationship satisfaction. On average, well-being and relationship satisfaction increased leading up to marriage, dropped significantly shortly after marriage, and continued to decline following marriage. By integrating well-being and relationship/marriage literatures, these findings provide novel insights that for continuously partnered individuals, the course of well-being and relationship satisfaction change in similar ways leading up to marriage, shortly after marriage, and years following marriage.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".