Longitudinal associations of spousal support and strain with health and well‐being: An outcome‐wide study of married older U.S. Adults
Bibliographic record
Abstract
Abstract In the present study, we examined the prospective associations of both spousal support and spousal strain with a wide range of health and well‐being outcomes in married older adults. Applying the analytic template for outcome‐wide designs, three waves of longitudinal data from the Health and Retirement Study (n = 7788, Mage = 64.2 years) were analyzed using linear regression, logistic regression, and generalized linear models. A set of models was performed for spousal support and another set of models for spousal strain (2010/2012, t1). Outcomes included 35 different aspects of physical health, health behaviors, psychological well‐being, psychological distress, and social factors (2014/2016, t2). All models adjusted for pre‐baseline levels of sociodemographic covariates and all outcomes (2006/2008, t0). Spousal support evidenced positive associations with five psychological well‐being outcomes, as well as negative associations with five psychological distress outcomes and loneliness. Conversely, spousal strain evidenced negative associations with three psychological well‐being outcomes, in addition to positive associations with three psychological distress outcomes and loneliness. The magnitude of these associations was generally small, although some effect estimates were somewhat larger. Associations of both spousal support and strain with other social and health‐related outcomes were more negligible. Both support and strain within a marital relationship have the potential to impact various aspects of psychological well‐being, psychological distress, and loneliness in the aging population.
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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 | 0.003 |
| 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 | 0.000 |
| 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".