Exploring the relationship between marital quality and cognitive function: A systematic review
Bibliographic record
Abstract
Cognitive function is an important indicator of healthy aging as it is central to maintaining functional independence, performing job-related tasks, decision-making, and improving quality of life. Therefore, researchers seek to identify biopsychosocial factors that can help preserve cognitive function in aging individuals. One such factor is the maintenance of good quality marital relationships. Research has consistently shown that married individuals fare better in terms of both physical and psychological health compared to their unmarried counterparts. However, being married is not universally beneficial - the quality of a marriage is also important to consider. To explore the issue further, we conducted a systematic review to examine the association between marital quality and cognitive function. PubMed, PsycINFO, and Scopus were searched for eligible articles examining any measure of marital quality and any cognitive outcome from the inception of each database to January 9th, 2024. Following two levels of citation screening by two independent reviewers, we included 15 articles representing 11 unique studies. Data were synthesized narratively following the Synthesis without Meta-Analysis guidelines and a risk of bias assessment was conducted using the Joanna Briggs Institute checklist. Most articles had a low risk of bias. Although some findings suggested more positive marital quality was associated with improved cognitive function, the results were not uniformly positive; some results were inverse or null, depending upon factors such as differences in study designs and measures of marital quality or cognition. This review is the first attempt to synthesize the literature on this topic. Our findings highlight that any examination of marital status and cognition should also consider contextual factors such as marital quality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".