WIDOWHOOD STATUS AS A RISK FOR COGNITIVE DECLINE AMONG KOREAN OLDER ADULTS
Bibliographic record
Abstract
Previous studies have demonstrated that spousal bereavement has negative impacts on the survivor’s mental health. However, few studies have examined its impact on the survivor’s cognitive function in later life. Therefore, the purpose of this study was to investigate the longitudinal effect of widowhood status on cognitive change among older adults. The study sample was drawn from a nationally representative data set, the Korean Longitudinal Study of Aging (KLoSA), and the final sample consisted of 5,529 Korean adults aged 60 and over at baseline. As a dependent variable, cognitive function was measured by the Korean version of the Mini-Mental State Exam (K-MMSE) score. Widowhood status was measured as a time-varying dichotomous variable. Using five waves of KLoSA, longitudinal trajectories of cognitive change from 2006 to 2014 were examined using growth curve models. Adjusting for gender, education, self-rated health, chronic conditions, and depression, results from growth curve models showed that widowed older adults had significantly lower cognitive function than their counterparts (p<.001). Cognitive function declined over time, and the rate of decline in cognitive function was steeper among the widowed than among the non-widowed (p<.001). These findings suggest that widowhood is detrimental for late-life cognitive decline. Further research is needed to understand the mechanisms underlying this relationship. Policy and practice implications are discussed accordingly.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".