Marital dissolution and cognition: The mediating effect of Aβ neuropathology
Bibliographic record
Abstract
Abstract INTRODUCTION Widowhood and divorce are extremely stressful life events that are associated with dementia, but the neurobiological underpinnings of this risk remain unknown. Amyloid beta (Aβ) load may explain influences of chronic stress, commonly seen in disruptive marital transitions, on cognitive decline. METHODS We examined whether Aβ quantified by tracer uptake on positron emission tomography mediates associations between marital dissolution and executive functioning and episodic memory performance using data from 543 cognitively normal (CN) participants from the Alzheimer's Disease Neuroimaging Initiative. RESULTS Marriage dissolution was associated with increased Aβ burden (β = 0.56; P = 0.015) and worse memory performance (β = –0.09; P = 0.003). Aβ levels were a significant mediator for the relationship between marriage dissolution and memory (average causal mediation effect = –0.007; P = 0.029). DISCUSSION Findings suggest that stressful life events, such as the dissolution of one's marriage, might exert an effect on Alzheimer's disease proteinopathy, which may subsequently influence poor cognition. Highlights Marital dissolution was associated with increased amyloid beta (Aβ) and memory declines. Aβ burden mediated associations between marital dissolution and memory. Findings were robust to potential non‐linear influences of age. Mediation results were not observed when stratifying marital groups by sex.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".