Dynamic links of cognitive functioning among married couples: Longitudinal evidence from the Australian Longitudinal Study of Ageing.
Bibliographic record
Abstract
Development does not take place in isolation; close others form an important dyad for exploring interrelationships. To examine spousal interrelations in level and change of cognitive functioning in old age, the authors applied dynamic models to 11-year longitudinal data of, initially, 304 married couples from the Australian Longitudinal Study of Ageing (aged 64-98 years at Time 1; M = 76 years). Findings revealed that perceptual speed for husbands predicted subsequent perceptual speed decline for wives (time lags of 1 year). There was little evidence for the opposite unidirectional effect or a bidirectional association between husbands and wives. Potential covariates (age, education, medical conditions, functional limitations, and depressive symptoms) did not account for differential lead-lag associations. A similar, though less pronounced, pattern was found for memory, which held except when functional limitations were controlled. Findings suggest that late-life cognitive development is not solely a product of intraindividual resources and are consistent with conceptual notions that development actively influences, and is influenced by, contextual factors such as close relationships. The authors discuss possible underlying mechanisms and further steps to substantiate the findings.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".