Longitudinal Associations of Need for Cognition, Cognitive Activity, and Depressive Symptomatology With Cognitive Function in Recent Retirees
Bibliographic record
Abstract
OBJECTIVES: This study investigated how interindividual differences in cognitive function are related to interindividual differences in the motivational trait of need for cognition, cognitive activity levels, and depressive symptomatology in a sample of young-old adults. METHOD: The ample comprised 333 recent retirees from the Concordia Longitudinal Retirement Project (mean age = 59.06 years at entry into study), assessed at 4 annual time points. Cognitive function was measured at 2 time points with the Montreal Cognitive Assessment. We used structural equation modeling to examine a longitudinal mediation model controlling for age, education, years since retirement, and prior occupation. RESULTS: Need for cognition was positively associated with change in cognitive status 2 years later. Variety of cognitive activities was positively associated with level of cognitive status 1 year later. Depressive symptomatology was negatively associated with level of cognitive status 1 year later. DISCUSSION: Our findings indicate that motivational disposition plays a significant role in enhancing cognitive status in retirees, as do variety of cognitive activities. Additionally, subclinical depressive symptomatology can negatively influence cognitive status in young-old retirees. These results have implications for the design of interventions aimed at maintaining the cognitive health of retirees.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".