Retirement or no Retirement? The Decision’s Effects on Cognitive Functioning, Well-Being, and Quality of Life
Bibliographic record
Abstract
This study addressed the psychological effects on personal well-being and reported quality of life of staying professionally active in late adulthood, and to what extent years of professional inactivity modulates cognitive abilities. DESIGN AND METHODS: We collected data on 262 elderly adults, 129 of whom were professionally active elderly adults (who voluntarily maintained their professional activity after the age of retirement) and 133 of whom were retired adults, in a set of experimental tasks to measure basic cognitive resources. The study took place during the first quarter of 2020. RESULTS: Active elderly people performed better on cognitive tasks that assessed attention, memory, and solving abilities and also reported more satisfaction with life and their current work. Multiple linear regressions analyses revealed that years of inactivity were associated with lower cognitive performance. Mentally demanding jobs were significantly associated with memory performance, but not with attention and planning. CONCLUSIONS: An involuntary separation from professional activity in the beginning of late adulthood may cause a deeper decline of cognitive functions, poorer adaptive adjustment to the aging process, and higher dissatisfaction with the period of life the individual is going through.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".