The Relation Between Everyday Activities and Successful Aging: A 6-Year Longitudinal Study
Bibliographic record
Abstract
OBJECTIVES: Activity has long been thought to be related to successful aging. This study was designed to examine longitudinally the relation between everyday activities and indicators of successful aging, namely well-being, function, and mortality. METHODS: The study was based on the Aging in Manitoba Study, with activity being measured in 1990 and function, well-being, and mortality assessed in 1996. Well-being was measured in terms of life satisfaction and happiness; function was defined in terms of a composite measure combining physical and cognitive function. RESULTS: Regression analyses indicated that greater overall activity level was related to greater happiness, better function, and reduced mortality. Different activities were related to different outcome measures; but generally, social and productive activities were positively related to happiness, function, and mortality, whereas more solitary activities (e.g., hand-work hobbies) were related only to happiness. DISCUSSION: These findings highlight the importance of activity in successful aging. The results also suggest that different types of activities may have different benefits. Whereas social and productive activities may afford physical benefits, as reflected in better function and greater longevity, more solitary activities, such as reading, may have more psychological benefits by providing a sense of engagement with life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 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 | 0.001 | 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".