Leisure practice and its relations to cognitive vitality for seniors attending community organizations
Bibliographic record
Abstract
The purpose of this study was to explore the relations between certain dimensions of leisure practice and cognitive vitality in seniors and identify which of their sociodemographic and health characteristics (SHC) are related to leisure practice. A cross-sectional analysis of leisure practice, cognitive performance, self-perceived memory and SHC was performed among 294 French-speaking Canadian seniors attending community centres (255 women, average age: 71), by multiple linear regressions and partial correlations controlled for SHC. Outcomes from the project show that the diversity of leisure was related to the Montreal Cognitive Assessment and the California Verbal Learning Test, the frequency of cognitive leisure was associated to the Stroop Test, and the frequency of social leisure showed no significant association. “Paper and pencil games”, “computer use” and “helping a sibling” were related to various cognitive tests. Frequency of leisure (total) was related to gender and education, and diversity of leisure was related to education, age and depression. Study outcomes indicate that diversity of leisure was more related to cognitive vitality than frequency. Future studies should address leisure diversity as a way to promote cognitive vitality among seniors. Moreover, seniors’ characteristics should be considered when seeking to facilitate their participation in leisure activities.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".