65A Mixed-Method Investigation of the Factors Influencing Leisurely Activity Choice in Older Adults
Bibliographic record
Abstract
Background: The choice of social and recreational activities is important to support health and well-being with ageing (Stern, 2012). We explored the profile of older individuals partaking in social dancing and choir singing to gain insight on which characteristics best predict activity choice cross-sectionally (Ryan et al., 2013). Methods: 67 community-dwellers (age 60+) participated in the study. Thirty were social dancers and thirty-seven choristers. Questionnaires were administered on socio-demographic characteristics, health, and satisfaction with life. Cognitive performance was assessed by Montreal Cognitive Assessment and Colour Trail Making Test (TMT). Participants were also interviewed on their motivations and perceived benefits in taking part in these activities. Multiple logistic regression was used to determine predictive factors to partaking in the activities. Thematic analysis was used to analyse interviews data. Results: The regression model indicated that education, TMT performance, and, level of satisfaction with life were significant predictors of the likelihood to be either a social dancer or a chorister. Qualitative analyses indicated that while social dancers aimed to create social connections and experience enjoyment; for choristers, motivation was related to enhancing cognition and self-improvement. Conclusion: Choir singers presented higher scores on cognitive function and a higher level of education but, reported a lower level of satisfaction with life. The interviews indicated that dancers’ motivation pertained enjoyment, while choristers expected cognitive benefits, however, they felt the social pressure to perform. Further longitudinal investigations should elucidate whether motivations (e.g. cognitive fitness) and challenges (e.g. social pressure) in partaking in activities are mediators of outcomes such as cognitive benefits and satisfaction with life.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".