OLDER ADULTS’ PERSPECTIVES OF COGNITIVE HEALTH PROMOTION AND ACTIVITIES TO AMELIORATE COGNITIVE DECLINE
Bibliographic record
Abstract
Abstract There is a paucity of research on cognitive health promotion from the perspective of older adults, especially within a rural context. However, dementia and cognitive impairment are more prevalent among rural older adults than urban older adults. This presentation has two objectives: to examine cognitive health promotion from the perspective of rural older adults; and 2) to identify key activities associated with ameliorating cognitive decline in rural communities. Drawing on a community-based participatory research approach, data was collected through two waves of semi-structured interviews with the same group of 42 older adults in rural Saskatchewan, Canada. Guided by lay theory and cultural schema theory, data was coded using thematic analysis. In describing cognitive health promotion, four key areas emerged including emotional health, intellectual health, social health, and functional health. In discussing activities to support cognitive health promotion, participants emphasized the importance of thinking positively, keeping your brain active, mingling with others, and managing your daily affairs. Focusing on older adults’ perceptions of cognitive health promotion provides valuable information to advance knowledge of key strategies and activities to support cognitive health. In developing effective strategies to promote cognitive health, it is essential to engage in collaborative research and partnerships with older adults.
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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 | 0.003 | 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 | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".