Connectedness, feeling At home, and joyful Play (CAP): A place-based wellness model for cognitive health promotion in the community by the community
Bibliographic record
Abstract
As populations age, leveraging community resources to reduce dementia risk is increasingly vital for brain health. Using community-based participatory research methods, we co-developed and tested a pilot program with older adults in Metro Vancouver, Canada, to better understand and address brain health needs in community settings. Over 12 focus groups, older adults provided input which led to a place-based wellness model ‘Connectedness, feeling At home, and joyful Play’ (CAP). The CAP model was incorporated into an 8-week feasibility study, testing various components of a multi-domain realist controlled trial (n = 78). Older adults were recommended various existing activities in the community based on their CAP profiles. A ‘Finding Meaning in Aging’ mindful discussion program was added in response to older adults’ feedback on current gaps. Path analysis of preliminary data suggests that total attendance (β = .196, p = .070) improved brain health at week 8 by increasing a sense of playfulness at week 4 (β = .284, p = .002). Mindfulness (β = .215, p = .046) improved brain health by increasing a sense of at-homeness (β = .227, p = .025). Both pre- and post-implementation feedback from older adults centred the importance of friendship in late life, specifically to address late-life losses. The community-generated CAP model shows promise for place-based cognitive health promotion.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".