Perspectives of Persons with Memory Changes and Care Partners for Reducing Barriers to Community Wellness Programs
Bibliographic record
Abstract
Exercise and healthy diet can improve the well-being of community-dwelling persons with memory changes (PWMC) (including dementia) and care partners (CPs). Existing research demonstrates that PWMC and CPs benefit from nutrition and exercise for frailty and sarcopenia prevention. Yet, needs and preferences for wellness programs are still unknown. The objective of this eight-month online survey study was to explore PWMC (n=24) and CPs’ (n=46) perspectives on nutrition/exercise barriers, and preferences for program content and format to inform a community wellness program. PWMC self-reported, while CPs reported for themselves and their cared-for person with dementia (CPWD). Descriptive analyses revealed that 78% of PWMC, 64% of CPs, and 39% CPWDs were interested in a wellness program that combined nutrition and exercise. Content preferences were diverse (e.g., 45% of CPs were interested in yoga/Pilates, but only five percent of CPWD were interested). Over half of participants preferred online delivery for nutrition information (55% PWMC, 54% CP). Group fitness was popular for exercise among all groups. In addition, participants prioritized attending as dyads twice or more per week, closeness to home, reasonable cost, knowledgeable instructors, fun social environment, and beginner-friendliness. To conclude, flexibility in program content and format will meet diverse needs and preferences.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".