THE MISSING PIECE IN AGING IN PLACE RESEARCH: PARTICIPATORY RESEARCH WITH OLDER ADULTS LIVING IN THE COMMUNITY
Bibliographic record
Abstract
Although research on aging in place in the community context has significantly increased in the last decade, few studies have adopted a participatory method engaging older adults in the conception, conduct and/or knowledge translation in a project. Also, there is limited empirical evidence based on older adults’ subjective experiences of the social and physical environments, and their influence on the processes of aging in place, e.g., experience of place, mobility, social participation. This symposium presents a set of participatory research projects on aging in place with diverse groups of older adults with different levels of functional abilities and mobility capacities living in different types of communities across North America. They include cohousing projects, naturally occurring retirement communities (NORC), community-dwelling residences, senior living facilities and official language minority communities in urban, suburban and rural areas. Presentations highlight a wide range of participatory research methods including photovoice and photo-elicitation, video-making, user-led audit tools, focus groups, and community forums. They explore factors and processes related to older adults’ experience of “aging in place” versus being “stuck in place.” Participatory research with diverse groups of older adults living in the community provides the opportunity to meaningfully engage them in processes that have direct influence on the services and resources they need to age in their home and community as long as possible. Lessons learned for effective engagement of older adults in the processes and outcomes of research on aging in place are discussed. Implications for knowledge translation and policy changes are highlighted.
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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 | 0.125 | 0.091 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.020 | 0.027 |
| Scholarly communication | 0.012 | 0.015 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".