How Does Community-Based Housing Foster Social Participation in Older Adults: Importance of Well-Designed Common Space, Proximity to Resources, Flexible Rules and Policies, and Benevolent Communities
Bibliographic record
Abstract
As supporting active and healthy aging calls for different community-based housing alternatives, integrated knowledge of their impacts on older adults' social participation is required. This study aimed to explore how community-based housing fostered social participation in older adults. A scoping review was used to systematically identify relevant studies according to 32 keywords in 8 electronic databases. Published during 2000-2021, the 46 studies were carried out in North America, Europe, Oceania, and Asia, documenting older adults' social participation in six community-based housing models. Targeting different clienteles, these models mainly promote older adults' social participation by providing: 1) accessible common space in a design favorable to social interactions; 2) proximity to resources; 3) flexible rules and policies that facilitate residents' interactions with not only co-residents but community neighbors; and 4) benevolent communities. These results highlight the interactions between the physical and social environments; they suggest the importance of building benevolent communities as well as of sharing resources among residences and local communities to create a supportive living and neighborhood environment for active and healthy aging. Future studies should further explore the role of different stakeholders in developing benevolent communities by considering the dynamics between the person and the environment.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".