A Scoping Review of Innovative Housing for Older Adults: Focus on Homesharing, Cohousing, NORC-SSPs, and Villages
Bibliographic record
Abstract
Abstract This scoping review explores the benefits, and challenges of major innovative housing and service models for older adults. Several countries are prioritizing housing and service innovation for older adults to address the limitations of traditional market housing in meeting their housing needs and challenges. This study contributes to this issue by reviewing peer-reviewed and grey literature on four well-established innovative housing and service models: cohousing, homesharing, Naturally Occurring Retirement Community Supportive Services Programs (NORC-SSPs), and Villages. Based on the findings synthesized from 65 sources, a pair-wise comparison of (i) cohousing and homesharing; and (ii) NORC-SSPs and Villages was conducted on the basis of: (a) financial aspects (e.g., affordability); and (b) psychosocial aspects (e.g., social interaction and engagement, intergenerationality, autonomy and interdependence, safety, diversity and inclusivity); and (c) long-term sustainability. While there were several financial and psychosocial benefits related to each model, the following challenges were identified that need to be addressed to further improve the relevance and effectiveness of these models: (i) lack of funding and resources to support NORC-SSPs and Villages; (ii) inter-resident conflict in homesharing and cohousing; (iii) limitations of informal support provided by fellow-residents in meeting the needs of older adults with complex needs in all four models; and (iv) lack of inclusivity and sociocultural diversity in cohousing and Villages. By integrating research on older adults’ housing needs and innovative solutions, the findings of this study could guide future housing initiatives that seek to adopt these innovative models by highlighting their strengths, while recognizing areas for improvement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".