High support housing for people with serious mental illness in Canada: a scoping review
Bibliographic record
Abstract
Introduction: Mental health supportive housing aims to provide accommodation and support services to people with serious mental illness (SMI). Various supportive housing models have emerged in Canada post-deinstitutionalization, with heterogeneous and limited available information on congregate-based high support housing models (HSH) that provide 24/7 onsite supports. A registered scoping review was undertaken to identify the models and outcomes of HSH for people with SMI in Canada, including those exiting homelessness. Methods: Four academic databases (Medline, Embase, PsycINFO, CINAHL Plus) were searched, in addition to backward and forward citation searching and strategies for identifying grey literature. HSH configurations and outcomes (e.g., housing stability and preferences; physical and behavioral health; community integration, social support, and quality of life; costs) were investigated within the Canadian context. Results: A total of 27,180 academic articles and 164 grey literature reports were initially screened. Following full-text review of 337 academic and 109 grey literature articles, and citation searching, a total of 58 academic articles and 31 grey literature reports were included in the review. The characteristics, objectives, and outcomes of HSH models were mixed. Three nonexclusive types of HSH were identified: [1] custodial HSH, [2] recovery-oriented HSH, and [3] alternatives to hospital programs and other institutions. Most studies were uncontrolled, though there was preliminary evidence to support improvements in HSH residents' health and functioning; gains in social support, quality of life, and community integration; reductions in housing and service costs, particularly when compared to the cost of inpatient hospitalization; and satisfaction with living arrangements, supports, and relationships. However, the findings were not unequivocal, and the diversity of methodologies and HSH models limited further comparisons of outcomes between the different types of HSH. Conclusion: People with SMI experiencing complex and diverse needs can benefit from the services and supports provided by HSH. However, research on HSH is less developed compared to other, well-studied housing interventions. Further research on congregate housing settings, including their long-term outcomes and recovery-oriented practices, is warranted.
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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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.022 | 0.035 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".