A Multiple-City RCT of Housing First With Assertive Community Treatment for Homeless Canadians With Serious Mental Illness
Bibliographic record
Abstract
OBJECTIVE: Housing First with assertive community treatment (ACT) is a promising approach to assist people with serious mental illness to exit homelessness. The article presents two-year findings from a multisite trial on the effectiveness of Housing First with ACT. METHODS: The study design was a randomized controlled trial conducted in five Canadian cities. A sample of 950 participants with serious mental illness who were absolutely homeless or precariously housed were randomly assigned to receive either Housing First with ACT (N=469) or treatment as usual (N=481). RESULTS: Housing First participants spent more time in stable housing than participants in treatment as usual (71% versus 29%, adjusted absolute difference [AAD]=42%, p<.01). Compared with treatment-as-usual participants, Housing First participants who entered housing did so more quickly (73 versus 220 days, AAD=146.4, p<.001), had longer housing tenures at the study end-point (281 versus 115 days, AAD=161.8, p<.01), and rated the quality of their housing more positively (adjusted standardized mean difference [ASMD]=.17, p<.01). Housing First participants reported higher quality of life (ASMD=.15, p<.01) and were assessed as having better community functioning (ASMD=.18, p<.01) over the two-year period. Housing First participants showed significantly greater gains in community functioning and quality of life in the first year; however, differences between the two groups were attenuated by the end of the second year. CONCLUSIONS: Housing First with ACT is an effective approach in various contexts for assisting individuals with serious mental illness to rapidly exit homelessness.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".