A Randomized Trial Examining Housing First in Congregate and Scattered Site Formats
Bibliographic record
Abstract
OBJECTIVE: No previous experimental trials have investigated Housing First (HF) in both scattered site (SHF) and congregate (CHF) formats. We hypothesized that CHF and SHF would be associated with a greater percentage of time stably housed as well as superior health and psychosocial outcomes over 24 months compared to treatment as usual (TAU). METHODS: Inclusion criteria were homelessness, mental illness, and high need for support. Participants were randomised to SHF, CHF, or TAU. SHF consisted of market rental apartments with support provided by Assertive Community Treatment (ACT). CHF consisted of a single building with supports equivalent to ACT. TAU included existing services and supports. RESULTS: Of 800 people screened, 297 were randomly assigned to CHF (107), SHF (90), or TAU (100). The percentage of time in stable housing over 24 months was 26.3% in TAU (reference; 95% confidence interval (CI) = 20.5, 32.0), compared to 74.3% in CHF (95% CI = 69.3, 79.3, p<0.001) and 74.5% in SHF (95% CI = 69.2, 79.7, p<0.001). Secondary outcomes favoured CHF but not SHF compared to TAU. CONCLUSION: HF in scattered and congregate formats is capable of achieving housing stability among people experiencing major mental illness and chronic homelessness. Only CHF was associated with improvement on select secondary outcomes. REGISTRATION: Current Controlled Trials: ISRCTN57595077.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.019 | 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".