The At Home/Chez Soi trial protocol: a pragmatic, multi-site, randomised controlled trial of a Housing First intervention for homeless individuals with mental illness in five Canadian cities
Bibliographic record
Abstract
Introduction Housing First is a complex housing and support intervention for homeless individuals with mental health problems. It has a sufficient knowledge base and interest to warrant a test of wide-scale implementation in various settings. This protocol describes the quantitative design of a Canadian five city, $110 million demonstration project and provides the rationale for key scientific decisions. Methods A pragmatic, mixed methods, multi-site field trial of the effectiveness of Housing First in Vancouver, Winnipeg, Toronto, Montreal and Moncton, is randomising approximately 2500 participants, stratified by high and moderate need levels, into intervention and treatment as usual groups. Quantitative outcome measures are being collected over a 2-year period and a qualitative process evaluation is being completed. Primary outcomes are housing stability, social functioning and, for the economic analyses, quality of life. Hierarchical linear modelling is the primary data analytic strategy. Ethics and dissemination Research ethics board approval has been obtained from 11 institutions and a safety and adverse events committee is in place. The results of the multi-site analyses of outcomes at 12 months and 2 years will be reported in a series of core scientific journal papers. Extensive knowledge exchange activities with non-academic audiences will occur throughout the duration of the project. Trial registration number This study has been registered with the International Standard Randomised Control Trial Number Register and assigned ISRCTN42520374.
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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 | 0.016 | 0.013 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.029 | 0.002 |
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".