Effect of Housing First on Suicidal Behaviour
Bibliographic record
Abstract
OBJECTIVE: This study attempted to determine if Housing First (HF) decreased suicidal ideation and attempts compared to treatment as usual (TAU) amongst homeless persons with mental disorders, a population with a demonstrably high risk of suicidal behaviour. METHOD: The At Home/Chez Soi project is an unblinded, randomised control trial conducted across 5 Canadian cities (Vancouver, Winnipeg, Toronto, Montreal, Moncton) from 2009 to 2013. Homeless adults with a diagnosed major mental health disorder were recruited through community agencies and randomised to HF ( n = 1265) and TAU ( n = 990). HF participants were provided with private housing units and received case management support services. TAU participants retained access to existing community supports. Past-month suicidal ideation was measured at baseline and 6, 12, 18, and 21/24 months. A history of suicide attempts was measured at baseline and the 21/24-month follow-up. RESULTS: Compared to baseline, there was an overall trend of decreased past-month suicidal ideation (estimate = -.57, SE = .05, P < 0.001), with no effect of treatment group (i.e., HF vs. TAU; estimate = -.04, SE = .06, P = 0.51). Furthermore, there was no effect of treatment status (estimate = -.10, SE = .16, P = 0.52) on prevalence of suicide attempts (HF = 11.9%, TAU = 10.5%) during the 2-year follow-up period. CONCLUSION: This study failed to find evidence that HF is superior to TAU in reducing suicidal ideation and attempts. We suggest that HF interventions consider supplemental psychological treatments that have proven efficacy in reducing suicidal behaviour. It remains to be determined what kind of suicide prevention interventions (if any) are specifically effective in further reducing suicidal risk in a housing-first intervention.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".