Housing Histories of Assertive Community Treatment Clients: Program Impacts and Factors Associated with Residential Stability
Bibliographic record
Abstract
OBJECTIVE: Although housing is widely recognized as a crucial issue for people with severe and persistent mental illness, there is much to learn about the ongoing housing experiences of this group of people. Using secondary data, this study examined the housing histories of 65 assertive community treatment (ACT) clients from 2 years prior until up to 7 years after intake, totalling 407 addresses. METHOD: We used statistical process control to assess the significance and longevity of pre- and post-ACT changes in residential tenure and independent living. We used multivariate survival analysis to explore participant and residence characteristics associated with residential stability. RESULTS: After 6 months in ACT, the client population showed a significant, sustained improvement in housing stability. Similarly, shortly after ACT entry, there was a marked increase in the proportion of participants living independently. At the participant level, substance abuse was the strongest predictor of residential instability; other predictors included age (30 years or younger) and sex (female). Residence characteristics also proved important; independent housing, neighbourhood income (a proxy for housing quality), and receipt of a rental subsidy were associated with significantly longer tenure, controlling for client characteristics. CONCLUSIONS: The timing and magnitude of the observed changes imply that ACT was effective in helping clients to achieve stable housing and to live independently. The results also underscore the importance of high-quality housing in promoting residential stability.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".