Housing trajectories and the risk of homelessness among new mental health service users: Protocol for the <scp>AMONT</scp> study
Bibliographic record
Abstract
AIMS: High rates of mental illness among individuals experiencing homelessness, as well as documented contacts with psychiatric services prior to episodes of homelessness, indicate that early intervention could play a key role in homelessness prevention. Decision-makers and clinical teams need longitudinal data on housing trajectories following initial contact with psychiatric services, as well as on predictors of risk of housing instability and homelessness. This paper describes the AMONT study, a mixed-methods naturalistic longitudinal cohort study of individuals identified as new psychiatric service users in seven clinical sites across the province of Québec (Canada). METHODS: The goal of AMONT is to examine the housing situations of individuals over 36 months after their initial contact with psychiatric services, and to identify environmental and individual correlates and predictors of housing outcomes. Participants complete a broad battery of instruments at baseline and follow-up assessments after 24 and 36 months. We explore housing stability following an initial episode of psychiatric service use from the perspective of service users, family members, and service providers, through qualitative interviews. RESULTS AND CONCLUSIONS: The findings from the AMONT study will yield a better understanding of the residential pathways of individuals with mental illness, from their first contact with psychiatric services and for 3 years subsequently. This will inform service providers, decision-makers and managers on the specific housing concerns and issues that affect first-time mental health service users. This in turn can lead to the development and implementation of evidence-informed practices and policies that aim to prevent instability and 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 | 0.016 | 0.017 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.051 | 0.008 |
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".