A cross-sectional study of factors associated with unstable housing among marginalized people who use drugs in Ottawa, Canada
Bibliographic record
Abstract
INTRODUCTION: Housing affects an individual's physical and mental health, particularly among people who use substances. Understanding the association between individual characteristics and housing status can inform housing policy and help optimize the care of people who use drugs. The objective of this study was to explore the factors associated with unstable housing among people who use drugs in Ottawa. METHODS: This is a cross-sectional analysis of data from 782 participants in the Participatory Research in Ottawa: Understanding Drugs (PROUD) Study. PROUD is a prospective cohort study of people who use drugs in Ottawa. Between March and December 2013, participants were recruited through peer-based recruitment on the streets and in social services settings and completed a peer-administered questionnaire that explored socio-demographic information, drug use patterns, community integration, experiences with police and incarceration, and access to health care and harm reduction services. Eligibility criteria included age of 16 years or older, self-reported illicit drug use within the past 12 months and having lived in Ottawa for at least 3 months. Housing status was determined by self-report. "Stable housing" was defined as residence in a house or apartment and "unstable housing" was defined as all other residence types. Exploratory multivariable logistic regression analyses of the association between characteristics of people who use drugs and their housing status were conducted. RESULTS: Factors that were associated with unstable housing included: recent incarceration; not having a regular doctor; not having received support from a peer worker; low monthly income; income source other than public disability support payments; and younger age. Gender, language, ethnicity, education level, opioid use and injection drug use were not independently associated with housing status. CONCLUSIONS: People who use drugs face significant barriers to stable housing. These results highlight key areas to address in order to improve housing stability among this community.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 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".