Evaluating a transitional housing program for people who use substances (PWUS) who experience homelessness and live with a mental health issue: a mixed-methods study protocol in Sudbury Ontario
Bibliographic record
Abstract
BACKGROUND: A new transitional housing program was established in Sudbury, Ontario, Canada, in response to the escalating global prevalence of substance use and homelessness, and the specific challenges faced in Northern Ontario. This protocol outlines a comprehensive program evaluation to assess its impact on patient outcomes, healthcare utilization, and client perspectives. METHODS: We will conduct a parallel mixed-method study that includes the analysis of single-center-level administrative health data and primary data collection. This includes a longitudinal observational study (target n = 1,200), pre- and post-admission quantitative interviews (target n = 40), and qualitative interviews (target n = 40). We will implement a participatory approach to this evaluation collaborating with people who use substances, frontline staff, and decision-makers. Data analysis methods include a range of statistical techniques, including logistic regression models, Cox proportional hazards models, Kaplan-Meier curves, Generalized Estimating Equations, and thematic qualitative analysis, ensuring a robust evaluation of patient outcomes and healthcare utilization. DISCUSSION: This protocol underpins a comprehensive assessment aimed at providing insights into the program's effectiveness in addressing substance use-related challenges, reducing healthcare disparities, and improving patient outcomes, such as stable housing and increased social capital. All study procedures adhere to the ethical principles outlined in the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans. Findings will be disseminated progressively through established committees and working groups and subsequently published in peer-reviewed journals. Anticipated outcomes include informing evidence-based healthcare decision-making and driving improvements in addiction treatment practices within healthcare settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.033 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".