Evaluating the Effectiveness of the Housing First for Youth Intervention for Youth Experiencing Homelessness in Canada: Protocol for a Multisite, Mixed Methods Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Emerging evidence at the international level suggests that the Housing First approach could improve the housing stability of young people experiencing homelessness. However, there is a dearth of literature in Canada on whether the Housing First intervention for young people experiencing homelessness can improve outcomes including housing stability, health and well-being, and access to complementary supports. Adapted from the original Housing First model, Housing First for Youth (HF4Y) was developed in Canada as a rights-based approach tailored specifically for young people aged 16 to 24 years who are experiencing or are at risk of homelessness. OBJECTIVE: The Making the Shift Youth Homelessness Social Innovation Lab is testing the effectiveness of the HF4Y intervention in Canada. The objective of this study is to determine whether the HF4Y model results in better participant-level outcomes than treatment-as-usual services for young people experiencing homelessness in 2 urban settings: Ottawa and Toronto, Ontario. Primary outcomes include housing stability, health and well-being, and complementary supports, and secondary outcomes include employment and educational attainment and social inclusion. METHODS: The HF4Y study used a multisite, mixed methods, randomized controlled trial research approach for data collection and analysis. Eligible participants included young people aged 16 to 24 years who were experiencing homelessness or housing precarity. The participants were randomly assigned to either the treatment-as-usual group or the housing first intervention group. Survey and interview data in Ottawa and Toronto, Ontario are being collected at multiple time points (3-6 months) over 4 years to capture a range of outcomes. Analytic strategies for quantitative data will include mixed-effects modeling for repeated measures and logistic models. A thematic analysis will be used to analyze qualitative data based on participants' narratives and life journeys through homelessness. Furthermore, program fidelity evaluations are conducted within each HF4Y program. These evaluations assess how well the intervention aligns with the HF4Y model and identify any areas that may require adjustments or additional support. RESULTS: The HF4Y study has received human participant research ethics approval from the Office of Research Ethics at York University. Recruitment was conducted between February 2018 and March 2020. Data collection is expected to be completed at both sites by March 2024. A preliminary analysis of the quantitative and qualitative data collected between baseline and 24 months is underway. CONCLUSIONS: This pilot randomized controlled trial is the first to test the effectiveness of the HF4Y intervention in Canada. The findings of this study will enhance our understanding of how to effectively deliver and scale up the HF4Y intervention, with the aim of continually improving the HF4Y model to promote better outcomes for youth. TRIAL REGISTRATION: International Standard Randomized Controlled Trial Number (ISRCTN) ISRCTN10505930; https://www.isrctn.com/ISRCTN10505930. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/46690.
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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 | 0.048 | 0.039 |
| Meta-epidemiology (narrow) | 0.006 | 0.004 |
| Meta-epidemiology (broad) | 0.011 | 0.008 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.008 | 0.010 |
| Insufficient payload (model declined to judge) | 0.059 | 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".