Examining harm reduction in Housing First for youth experiencing homelessness and concurrent mental health and substance use issues
Bibliographic record
Abstract
Purpose: Housing First for Youth (HF4Y) is a youth-focused adaptation of the well-established Housing First (HF) program model to housing and service provision for individuals experiencing homelessness. Given that the experience of youth homelessness is associated with an increased likelihood of substance use issues, a central tenet of the HF4Y framework is the use of a harm reduction approach to substance use and addictions. However, research on HF4Y programming has yet to examine how harm reduction is specifically being implemented in these settings. The purpose of this thesis was to examine how the principles and philosophies of harm reduction are operationalized and implemented in an HF4Y program for youth experiencing homelessness and concurrent mental health and substance use issues.\nMethods: This thesis was part of a larger process and outcome evaluation of a 2-year HF4Y research demonstration project for youth experiencing homelessness and concurrent disorders – the Restart Project in Kelowna, British Columbia, and Toronto, Ontario, Canada. Data were collected from the Kelowna site using qualitative semi-structured interviews with 2 program leaders and 6 service providers working in the HF4Y program, and analyzed using thematic analysis. Program documents and case management materials were also reviewed and analyzed using content analysis. Findings were then triangulated to determine how harm reduction was operationalized and delivered in the Restart HF4Y Program.\nFindings: In total, twelve themes emerged from the analysis of interview data and program documents. Thematic analysis of interview data resulted in seven main themes illustrating program leaders’ and service providers’ perspectives on harm reduction in the Restart HF4Y Program: (1) working with youth to ensure they are using substances as safely as possible; (2) connecting youth to services in the community; (3) providing youth with individualized support; (4) reducing stigma around substance use; (5) empowering youth who use substances; (6) creating environments where the risk of harm is reduced; and (7) building strong relationships with youth. Themes demonstrating factors that impeded the delivery of harm reduction in the Restart Program also emerged from the interview data, including the lack of low barrier housing for youth who use substances and the expectations of landlords. Lastly, three themes emerged from the document review demonstrating how harm reduction was enacted in the Restart Program documents: (1) by connecting youth to supports and services in the community, (2) by reducing the risks and harms of substance use, and (3) by providing guidance to program staff.\nConclusion: This thesis addresses a knowledge gap on the implementation of harm reduction in HF4Y programming, including systems-level barriers to harm reduction delivery, such as the lack of housing availability for youth experiencing homelessness and substance use issues. These findings emphasize the need for greater advocacy for low-barrier housing options for youth who actively use substances. Similarly, to effectively practice harm reduction, further research is needed to identify and address other contextual factors promoting and limiting harm reduction delivery in HF programming.
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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".