Examining harm reduction in Housing First for youth experiencing homelessness and concurrent mental health and substance use issues
Notice bibliographique
Résumé
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.
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Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».