“The system always undermined what I was trying to do as an individual”: identifying opportunities to improve the delivery of opioid use services for youth from the perspective of service providers in four communities across British Columbia, Canada
Notice bibliographique
Résumé
BACKGROUND: Substance use among youth is a longstanding global health concern that has dramatically risen in the era of highly toxic and unregulated drugs, including opioids. It is crucial to ensure that youth using unregulated opioids have access to evidence-based interventions, and yet, youth encounter critical gaps in the quality of such interventions. This study aims to address these gaps by identifying opportunities to improve the quality of opioid use services from the perspective of service providers, a perspective that has received scant attention. METHODS: This community-based participatory study was conducted in four communities in British Columbia (Canada), a province that declared a public health overdose emergency in 2016. Human-centered co-design workshops were held to understand service providers' (n = 41) experiences, needs, and ideas for improving the quality of youth opioid use services/treatments in their community. Multi-site qualitative analysis was used to develop overarching experiences and needs themes that were further contextualized in each local community. A blended deductive and inductive thematic analysis was used to analyze the ideas data. RESULTS: Three overarching themes were identified, reflecting service providers' goals to respond to youth in a timely and developmentally appropriate manner. However, this was significantly limited by organizational and systems-level barriers, revealing service providers' priorities for intra- and inter-organizational support and collaboration and systems-level innovation. Across communities, service providers identified 209 individual ideas to address these prioritized needs and improve the quality of youth opioid use services/treatments. CONCLUSION: These themes demonstrate a multi-level tension between macro-level systems and the meso-level organization of youth opioid use services, which undermine the quality of individual-level care service providers can deliver. These findings underscore the need for a coordinated multi-level response, such as developing youth-specific standards (macro-level), increasing inter-organizational activities and collaboration (meso-level), and creating programs that are specific to youths' needs (micro-level).
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,005 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,002 | 0,003 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».