Risk environments facing potential users of a supervised injection site in Ottawa, Canada
Notice bibliographique
Résumé
BACKGROUND: Supervised injection sites (SISs) have been effective in reducing health risks among people who inject drugs (PWID), including those who face issues of homelessness, mental health illness, interactions with local policing practices, and HIV infection. We investigate the risk behaviours and risk environments currently faced by potential users of an SIS in Ottawa to establish the need for such a service and to contribute to the design of an SIS that can address current health risks and reduce harm. METHODS: The PROUD cohort is a community-based participatory research (CBPR) project that examines the HIV risk environment among people who use drugs in Ottawa. From March to October 2013, 593 people who reported using injection drugs or smoking crack cocaine were enrolled through street-based recruitment in the ByWard Market neighbourhood, an area of the city with a high concentration of public drug use and homelessness. Participants completed a demographic, behavioural, and risk environment questionnaire and were offered HIV point-of-care testing. We undertook descriptive and univariate analyses to estimate potential use of an SIS by PWID in Ottawa and to explore risk behaviours and features of the risk environment faced by potential users of the service. RESULTS: Of those participants who reported injecting drugs in the previous 12 months (n = 270), 75.2 % (203) reported a willingness to use an SIS in Ottawa. Among potential SIS users, 24.6 % had recently injected with a used needle, 19.0 % had trouble accessing new needles, 60.6 % were unstably housed, 49.8 % had been redzoned by the police, and 12.8 % were HIV positive. Participants willing to use an SIS more frequently injected in public (OR = 1.98, 95 % CI = 1.06-3.70), required assistance to inject (OR = 1.84, 95 % CI = 1.00-3.38), were hepatitis C positive (OR = 2.13, 95 % CI = 1.16-3.91), had overdosed in the previous year (OR = 2.00, 95 % CI = 1.02-3.92), and identified as LGBTQ (OR = 5.61, 95 % CI = 1.30-24.19). CONCLUSION: An SIS in Ottawa would be well-positioned to reach its target group of highly marginalized PWID and reduce drug-related harms. The application of CBPR methods to a large-scale quantitative survey supported the mobilization of communities of PWID to identify and advocate for their own service needs, creating an enabling environment for harm reduction action.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».