Scoping review of managed alcohol programs
Notice bibliographique
Résumé
BACKGROUND: Internationally, strategies focusing on reducing alcohol-related harms in homeless populations with severe alcohol use disorder (AUD) continue to gain acceptance, especially when conventional modalities focused on alcohol abstinence have been unsuccessful. One such strategy is the managed alcohol program (MAP), an alcohol harm reduction program managing consumption by providing eligible individuals with regular doses of alcohol as a part of a structured program, and often providing resources such as housing and other social services. Evidence to the role of MAPs for individuals with AUD, including how MAPs are developed and implemented, is growing. Yet there has been limited collective review of literature findings. METHODS: We conducted a scoping review to answer, "What is being evaluated in studies of MAPs? What factors are associated with a successful MAP, from the perspective of client outcomes? What are the factors perceived as making them a good fit for clients and for communities?" We first conducted a systematic search in PubMed, Embase, PsycINFO, CINAHL, Sociological Abstracts, Social Services Abstracts, and Google Scholar. Next, we searched the gray literature (through focused Google and Ecosia searches) and references of included articles to identify additional studies. We also contacted experts to ensure relevant studies were not missed. All articles were independently screened and extracted. RESULTS: We included 32 studies with four categories of findings related to: (1) client outcomes resulting from MAP participation, (2) client experience within a MAP; (3) feasibility and fit considerations in MAP development within a community; and (4) recommendations for implementation and evaluation. There were 38 established MAPs found, of which 9 were featured in the literature. The majority were located in Canada; additional research works out of Australia, Poland, the USA, and the UK evaluate potential feasibility and fit of a MAP. CONCLUSIONS: The growing literature showcases several outcomes of interest, with increasing efforts aimed at systematic measures by which to determine the effectiveness and potential risks of MAP. Based on a harm reduction approach, MAPs offer a promising, targeted intervention for individuals with severe AUD and experiencing homelessness. Research designs that allow for longitudinal follow-up and evaluation of health- and housing-sensitive outcomes are recommended.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
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 | 0,002 | 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 | 0,002 | 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) | 0,005 | 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 ».