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Title: Development and evaluation of a risk algorithm predicting alcohol dependence after early onset of regular alcohol use
Authors: Bharat, Chrianna
Glantz, Meyer D
Aguilar-Gaxiola, Sergio
Alonso, Jordi
Bruffaerts, Ronny
Bunting, Brendan
Caldas-de-Almeida, José Miguel
Cardoso, Graça
Chardoul, Stephanie
de Jonge, Peter
Gureje, Oye
Haro, Josep Maria
Harris, Meredith G
Karam, Elie G.
Kawakami, Norito
Kiejna, Andrzej
Kovess-Masfety, Viviane
Lee, Sing
McGrath, John J
Moskalewicz, Jacek
Navarro-Mateu, Fernando
Rapsey, Charlene
Sampson, Nancy A
Scott, Kate M
Tachimori, Hisateru
Ten Have, Margreet
Vilagut, Gemma
Wojtyniak, Bogdan
Xavier, Miguel
Kessler, Ronald C
Degenhardt, Louisa
Affiliations: Faculty of Medicine 
Keywords: Adolescence
Alcohol use
Machine learning
Issue Date: 2023-05
Publisher: Wiley Online Library
Part of: Addiction
Likelihood of alcohol dependence (AD) is increased among people who transition to greater levels of alcohol involvement at a younger age. Indicated interventions delivered early may be effective in reducing risk, but could be costly. One way to increase cost-effectiveness would be to develop a prediction model that targeted interventions to the subset of youth with early alcohol use who are at highest risk of subsequent AD.
ISSN: 09652140
DOI: 10.1111/add.16122
Ezproxy URL: Link to full text
Type: Journal Article
Appears in Collections:Faculty of Medicine

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