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• W2790201757 abstract "We aimed to identify phenotypes of DSM–ICD nicotine dependence among a representative sample of lifetime weekly smokers in the largest metropolitan area in South America. Data came from 1,387 lifetime weekly smokers in the São Paulo Megacity Mental Health Survey. We used exploratory factor analysis (EFA) and latent class analysis (LCA) on ICD-11 nicotine dependence proposed criteria to explore dimensionality and phenotypes profiles, followed by logistic regression models to examine the association between latent classes and socio-demographic, psychiatric and chronic medical conditions. Analyses were performed using Mplus taking into account the complex survey design features. An unidimensional model had the best EFA fit with high loadings on all criteria. Response patterns detected by LCA indicated class differences based on severity continuum: a “non-symptomatic class” (32.0%), a “low-moderate symptomatic class” (34.9%)—with high probability of the criterion “use in larger amounts”, and a “high-moderate symptomatic class” (33.1%). We found an association between high-income and the intermediate class that differs from findings in high-income countries, and high likelihood of psychiatric comorbidity among the most symptomatic smokers. The best dimensional model that pulled together nicotine dependence criteria supported a single factor, in concordance with the changes proposed for ICD-11." @default.
• W2790201757 created "2018-03-29" @default.
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• W2790201757 date "2018-08-01" @default.
• W2790201757 modified "2023-09-30" @default.
• W2790201757 title "The latent trait of ICD-11 nicotine dependence criteria: Dimensional and categorical phenotypes" @default.
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• W2790201757 doi "https://doi.org/10.1016/j.psychres.2018.03.018" @default.
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