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      Adolescent alcohol use: use of social network analysis and cross-classified multilevel modeling to examine peer group, school, and neighborhood-level influences

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          Abstract

          Background:

          Neighborhood-, school-, and peer-contexts play an important role in adolescent alcohol use behaviors. Methodological advances permit simultaneous modeling of these contexts to understand their relative and joint importance. Few empirical studies include these contexts, and studies that do typically: examine each context separately; include contexts for the sole purpose of accounting for clustering in the data; or do not disaggregate by sex.

          Objectives:

          This study takes an eco-epidemiologic approach to examine the role of socio-contextual contributions to variance in adolescent alcohol use. The primary parameters of interest are therefore variance rather than beta parameters (i.e. random rather than fixed effects). Sex-stratified models are also used to understand how each context may matter differently for male and female adolescents.

          Method:

          Data come from the National Longitudinal Study of Adolescent to Adult Health ( n = 8,534 females, n = 8,102 males). We conduct social network analysis and traditional and cross-classified multilevel models (CCMM) in the full and sex-disaggregated samples.

          Results:

          In final CCMM, peer groups, schools, and neighborhoods contributed 10.5%, 10.8%, and 0.4%, respectively, to total variation in adolescent alcohol use. Results do not differ widely by gender.

          Conclusions:

          Peer groups and schools emerge as more salient contributing contexts relative to neighborhoods in adolescent alcohol use for males and females. These findings have both methodological and practical implications. Multilevel modeling can model contexts simultaneously to prevent the overestimation of variance in youth alcohol use explained by each context. Primary prevention strategies addressing youth alcohol use should focus on schools and peer networks.

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          Most cited references56

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          • Abstract: found
          • Article: not found

          Fast unfolding of communities in large networks

          Journal of Statistical Mechanics: Theory and Experiment, 2008(10), P10008
            • Record: found
            • Abstract: not found
            • Article: not found

            The Strength of Weak Ties

              • Record: found
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              • Article: not found

              Modularity and community structure in networks

              M. Newman (2006)
              Many networks of interest in the sciences, including social networks, computer networks, and metabolic and regulatory networks, are found to divide naturally into communities or modules. The problem of detecting and characterizing this community structure is one of the outstanding issues in the study of networked systems. One highly effective approach is the optimization of the quality function known as "modularity" over the possible divisions of a network. Here I show that the modularity can be expressed in terms of the eigenvectors of a characteristic matrix for the network, which I call the modularity matrix, and that this expression leads to a spectral algorithm for community detection that returns results of demonstrably higher quality than competing methods in shorter running times. I illustrate the method with applications to several published network data sets.

                Author and article information

                Journal
                7502510
                420
                Am J Drug Alcohol Abuse
                Am J Drug Alcohol Abuse
                The American journal of drug and alcohol abuse
                0095-2990
                1097-9891
                25 April 2024
                03 September 2023
                11 July 2023
                04 May 2024
                : 49
                : 5
                : 576-586
                Affiliations
                [a ]Department of Medicine, University of California San Diego, La Jolla, CA, USA
                [b ]Department of Psychology, University of California San Diego, La Jolla, CA, USA
                [c ]School of Social Work, San Diego State University, San Diego, CA, USA
                [d ]Newcomb Institute, Tulane University, New Orleans, LA
                [e ]Tulane School of Public Health and Hygiene, New Orleans, LA
                Author notes
                [] CONTACT Kathryn M. Barker, k1barker@ 123456health.ucsd.edu , Department of Medicine, University of California San Diego, 9500 Gilman Drive, MC 0507, La Jolla, CA 92093-0507
                Author information
                http://orcid.org/0000-0002-6242-0217
                Article
                NIHMS1985640
                10.1080/00952990.2023.2222431
                11069396
                37433106
                b3c7088a-4e9e-4e6b-8ecf-b611bdae0edb

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License ( http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

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                Categories
                Article

                adolescents,alcohol drinking,gender,multilevel analysis,social network analysis

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