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      Alcohol Use among Adolescent Youth: The Role of Friendship Networks and Family Factors in Multiple School Studies

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          Abstract

          To explore the co-evolution of friendship tie choice and alcohol use behavior among 1,284 adolescents from 12 small schools and 976 adolescents from one big school sampled in the National Longitudinal Study of Adolescent to Adult Health (AddHealth), we apply a Stochastic Actor-Based (SAB) approach implemented in the R-based Simulation Investigation for Empirical Network Analysis (RSiena) package. Our results indicate the salience of both peer selection and peer influence effects for friendship tie choice and adolescent drinking behavior. Concurrently, the main effect models indicate that parental monitoring and the parental home drinking environment affected adolescent alcohol use in the small school sample, and that parental home drinking environment affected adolescent drinking in the large school sample. In the small school sample, we detect an interaction between the parental home drinking environment and choosing friends that drink as they multiplicatively affect friendship tie choice. Our findings suggest that future research should investigate the synergistic effects of both peer and parental influences for adolescent friendship tie choices and drinking behavior. And given the tendency of adolescents to form ties with their friends' friends, and the evidence of local hierarchy in these networks, popular youth who do not drink may be uniquely positioned and uniquely salient as the highest rank of the hierarchy to cause anti-drinking peer influences to diffuse down the social hierarchy to less popular youth. As such, future interventions should harness prosocial peer influences simultaneously with strategies to increase parental support and monitoring among parents to promote affiliation with prosocial peers.

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          Most cited references37

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          Emergence of scaling in random networks

          Systems as diverse as genetic networks or the world wide web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution. This feature is found to be a consequence of the two generic mechanisms that networks expand continuously by the addition of new vertices, and new vertices attach preferentially to already well connected sites. A model based on these two ingredients reproduces the observed stationary scale-free distributions, indicating that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
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            Emergence of scaling in random networks

            Systems as diverse as genetic networks or the World Wide Web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution. This feature was found to be a consequence of two generic mechanisms: (i) networks expand continuously by the addition of new vertices, and (ii) new vertices attach preferentially to sites that are already well connected. A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
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              Assortative mixing in networks

              M. Newman (2002)
              A network is said to show assortative mixing if the nodes in the network that have many connections tend to be connected to other nodes with many connections. We define a measure of assortative mixing for networks and use it to show that social networks are often assortatively mixed, but that technological and biological networks tend to be disassortative. We propose a model of an assortative network, which we study both analytically and numerically. Within the framework of this model we find that assortative networks tend to percolate more easily than their disassortative counterparts and that they are also more robust to vertex removal.
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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                10 March 2015
                2015
                : 10
                : 3
                : e0119965
                Affiliations
                [1 ]Department of Sociology, Cornell University, Ithaca, New York, United States of America
                [2 ]Departments of Criminology, Law and Society and Sociology, University of California Irvine, Irvine, California, United States of America
                [3 ]Departments of Sociology and Statistics, University of California Irvine, Irvine, California, United States of America
                [4 ]Department of Psychology and Social Behavior, University of California Irvine, Irvine, California, United States of America
                [5 ]Program in Public Health, University of California Irvine, Irvine, California, United States of America
                David Geffen School of Medicine at UCLA, UNITED STATES
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Analyzed the data: CW RJ. Contributed reagents/materials/analysis tools: CW CTB. Wrote the paper: CW JRH RJ CML.

                Article
                PONE-D-14-36142
                10.1371/journal.pone.0119965
                4355410
                25756364
                1aa027a2-4371-4c99-83f4-81a0933008e9
                Copyright @ 2015

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

                History
                : 14 August 2014
                : 18 January 2015
                Page count
                Figures: 1, Tables: 6, Pages: 19
                Funding
                This research is funded by National Institutes of Health Grant (5R21DA031152-02) administered through the Program in Public Health at the University of California Irvine. The funders had no role in study design, data collection and analysis, decision to publish,or preparation of the manuscript.
                Categories
                Research Article
                Custom metadata
                This research uses data from AddHealth, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill. Information on how to obtain the AddHealth data files is available on the AddHealth website ( http://www.cpc.unc.edu/addhealth).

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