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Peer influence in adolescent drinking behavior: A meta-analysis of stochastic actor-based modeling studies
OBJECTIVES: To measure the effects of peer influence and peer selection on drinking behavior in adolescence through a rigorous statistical approach designed to unravel these interrelated processes. METHODS: We conducted systematic searches of electronic databases, thesis collections and conference p...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Public Library of Science
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8051820/ https://www.ncbi.nlm.nih.gov/pubmed/33861781 http://dx.doi.org/10.1371/journal.pone.0250169 |
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author | Ivaniushina, Valeria Titkova, Vera |
author_facet | Ivaniushina, Valeria Titkova, Vera |
author_sort | Ivaniushina, Valeria |
collection | PubMed |
description | OBJECTIVES: To measure the effects of peer influence and peer selection on drinking behavior in adolescence through a rigorous statistical approach designed to unravel these interrelated processes. METHODS: We conducted systematic searches of electronic databases, thesis collections and conference proceedings to identify studies that used longitudinal network design and stochastic actor-oriented modeling to analyze drinking behavior in adolescents. Parameter estimates collected from individual studies were analyzed using multilevel random-effects models. RESULTS: We identified 26 articles eligible for meta-analysis. Meta-analyses for different specifications of the peer influence effect were conducted separately. The peer influence effect was positive for every specification: for average similarity (avSim) mean log odds ratio was 1.27 with 95% confidence interval [0.04; 2.49]; for total similarity (totSim) 0.46 (95% CI = [0.44; 0.48]), and for average alter (avAlt) 0.70 (95% CI = [-0.01; 1.41]). The peer selection effect (simX) was also positive: 0.46 (95% CI = [0.28; 0.63]). Conversion log odds ratio values to Cohen’s d gives estimates from 0.25 to 0.70, which is considered as medium to large effect. CONCLUSIONS: Advances in methodology for social network analysis have made it possible to accurately estimate peer influence effects free from peer selection effects. More research is necessary to clarify the roles of age, gender, and individual susceptibility on the changing behavior of adolescents under the influence of their peers. Understanding the effects of peer influence should inform practitioners and policy makers to design and deliver more effective prevention programs. |
format | Online Article Text |
id | pubmed-8051820 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-80518202021-04-28 Peer influence in adolescent drinking behavior: A meta-analysis of stochastic actor-based modeling studies Ivaniushina, Valeria Titkova, Vera PLoS One Research Article OBJECTIVES: To measure the effects of peer influence and peer selection on drinking behavior in adolescence through a rigorous statistical approach designed to unravel these interrelated processes. METHODS: We conducted systematic searches of electronic databases, thesis collections and conference proceedings to identify studies that used longitudinal network design and stochastic actor-oriented modeling to analyze drinking behavior in adolescents. Parameter estimates collected from individual studies were analyzed using multilevel random-effects models. RESULTS: We identified 26 articles eligible for meta-analysis. Meta-analyses for different specifications of the peer influence effect were conducted separately. The peer influence effect was positive for every specification: for average similarity (avSim) mean log odds ratio was 1.27 with 95% confidence interval [0.04; 2.49]; for total similarity (totSim) 0.46 (95% CI = [0.44; 0.48]), and for average alter (avAlt) 0.70 (95% CI = [-0.01; 1.41]). The peer selection effect (simX) was also positive: 0.46 (95% CI = [0.28; 0.63]). Conversion log odds ratio values to Cohen’s d gives estimates from 0.25 to 0.70, which is considered as medium to large effect. CONCLUSIONS: Advances in methodology for social network analysis have made it possible to accurately estimate peer influence effects free from peer selection effects. More research is necessary to clarify the roles of age, gender, and individual susceptibility on the changing behavior of adolescents under the influence of their peers. Understanding the effects of peer influence should inform practitioners and policy makers to design and deliver more effective prevention programs. Public Library of Science 2021-04-16 /pmc/articles/PMC8051820/ /pubmed/33861781 http://dx.doi.org/10.1371/journal.pone.0250169 Text en © 2021 Ivaniushina, Titkova https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Ivaniushina, Valeria Titkova, Vera Peer influence in adolescent drinking behavior: A meta-analysis of stochastic actor-based modeling studies |
title | Peer influence in adolescent drinking behavior: A meta-analysis of stochastic actor-based modeling studies |
title_full | Peer influence in adolescent drinking behavior: A meta-analysis of stochastic actor-based modeling studies |
title_fullStr | Peer influence in adolescent drinking behavior: A meta-analysis of stochastic actor-based modeling studies |
title_full_unstemmed | Peer influence in adolescent drinking behavior: A meta-analysis of stochastic actor-based modeling studies |
title_short | Peer influence in adolescent drinking behavior: A meta-analysis of stochastic actor-based modeling studies |
title_sort | peer influence in adolescent drinking behavior: a meta-analysis of stochastic actor-based modeling studies |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8051820/ https://www.ncbi.nlm.nih.gov/pubmed/33861781 http://dx.doi.org/10.1371/journal.pone.0250169 |
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