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Early Adolescent Social Networks and Substance Use

NCJ Number
219600
Journal
Journal of Early Adolescence Volume: 27 Issue: 3 Dated: August 2007 Pages: 346-362
Author(s)
David B. Henry; Kimberly Kobus
Date Published
August 2007
Length
17 pages
Annotation
This study explored the relationships between social network position and the use of tobacco, alcohol, marijuana, and inhalants among a sample of sixth grade youth.
Abstract
Results indicated that youth nominated by follow students as liaisons between social network groups were more likely to use tobacco than social network members or social isolates. Social liaisons were also more likely to use alcohol than were social isolates. Youth in the three social positions did not differ with regards to their use of inhalants or marijuana. Four potential explanations are offered for the higher use of tobacco and alcohol use among social liaisons: (1) greater opportunity for association with substance abusing peers; (2) social liaisons experience increased stress as a result of their boundary spanning and are thus more likely to self-medicate with alcohol and tobacco; (3) social liaisons offer a snapshot of a dynamic process whereby substance use promotes group acceptance or rejection; and (4) liaisons may have been in the process of being marginalized by peer groups, thus becoming more susceptible to peer pressure to use substances. Future research should use longitudinal data to investigate changes in substance use and social network position as youth progress through adolescence. Participants were 1,119 sixth-grade students from 144 classes in 14 public schools who were participating in the Metropolitan Area Child Study in and around Chicago, IL. Social networks were assessed using the peer nomination inventory in which students rate their peers according to a series of questions, such as “Who would you like to be your best friend?” Involvement in substance abuse was measured using an abbreviated version of the Self-Report of Delinquency questionnaire. Data were analyzed using logistic regression models. Tables, references

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