A Network Method of Measuring Affiliation-Based Peer Influence: Assessing the Influences of Teammates’ Smoking on Adolescent Smoking

Authors


  • This study was supported by grants to the first author (Kayo Fujimoto) from the National Institute on Alcohol Abuse and Alcoholism (K99AA019699), to the second author (Jennifer Unger) from the National Cancer Institute (5P50CA084735), and to the last author (Thomas Valente) from the National Institute on Alcohol Abuse and Alcoholism (RC1AA019239-01). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. We gratefully acknowledge Erik Lindsley for valuable discussions, and Steven Cen for consulting on the data set itself.

concerning this article should be addressed to Kayo Fujimoto, Division of Health Promotion and Behavioral Sciences, School of Public Health, University of Texas at Houston, Houston, TX 77030. Electronic mail may be sent to kayo.fujimoto@uth.tmc.edu.

Abstract

Using a network analytic framework, this study introduces a new method to measure peer influence based on adolescents’ affiliations or 2-mode social network data. Exposure based on affiliations is referred to as the “affiliation exposure model.” This study demonstrates the methodology using data on young adolescent smoking being influenced by joint participation in school-based organized sports activities with smokers. The analytic sample consisted of 1,260 American adolescents from ages 10 to 13 in middle schools, and the results of the longitudinal regression analyses showed that adolescents were more likely to smoke as they were increasingly exposed to teammates who smoke. This study illustrates the importance of peer influence via affiliation through team sports.

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