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Dynamic associations of network isolation and smoking behavior


Prevailing social network frameworks examine the association between peer ties and behaviors, such as smoking, but the role of social isolates is poorly understood. Some theories predict isolated adolescents are protected from peer influence that increases smoking, while others suggest isolates are more likely to initiate smoking because they lack the social control provided by peer friendships. Building on a growing literature that seeks to explain these contradictions by moving beyond a homogeneous understanding of isolation, we identify the relationship between smoking and three distinct dimensions of isolation: avoided (adolescents who do not receive ties), withdrawn (adolescents who do not send ties), and externally oriented (adolescents who claim close out-of-grade friends). We examine the co-evolutionary effects of these dimensions and cigarette smoking using an autoregressive latent trajectory model with PROSPER Peers, a unique, longitudinal network dataset. These data include students (47% male and 86% white) from rural Iowa and Pennsylvania, ranging successively from grades 6–12 in eight waves of data. We find avoided isolation is associated with decreased subsequent smoking in high school. Smoking increases subsequent avoided and withdrawn isolation, but decreases external orientation.

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Alexander C., Piazza M., Mekos D., & Valente T. (2001). Peers, schools, and adolescent cigarette smoking. Journal of Adolescent Health, 29 (1), 2230.
Allison P. D. (2009). Fixed effects regression models. Los Angeles: Sage Publications.
Arnett J. J. (2000). Emerging adulthood: A theory of development from the late teens through the twenties. American Psychologist, 55 (5), 469480.
Arnett J. J. (2004). Emerging adulthood: The winding road from the late teens through the twenties. New York: Oxford University Press.
Ball B., & Newman M. E. J. (2013). Friendship networks and social status. Network Science, 1 (1), 1630.
Bearman P. S., & Moody J. (2004). Suicide and friendships among American adolescents. American Journal of Public Health, 94 (1), 8995.
Bollen K. A., & Curran P. J. (2004). Autoregressive latent trajectory (ALT) models a synthesis of two traditions. Sociological Methods & Research, 32 (3), 336383.
Bollen K. A., & Curran P. J. (2006). Latent curve models: A structural equation perspective. Hoboken, NJ: Wiley-Interscience.
Cairns R. B., & Cairns B. D. (1994). Lifelines and risks: Pathways of youth in our time. New York, NY: Cambridge University Press.
Choi H. J., & Smith R. A. (2013). Members, isolates, and liaisons: Meta-analysis of adolescents' network positions and their smoking behavior. Substance Use & Misuse, 48 (8), 612622. Retrieved from
Copeland M., Fisher J. C., Moody J., & Feinberg M. E. (2015). The dimensions of social isolation in adolescence: Implications for substance use. Paper presented at the meeting of the American Sociological Association, Chicago, IL.
Cotterell J. (2007). Social networks in youth & adolescence. New York, NY: Routledge.
Curran P. J. (2000). A latent curve framework for the study of development trajectories in substance use. In Rose J. S., Chassin L., Presson C. C., & Sherman S. J. (Eds.), Multivariate applications in substance use research: New methods for new questions (pp. 142). New York: Psychology Press.
Curran P. J., & Hussong A. M. (2003). The use of latent trajectory models in psychopathology research. Journal of Abnormal Psychology, 112 (4), 526544. Retrieved from
DeLay D., Laursen B., Kiuru N., Salmela-Aro K., & Nurmi J. E. (2013). Selecting and retaining friends on the basis of cigarette smoking similarity. Journal of Research on Adolescence, 23 (3), 464473. Retrieved from
Dishion T. J., Capaldi D. M., Spracklen K. M., & Li F. (1995). Peer ecology of male adolescent drug use. Development and Psychopathology, 7 (4), 803824.
Dishion T. J., & Owen L. D. (2002). A longitudinal analysis of friendships and substance use: Bidirectional influence from adolescence to adulthood. Developmental Psychology, 38 (4), 480491. Retrieved from
Ennett S. T., & Bauman K. E. (1993). Peer group structure and adolescent cigarette smoking: A social network analysis. Journal of Health and Social Behavior, 34 (3), 226236.
Ennett S. T., & Bauman K. E. (1994). The contribution of influence and selection to adolescent peer group homogeneity: The case of adolescent cigarette smoking. Journal of Personality and Social Psychology, 67 (4), 653663. Retrieved from
Ennett S. T., Bauman K. E., Hussong A., Faris R., Foshee V. A., Cai L., & DuRant R. (2006). The peer context of adolescent substance use: Findings from social network analysis. Journal of Research on Adolescence, 16 (2), 159186.
Ennett S. T., Faris R., Hipp J., Foshee, V. a, Bauman, K. E., Hussong, A., & Cai L. (2008). Peer smoking, other peer attributes, and adolescent cigarette smoking: A social network analysis. Prevention Science: The Official Journal of the Society for Prevention Research, 9 (2), 8898. Retrieved from
Fujimoto K., & Valente T. W. (2012). Social network influences on adolescent substance use: Disentangling structural equivalence from cohesion. Social Science and Medicine, 74 (12), 19521960. Retrieved from
Gelman A., & Hill J. (2006). Data analysis using regression and multilevel/hierarchichal models. New York: Cambridge University Press.
Goodreau S. M., Kitts J. A., & Morris M. (2009). Birds of a feather, or friend of a friend? Using exponential random graph models to investigate adolescent social networks. Demography, 46 (1), 103125. Retrieved from
Gould R. V. (2002). The origins of status hierarchies: A formal theory and empirical test. American Journal of Sociology, 107 (5), 11431178. Retrieved from
Haas S. A., & Schaefer D. R. (2014). With a little help from my friends? Asymmetrical social influence on adolescent smoking initiation and cessation. Journal of Health and Social Behaviorocial Behavior, 55 (2), 126143. Retrieved from
Hall-Lande J., Eisenberg M., Christenson S. L., & Neumark-Sztainer D. (2007). Social isolation, psychological health, and protective factors in adolescence. Adolescence, 42 (166), 265286.
Hamilton J. L., Hamlat E. J., Stange J. P., Abramson L. Y., & Alloy L. B. (2014). Pubertal timing and vulnerabilities to depression in early adolescence: Differential pathways to depressive symptoms by sex. Journal of Adolescence, 37 (2), 165174. Retrieved from
Haynie D. L., & Osgood D. W. (2005). Reconsidering peers and delinquency: How do peers matter? Social Forces, 84 (2), 11091130.
Henry D. B., & Kobus K. (2007). Early adolescent social networks and substance use. The Journal of Early Adolescence, 27 (3), 346362. Retrieved from
Hirschi T. (1969). Causes of delinquency. Berkeley, CA: University of California Press.
Hoffman B. R., Sussman S., Unger J. B., & Valente T. W. (2006). Peer influences on adolescent cigarette smoking: A theoretical review of the literature. Substance Use & Misuse, 41 (1), 103–55. Retrieved from
Kirke D. M. (2004). Chain reactions in adolescents' cigarette, alcohol and drug use: Similarity through peer influence or the patterning of ties in peer networks? Social Networks, 26 (1), 328. Retrieved from
Kobus K. (2003). Peers and adolescent smoking. Addiction, 98 (Suppl 1), 3755.
Kobus K., & Henry D. B. (2010). Interplay of network position and peer substance use in early adolescent cigarette, alcohol, and marijuana use. The Journal of Early Adolescence, 30 (2), 225245. Retrieved from
Kreager D. A. (2004). Strangers in the halls: Isolation and delinquency in school networks. Social Forces, 83 (1), 351390.
Mahoney J. L., & Stattin H. (2000). Leisure activities and adolescent antisocial behavior: The role of structure and social context. Journal of Adolescence, 23 (2), 113–27. Retrieved from
Maxwell K. A. (2002). Friends: The role of peer influence across adolescent risk behaviors. Journal of Youth and Adolescence, 31 (4), 267277.
McFarland D. A., Moody J., Diehl D., Smith J. A., & Thomas R. J. (2014). Network ecology and adolescent social structure. American Sociological Review, 79 (6), 10881121. Retrieved from
Mercken L., Snijders T. A. B., Steglich C., Vartiainen E. & de Vries H. (2010). Dynamics of adolescent friendship networks and smoking behavior. Social Networks, 32 (1), 7281. Retrieved from
Molloy L. E., Gest S. D., Feinberg M. E., & Osgood D. W. (2014). Emergence of mixed-sex friendship groups during adolescence: Developmental associations with substance use and delinquency. Developmental Psychology, 50 (11), 24492461. Retrieved from
Niño M. D., Cai T., & Ignatow G. (2016). Social isolation, drunkenness, and cigarette use among adolescents. Addictive Behaviors, 53, 94100. Retrieved from
Osgood D. W., Feinberg M. E., Wallace L. N., & Moody J. (2014). Friendship group position and substance use. Addictive Behaviors, 39 (5), 923933.
Poulin F., & Pedersen S. (2007). Developmental changes in gender composition of friendship networks in adolescent girls and boys. Developmental Psychology, 43 (6), 14841496. Retrieved from
Raudenbush S. W. (2002). Hierarchichal linear models: Applications and data analysis methods (2nd ed.). Thousand Oaks: Sage Publications.
Ripley R. M., Snijders T. A. B., Boda Z., Vörös A., & Preciado P. (2016). Manual for SIENA version 4.0. Oxford: University of Oxford, Department of Statistics; Nuffield College.
Rubin K. H., & Mills R. S. (1988). The many faces of social isolation in childhood. Journal of Consulting and Clinical Psychology, 56 (6), 916924. Retrieved from
Schaefer D. R., Haas S. A., & Bishop N. J. (2012). A dynamic model of us adolescents' smoking and friendship networks. American Journal of Public Health, 102 (6), 1218. Retrieved from
Schaefer D. R., Kornienko O., & Fox A. M. (2011). Misery does not love company: Network selection mechanisms and depression homophily. American Sociological Review, 76 (5), 764785. Retrieved from
Skrondal A. & Rabe-Hesketh S. (2014). Handling initial conditions and endogenous covariates in dynamic/transition models for binary data with unobserved heterogeneity. Journal of the Royal Statistical Society: Series C (Applied Statistics), 63 (2), 211237.
Snijders T. A. B., van de Bunt G. G., & Steglich C. E. G. (2010). Introduction to stochastic actor-based models for network dynamics. Social Networks, 32 (1), 4460. Retrieved from
Spoth R., Greenberg M., Bierman K., & Redmond C. (2004). PROSPER community-university partnership model for public education systems: Capacity-building for evidence-based, competence-building prevention. Prevention Science, 5 (1), 3139. Retrieved from
Spoth R., Redmond C., Clair S., Shin C., Greenberg M., & Feinberg M. (2011). Preventing substance misuse through community-university partnerships: Randomized controlled trial outcomes 4 1/2 years past caseline. American Journal of Preventive Medicine, 40 (4), 440447. Retrieved from
Steglich C., Snijders T. A. B., & Pearson M. (2010). Dynamic networks and behavior: Separating selection from influence. Sociological Methodology, 40 (1), 329393.
Tani C. R., Chavez E. L., & Deffenbacher J. L. (2001). Peer isolation and drug use among white non-hispanic and Mexican American adolescents. Adolescence, 36 (141), 127139.
Urberg K. A., Luo Q., Pilgrim C., & Degirmencioglu S. M. (2003). A two-stage model of peer influence in adolescent substance use: Individual and relationship-specific differences in susceptibility to influence. Addictive Behaviors, 28 (7), 12431256. Retrieved from
Valente T. W., Unger J. B., & Johnson C. A. (2005). Do popular students smoke? The association between popularity and smoking among middle school students. The Journal of Adolescent Health, 37 (4), 323329. Retrieved from
Van Zalk M. H. W., Kerr M., Branje S. J. T., Stattin H., & Meeus W. H. J. (2010). It takes three: selection, influence, and de-selection processes of depression in adolescent friendship networks. Developmental Psychology, 46 (4), 927938.
Wentzel K. R., Barry C. M., & Caldwell K. A. (2004). Friendships in middle school: Influences on motivation and school adjustment. Journal of Educational Psychology, 96 (2), 195203. Retrieved from
Wooldridge J. M. (2005). Simple solutions to the initial conditions problem in dynamic, nonlinear panel data models with unobserved heterogeneity. Journal of Applied Econometrics, 20 (1), 3954.
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Network Science
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