Network position


Network position (isolate, member and liaison), peer-group substance use, and their interaction were examined as predictors of cigarette, alcohol, and marijuana use in a sample of 163 urban sixth, seventh, and eighth graders. Two measures of peer substance use were compared: one based on social network analysis (SNA), the other on perceptions of use. Results varied by substance. For cigarettes, network position and the interaction between position and peer-group use predicted use in the model using SNA to measure peer use. Liaisons were most likely to smoke, but isolates’ and members’ smoking was significantly associated with peer smoking. For alcohol, perceptions of peer- group alcohol use predicted individual use. For marijuana, peer-group use and the interaction between position and peer use predicted use, regardless of measure. Liaisons’ marijuana use was significantly associated with peer use. The importance of SNA for understanding peer factors in adolescent substance use is discussed.



Peer relationships; networks; substance use; alcohol use; peer groups; tobacco use; smoking

Social network analysis (SNA) is an attractive approach for assessing social relationships, given the unique information it provides on interaction pat- terns, social structures, and their implications (Wasserman & Faust, 1994). It can be used to examine characteristics of individuals based on their connections to others, to compare those who occupy different peer groups, to examine processes of peer selection and socialization, and to assess the spread of information or behavior throughout a social system (Kobus, 2003). For these and other reasons, network analysis has come to be preferred over self-report methods for measuring homophily (similarity among peers) in studies of adolescent substance use (Bauman & Ennett, 1996; Bauman & Fisher, 1986; Kobus, 2003).

Network Position and Substance Use

The theoretical perspective of sociologist Georg Simmel (1950) suggests that peer influence is greatest in the most close-knit groups—a perspective that maps well with commonly held perceptions of peer pressure and parental concerns about “who my child’s friends are.” Simmel’s theoretical perspec- tive is based on the concept of triads, groups of three or more individuals connected by triangular relational ties, that is, where all three individuals identify each other as friends. The influential nature of peers is considered to be heightened in triads because of the potential for two-against-one pressures that lead to stronger enforcement of norms than is seen in dyads or among isolates (Bowen, 1978; Kerr & Bowen, 1988; Krackhardt, 1996; Simmel, 1950). According to this perspective, members of substance-using peer groups would be most similar to friends in their substance use behaviors.

Perceptions Versus Friend Report of Substance Use

We also consider the issue of whether peer substance use is measured accurately through perceptions of friend behavior. Various investigators (Bauman & Ennett, 1996; Bauman & Fisher, 1986; Kandel, 1996; Kobus, 2003) have argued that findings of homophily derived from perceptions of peer use are flawed because they reflect respondents’ projections of their own behavior onto their friends, known otherwise as a rater effect. Studies that have used network analysis and friend reports of their own behavior have found somewhat smaller effects than those using perceptions of peer use, leading to the suspicion that perceptions overestimate actual peer use (Bauman & Ennett, 1994, 1996; Bauman & Fisher, 1986; Eiser & van der Pligt, 1984; Fisher & Bauman, 1988; Kandel, 1996). How- ever, it also has been argued that adolescents’ perceptions of substance use prevalence are more important in predicting substance use than direct peer pres- sure (Urberg, Shyu, & Liang, 1990).

The Present Study

In this study, we add to the extant literature by examining the relation between network position and adolescent substance use with a heightened focus on referent peer groups. Previous studies that have considered the interaction of network position and peer groups have been limited by their comparisons of those who belong to tight-knit peer groups or those who are peripheral to these groups. We borrow from Simmel (1950) and Granovetter (1973) and their concepts of triadic or dyadic relationships and strong or weak ties to expand this focus on peer groups, specifically identifying referent peer groups for each network position separately. Referent peer groups are deter- mined by the nature of the relational characteristics of each network position and the individual’s location in the social system. For example, we identify the referent peer group for members as their tight-knit, triadic network and the referent group for liaisons as their larger, loose-knit dyadic network. In addition, we conduct separate analyses using perceptions of friends’ sub- stance use as an alternate way of measuring peer-group substance use.


Research Participants

This study was approved by the Institutional Review Board of the University of Illinois at Chicago. Participants were recruited from a population of sixth-, seventh-, and eighth-grade students who attended regular education classes at a K-8 Chicago public elementary school. The participating school was selected based on its size (n  700) and rate of daily attendance (93.8%; Illinois State Board of Education, 1996), both of which were near the median for Chicago Public Schools. Of the 188 eligible students, 165 (88%) returned signed parental consent and student assent forms. Two students reported having been dishonest in answering the questionnaire and were excluded  from analysis. The remaining 163 students (87% of the eligible population) completed study measures. The sample was approximately equally distrib- uted by gender and grade and was predominantly White (65%). The ethnic distribution of the sample did not differ significantly from that of the school population, 2(2, N  163)  1.11, ns. Demographic information is presented in Table 1.


The Teen Survey included items that assessed participants’ demographic information, substance use, perceived substance use of friends, and nominations of friends. This information was used to calculate network position and substance use of those in participants’ friendship networks, as described below.

  • Demographics
  • Past 6-month substance use
  • Perceived friend substance use
  • Friendship nominations
  • Network position
  • Network substance use
  • School-based friendships
  • Self-perceptions of social acceptance and close friendships


Participants were administered the Teen Survey at their desks by an experi- menter unknown to them in an extended study hall period. Participants absent during data collection (n  8) were administered measures in small groups at a later date. The 23 participants (12%) who did not participate in the study had a supervised study hall during measure administration. Following survey completion, participants were provided with a one-page, written debriefing statement and received a T-shirt of a local, popular sports team.


Preliminary Analyses

Nearly 90% of the sample (89.9%) reported that more than half of their friends attended school with them and were in the sixth, seventh, or eighth grades. The number of friends attending the same school did not differ by network position, F (2, 155)  1.92, ns.

Examination of Study Questions

We used generalized linear models (McCullagh & Nelder, 1989; Nelder, 1961) through SAS PROC GENMOD to address our research questions about peer effects on adolescent substance use.

Cigarette Use

There was no overall effect of peer-group cigarette use, regardless of whether network use or perceived friend use was the measure of peer smoking. In the model using network use, there was a significant effect for network position.

Alcohol Use

On past 6-month alcohol use, the level of peer-group use was associated with the level of individual alcohol use but was significant only in the model using perceived friend use (p  .01; p  .06 in network use model).

Marijuana Use

A main effect was found for the association between peer-group marijuana uses, in both models (p < .01), with friend marijuana use predicting individual marijuana use. A marginal effect was found in analyses of network use for isolates versus liaisons on marijuana use, with isolates more likely than liaisons to use marijuana overall (p = .06). This effect was moderated by a significant interaction between peer marijuana use and network position in both models, as is shown in the top and bottom right panels of Figure 1. Liaisons were more affected by the marijuana use of their peers than either isolates or members (p < .05 or p < .01, see Table 3).


In this study we examine the relation between social connectedness and use of cigarettes, alcohol, and marijuana in a sample of urban sixth, seventh, and eighth graders. We use SNA to identify friendship networks and to categorize youth into one of three network positions (member, liaison, isolate). Findings reveal that network position, referent peer-group substance use, and their interaction all predict early adolescent substance use. However, the specific patterns of effects vary by substance.


Some limitations should be considered when interpreting these results. Fore- most among these is the cross-sectional nature of the study, making it impossible to determine whether the effects obtained are because of peer selection or influence (Kobus, 2003). Other studies using longitudinal data have found evidence for both types of peer effects on adolescent risk behav- iors (Ennett & Bauman, 1994; Henry, Schoeny, Deptula, & Slavick, 2007; Pearson & Michell, 2000). At the same time, this article adds to the literature on the effects of peer-group structure on risk behaviors (Ennett & Bauman, 1993; Fang et al., 2003; Henry & Kobus, 2007; Pearson et al., 2006).

Implications of Findings

The findings of this study have implications for future research on the prevention and treatment of substance use. Additional research should examine the possibility that grouping substance-using youth together for treatment may have unintended negative consequences.

Authors’ Note

These data were collected as part of the first author’s dissertation. The authors would like to thank the Chicago Tribune and the Chicago Bulls for their finan-cial support of this project. We gratefully acknowledge the assistance of Olga Reyes, Karen Gillock, Michael Heinstein, George Greene, Bernadette San- chez, and the teachers and principal at the participant school.


Alexander, C., Piazza, M., Mekos, D., & Valente, T. (2001). Peers, schools, and ado- lescent cigarette smoking. Journal of Adolescent Health, 29, 22-30.

Aloise-Young, P. A., Graham, J. W., & Hansen, W. B. (1994). Peer influence on smoking initiation during early adolescence: A comparison of group members and group outsiders. Journal of Applied Psychology, 79, 281-287.

Bauman, K. E., & Ennett, S. T. (1994). Peer influence on adolescent drug use. Ameri- can Psychologist, 49, 820-822.

Bauman, K. E., & Ennett, S. T. (1996). On the importance of peer influence for ado- lescent drug use: Commonly neglected considerations. Addiction, 91, 185-198.

Bauman, K. E., & Fisher, L. A. (1986). On the measurement of friend behavior in research on friend influence and selection: Findings from longitudinal studies of adolescent smoking and drinking. Journal of Youth and Adolescence, 15, 345-353. Borsari, B., & Carey, K. B. (2000). Effects of a brief motivational intervention with college student drinkers. Journal of Consulting and Clinical Psychology, 68, 728-733.

Bowen, M. (1978). Family therapy in clinical practice. Northvale, NJ: Jason Aronson. Bray, J. H., Adams, G. J., Getz, J. G., & McQueen, A. (2003). Individuation, peers, and adolescent alcohol use: A latent growth analysis. Journal of Consulting and Clinical Psychology, 71, 553-564.

Brown, B. B., Dolcini, M. M., & Leventhal, A. (1997). Transformations in peer relation- ships at adolescence: Implications for health-related behavior. In J. Schulenberg,

L. Maggs, & K. Hurrelmann (Eds.), Health risks and developmental transitions during adolescence (pp. 161-189). New York: Cambridge University Press.

Burt, R. S. (1981). Studying status/role-sets as ersatz network positions in mass surveys. Sociological Methods and Research, 9, 313-337.

Cairns, R., Gariepy, J., & Kindermann, T. (1990). Identifying social clusters in natural settings. Unpublished manuscript, University of North Carolina at Chapel Hill.

Coffey, C., Lynskey, M., Wolfe, R., & Patton, G. C. (2000). Initiation and progres- sion of cannabis use in a population-based Australian adolescent longitudinal study. Addiction, 95, 1679-1690.

Curran, P. J., Stice, E., & Chassin, L. (1997). The relation between adolescent alcohol use and peer alcohol use: A longitudinal random coefficients model. Journal of Consulting and Clinical Psychology, 65, 130-140.

Dishion, T. J., McCord, J., & Poulin, F. (1999). When interventions harm: Peer groups and problem behavior. American Psychologist, 54, 755-764.

Eiser, J. R., & van der Pligt, J. (1984). Attitudinal and social factors in adolescent smoking: In search of peer group influence. Journal of Applied Social Psychology, 14, 348-363. 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, 226-236.

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, 653-663.

Ennett, S. T., Bauman, K. E., Hussong, A., Faris, R., Foshee, V. A., Cai, L., et al. (2006). The peer context of adolescent substance use: Findings from social net- work analysis. Journal of Research on Adolescence, 16, 159-186.

Fang, X., Li, X., Stanton, B., & Dong, Q. (2003). Social network positions and smok- ing experimentation among Chinese adolescents. American Journal of Health Behavior, 27, 257-267.

Fisher, L. A., & Bauman, K. E. (1988). Influence and selection in the friend-ado- lescent relationship: Findings from studies of adolescent smoking and drinking. Journal of Applied Social Psychology, 18, 289-314.

Granovetter, M. S. (1973). The strength of weak ties. American Journal of Sociology, 78, 1360-1380.

Harter, S. (1988). Manual for the Self-perception Profile for Adolescents. Unpub- lished manuscript, University of Denver. Denver, CO.

Henry, D. B. (1996). FNET: A computer program for social network analysis of peer nomination data (Technical report). Chicago: University of Illinois at Chicago, Institute for Juvenile Research.

Henry, D., Guerra, N. G., Huesmann, L. R., Tolan, P. H., VanAcker, R., & Eron, L.

(2000). Normative influences on aggression in urban elementary school class- rooms. American Journal of Community Psychology, 28, 59-81.

Henry, D. B. (2008). Changing classroom social settings through attention to norms. In

Shinn & H. Yoshikawa (Eds.), Changing schools and community organizations to foster positive youth development (pp. 40-57). New York: Oxford University Press.

Henry, D. B., & Kobus, K. (2007). Early adolescent social networks and substance use. Journal of Early Adolescence, 27, 346-362.

Henry, D., Schoeny, M., Deptula, D., & Slavick, J. (2007). Peer selection and social- ization effects on adolescent intercourse without a condom and attitudes about the costs of sex. Child Development, 78, 825-838.

Iacobucci, D. (1994). Graphs and matrices. In S. Wasserman & F. Faust (Eds.), Social network analysis: Methods and applications (pp. 92-166). Cambridge, UK: Cam- bridge University Press.

Illinois State Board of Education. (1996). [School report cards]. Unpublished raw data. Jørgensen, M. H., Curtis, T., Christensen, P. H., & Grønbæk, M. (2007). Harm mini-

mization among teenage drinkers: Findings from an ethnographic study on teen- age alcohol use in a rural Danish community. Addiction, 102, 554-559.

Kandel, D. B. (1996). The parental and peer contexts of adolescent deviance: An alge- bra of interpersonal influence. Journal of Drug Issues, 26, 289-315.

Kerr, M., & Bowen, M. (1988). Family evaluation: An approach based on Bowen theory. New York: Norton.

Kiesner, J., Poulin, F., & Nicotra, E. (2003). Peer relations across contexts: Individ- ual-network homophily and network inclusion in and after school. Child Develop- ment, 74, 1328-1343.

Knoke, D., & Kuklinski, J. H. (1982). Network analysis. Beverly Hills, CA: Sage. Krackhardt, D. (1987). Cognitive social structures. Social Networks, 9, 109-134. Krackhardt, D. (1996). Groups, roles, and Simmelian ties in organization. (H. John

Heinz III School of Public Policy and Management Working Paper Series). Pitts- burgh, PA: Carnegie Mellon University.

Kobus, K. (2003). Peers and adolescent smoking. Addiction, 98, S37-S55.

Komro, K. A., Flay, B. R., Hu, F. B., Zelli, A., Rashid, J., & Amuwo, S. (1998). Urban pre-adolescents report perceptions of easy access to drugs and weapons. Journal of Child and Adolescent Substance Abuse, 8, 77-90.

Kuntsche, E., & Jordan, M. D. (2005). Adolescent alcohol and cannabis use in rela- tion to peer and school factors: Results of multilevel analyses. Drug and Alcohol Dependence, 84, 167-184.

McCullagh, P., & Nelder, J. A. (1989). Generalized linear models (2nd ed.). New York: Chapman & Hall.

Metropolitan Area Child Study Research Group. (2002). A cognitive-ecological approach to preventing aggression in urban settings: Initial outcomes for high risk children. Journal of Consulting and Clinical Psychology, 70, 179-194.

Michell, L. (1997). Loud, sad or bad: Young people’s perceptions of peer groups and smoking. Heath Education Research, 12, 1-14.

Michell, L., & Amos, A. (1997). Girls, pecking order, and smoking. Social Science and Medicine, 44, 1861-1869.

Nelder, J. A. (1961). The fitting of a generalization of the logistic curve. Biometrics, 17, 89-110.

Nichter, M., Nichter, M., Vuckovic, N., Quintero, G., & Ritenbaugh, C. (1997). Smoking experimentation and initiation among adolescent girls: Qualitative and quantitative findings. Tobacco Control, 6, 285-295.

Oetting, E. R., & Beauvais, F. (1987). Peer cluster theory, socialization characteris- tics, and adolescent drug use: A path analysis. Journal of Counseling Psychology, 34, 205-213.

Pearson, M., & Michell, L. (2000). Smoke rings: Social network analysis of friend- ship groups, smoking and drug taking. Drugs: Education, Prevention & Policy,  7, 21-36.

Pearson, M., Sweeting, H., West, P., Young, R., Gordon, J., & Turner, K. (2006). Adolescent substance use in different social and peer contexts: A social network analysis. Drugs: Education, Prevention & Policy, 13, 519-536.

Simmel, G. (1950). The sociology of Georg Simmel (K. H. Wolff, Trans.). New York: Free Press.

Tolan, P. H., Gorman-Smith, D., & Henry, D. B. (2003). The developmental-ecology of urban males’ youth violence. Developmental Psychology, 39, 274-291.

Urberg, K. A., Shyu, S., & Liang, J. (1990). Peer influence in adolescent cigarette smoking. Addictive Behaviors, 15, 247-255.

Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applica- tions. New York: Cambridge University Press.

Leave a Reply

Your email address will not be published. Required fields are marked *