Abstract
Self-identification with peer crowds (jocks, popular kids, druggies, etc.) has an important influence on adolescent substance use behavior. However, little is known about the impact of the shared nature of crowd identification on different stages of adolescent drinking behavior, or the way crowd identification interacts with participation in school-sponsored sports activities. This study examines drinking influences from (1) peers with shared crowd identities, and (2) peers who jointly participate in organized sports at their school (activity members). This study introduces a new network analytic approach that can disentangle the effects of crowd identification and sports participation on individual behavior. Using survey data from adolescents in five high schools in a predominantly Hispanic/Latino district (N = 1,707), this paper examines the association between social influences and each stage of drinking behavior (intention to drink, lifetime, past-month, and binge drinking) by conducting an ordinal regression analysis. The results show that both shared identities and joint participation were associated with all stages of drinking, controlling for friends' influence. Additionally, shared identification overlapped with joint participation was associated with more frequent drinking. Related policy implications are discussed.
Keywords: adolescent alcohol use, affiliation exposure model, peer influence, two-mode affiliation network, multiplex networks, organized sports participation, crowd identification
References
- Agneessens F., & Roose H. (2008). Local structural patterns and attribute characteristics in 2-mode networks: p* models to map choices of theatre events. Journal of Mathematical Sociology, 32, 204–237 [Google Scholar]
- Audrey S., Holliday J., & Campbell R. (2008). Commitment and compatibility: Teachers' perspectives on the implementation of an effective school-based, peer-led smoking intervention. Health Education Journal, 67(2), 74–90 [Google Scholar]
- Barber B. L., Stone M., Hunt J., & Eccles J. S. (2005). Benefits of activity participation: The roles of identity affirmation and peer group norm sharing In Mahoney J. L., Larson R., & Eccles J. S. (Eds.), Organized activities as contexts of development: Extracurricular activities, after school and community programs (pp. 185–209). Mahwah, NJ: Lawrence Erlbaum Assoc Inc [Google Scholar]
- Brown B. B. (1990). Peer groups and peer cultures In Feldman S. S., & Elliott G. R. (Eds.), At the threshold: The developing adolescent (pp. 171–196). Cambridge, MA: Harvard University Press [Google Scholar]
- Brown B. B., Eicher S. A., & Petrie S. (1986). The importance of peer group (“crowd”) affiliation in adolescence. Journal of Adolescence, 9(1), 73–96 [DOI] [PubMed] [Google Scholar]
- Brown B. B., & Lohr M. J. (1987). Peer group affiliation and adolescent self-esteem: An integration of ego identity and symbolic interaction theories. Journal of Personality and Social Psychology, 52(1), 47–55 [DOI] [PubMed] [Google Scholar]
- Brown B. B., Lohr M. J., & Trujillo C. (1990). Multiple crowds and multiple life styles: Adolescents' perceptions of peer-group stereotypes In Muuss R. E. (Ed.), Adolescent behavior and society (4th ed.) (pp. 30–36). New York: McGraw-Hill Publishing Company [Google Scholar]
- Campbell R., Starkey F., Holliday J., Audrey S., Bloor M., Parry-Langdon N. . . Moore L. (2008). An informal school-based peer-led intervention for smoking prevention in adolescence (ASSIST): A cluster randomized trial. The Lancet, 371, 1595–1602 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Coleman J. S. (1961). The adolescent society. New York: Free Press [Google Scholar]
- Coleman J. C. (1974). Relationships in adolescence. London: Routledge & Kegan Paul [Google Scholar]
- Coleman J. C. (1980). Friendship and peer group acceptance in adolescence In Adelson J. (Ed.), Handbook of adolescent psychology (pp. 408–431). New York: John Wiley [Google Scholar]
- Costanzo P. R., & Shaw M. E. (1966). Conformity as a function of age level. Child Development, 37, 967–975 [Google Scholar]
- Daraganova G., & Robins G. (2013). Autologistic actor attribute models In Lusher D., Koskinen J., & Robins G. L. (Eds.), Exponential random graph models for social networks: Theories, methods and applications. Cambridge, MA: Cambridge University Press [Google Scholar]
- Darling N. (2005). Participation in extracurricular activities and adolescent adjustment: Cross-sectional and longitudinal findings. Journal of Youth and Adolescence, 34(5), 493–505 [Google Scholar]
- Eccles J. S., & Barber B. L. (1999). Student council, volunteering, basketball, or marching band: What kind of extracurricular involvement matters? Journal of Adolescent Research, 14(1), 10–43 [Google Scholar]
- Eccles J. S., Barber B. L., Stone M., & Hunt J. (2003). Extracurricular activities and adolescent development. Journal of Social Issues, 59(4), 865–889 [Google Scholar]
- Eder D. (1985). The cycle of popularity: Interpersonal relations among female adolescents. Sociology of Education, 58(3), 154–165 [Google Scholar]
- Erikson E. H. (1968). Identity, youth, and crisis. New York: Norton [Google Scholar]
- Frank O., & Strauss D. (1986). Markov graphs. Journal of the American Statistical Association, 81, 832–842 [Google Scholar]
- Fujimoto K. (2012). Using mixed-mode networks to disentangle multiple sources of social influence In Yang S. J., Greenberg A. M. & Endsley M. (Eds.), Social Computing, Behavioral–Cultural Modeling and Prediction, Lecture Notes in Computer Science, Vol. 7227 (pp. 214–221), Berlin/Heidelberg: Springer [Google Scholar]
- Fujimoto K., Chou C.-P., & Valente T. W. (2011). The network autocorrelation model using two-mode network data: Affiliation exposure and biasness in ρ. Social Networks, 33(3), 231–243 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Fujimoto K., Unger J., & Valente T. W. (2012). Network method of measuring affiliation-based peer influence: Assessing the influences on teammates smokers on adolescent smoking. Child Development, 83(2), 442–451 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Fujimoto K. & Valente T. W. (in press). Alcohol peer influence from participating in organized school activities among U. S. adolescents: A network approach. Health Psychology. doi: 10.1037/a0029466 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Gavin L. A., & Furman W. (1989). Age differences in adolescents' perceptions of their peer groups. Developmental Psychology, 25(5), 827–834 [Google Scholar]
- Handcock M. S., Hunter D. R., Butts C. T., Goodreau S. M., & Morris M. (2003). Statnet: Software tools for the statistical modeling of network data. Retrieved from http://statnetproject.org [DOI] [PMC free article] [PubMed]
- Hansen D. M., Larson R. W., & Dworkin J. B. (2003). What adolescents learn in organized youth activities: A survey of self-reported developmental experiences. Journal of Research on Adolescence, 13(1), 25–55 [Google Scholar]
- Harris K. M. (1999). The health status and risk behavior of adolescents in immigrant families In Hernandez D. (Ed.), Children of immigrants: Health, adjustment, and public assistance (pp. 286–347). Washington, DC: National Academy Press; [PubMed] [Google Scholar]
- Jessor R. (1984). Adolescent development and behavioral health In Matarazzo J. D., Weiss S. M., Herd J. A., Miller N. E., & Weiss S. M. (Eds.), Behavioral health: A handbook of health enhancement and disease prevention. New York: John Wiley and Sons [Google Scholar]
- La Greca A. M., Prinstein M. J., & Fetter M. D. (2001). Adolescent peer crowd affiliation: Linkages with health risk behaviors and close friendships. Journal of Pediatric Psychology of Addictive Behaviors, 26(3), 131–143 [DOI] [PubMed] [Google Scholar]
- Mahoney J. L. (2000). School extracurricular activity participation as a moderator in the development of antisocial patterns. Child Development, 71(2), 502–516 [DOI] [PubMed] [Google Scholar]
- Mahoney J. L., & Cairns R. B. (1997). Do extracurricular activities protect against early school dropout? Developmental Psychology, 33(2), 241–253 [DOI] [PubMed] [Google Scholar]
- Melnick M. J., Miller K. E., Sabo D. F., Farrell M. P., & Barnes G. M. (2001). Tobacco use among high school athletes and nonathletes: Results of the 1997 Youth Risk Behavior Survey. Adolescence, 36(144), 727–747 [PubMed] [Google Scholar]
- Miller K. E., Farrell M. P., Barnes G. M., Melnick, M. J., & Sabo D. (2005). Gender/racial differences in jock identity, dating, and adolescent sexual risk. Journal of Youth and Adolescence, 34(2), 123–136 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Miller K. E., Hoffman J. H., Barnes G. M., & Farrell M. P. (2003). Jocks, gender, race, and adolescent problem drinking. Journal of Drug Education, 33(4), 445–462 [DOI] [PubMed] [Google Scholar]
- Mosbach P., & Leventhal H. (1988). Peer group identification and smoking: Implications for intervention. Journal of Abnormal Psychology, 97(2), 238–245 [DOI] [PubMed] [Google Scholar]
- Newman P. R., & Newman B. M. (1976). Early adolescence and its conflict: Group identity versus alienation. Adolescence, 11, 261–274 [Google Scholar]
- Pate R. R., Trost S. G., Levin S., & Dowda M. (2000). Sports participation and health-related behaviors among US youth. Archives of Pediatrics and Adolescent Medicine, 154(9), 904–911 [DOI] [PubMed] [Google Scholar]
- Pattison P., & Wasserman S. (1999). Logit models and logistic regressions for social networks, II. Multivariate relationships. British Journal of Mathematical and Statistical Psychology, 52, 169–193 [DOI] [PubMed] [Google Scholar]
- Robins G. L., Pattison P., & Elliott P. (2001). Network models for social influence processes. Psychometrika, 66, 161–190 [Google Scholar]
- Robins G. L., Pattison P., Kalish Y., & Lusher D. (2007). An introduction to exponential random graph (p*) models for social networks. Social Networks, 29, 173–191 [Google Scholar]
- Royston P. (2004). Multiple imputation of missing values. Stata Journal, 4(3), 227–241 [Google Scholar]
- Simons-Morton B. G., & Farhat T. (2010). Recent findings on peer group influences on adolescent smoking. Journal of Primary Prevention, 31, 191–208 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Snijders T. A. B., Lomi A. & Torló V. J. (2013). A model for the multiplex dynamics of two-mode and one-mode networks, with an application to employment preference, friendship, and advice. Social Networks, 35, 265–276 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Sussman S., Dent C. W. & McCullar W. J. (2000). Group self-identification as a prospective predictor of drug use and violence in high-risk youth. Psychology of Addictive Behaviors, 14(2), 192–196 [PubMed] [Google Scholar]
- Sussman S., Pokhrel P., Ashmore R. D., & Brown B. B. (2007). Adolescent peer group identification and characteristics: A review of the literature. Addictive Behavior, 32(8), 1602–1627 [DOI] [PMC free article] [PubMed] [Google Scholar]
- Sussman S., Simon T. R., Stacy A. W., Dent C. W., Ritt A., Kipke M. D., . . . Flay B. R. (1999). The association of group self-identification and adolescent drug use in three samples varying in risk. Journal of Applied Social Psychology, 29(8), 1555–1581 [Google Scholar]
- Sussman S., Unger J. B., & Dent C. W. (2004). Peer group self-identification among alternative high school youth: A predictor of their psychosocial functioning five years later. International Journal of Clinical and Health Psychology, 41(1), 9–25 [Google Scholar]
- Valente T. W. (1995). Network models of the diffusion of innovations. Cresskill, NJ: Hampton Press [Google Scholar]
- Valente T. W. (2005). Network models and methods for studying the diffusion of innovations In Carrington P. J., Scott J., & Wasserman S. (Eds.), Models and methods in social network analysis: Structural analysis in the social sciences (pp. 98–116). Cambridge, MA: Cambridge University Press [Google Scholar]
- Valente T. W. (2010). Social networks and health: Models, methods, and applications. New York: Oxford University Press [Google Scholar]
- Valente T. W. (2012). Network interventions. Science, 337(6), 49–53 [DOI] [PubMed] [Google Scholar]
- Valente T. W., Fujimoto K., Unger J. B., Soto D., & Meeker D. (in press). Variations in network boundary and type: A study of adolescent peer influences. Social Networks. doi: 10.1016/j.socnet.2013.02.008 [DOI] [Google Scholar]
- Verkooijen K. T., de Vries N. K., & Nielsen G. A. (2007). Youth crowds and substance use: The impact of perceived group norm and multiple group identification. Psychology of Addictive Behaviors, 21(1), 55–61 [DOI] [PubMed] [Google Scholar]
- Wang P. (2013). ERGM extensions: Models for multiple networks and bipartite networks In Lusher D., Koskinen J., & Robins G. L. (Eds.), Exponential random graph models for social networks: Theories, methods and applications. New York: Cambridge University Press [Google Scholar]
- Wang P., Pattison P. E., & Robins G. L. (2013. a). Exponential random graph model specifications for bipartite networks – A dependence hierarchy. Social Networks, 35(2), 211–222 [Google Scholar]
- Wang P., Robins G. L., & Pattison P. E., (2006). PNet: A program for simulations and estimations of exponential random graph models., Australia: Melbourne School of Psychological Sciences, The University of Melbourne; URL: http://sna.unimelb.edu.au/PNet [Google Scholar]
- Wang P., Robins G. L., Pattison P. E., & Lazega E. (2013. b). Exponential random graph models for multilevel networks. Social Networks, 35(1), 96–115 [Google Scholar]
- Wasserman S., & Pattison P. E. (1996). Logit models and logistic regression for social networks, I. An introduction to Markov graphs and p*. Psychometrika, 6(3), 401–425 [Google Scholar]
- Williams R. (2006). Generalized ordered logit/partial proportional odds models for ordinal dependent variables. The Stata Journal, 6(1), 58–82 [Google Scholar]
- Wichstrøm T., & Wichstrøm L. (2009). Does sports participation during adolescence prevent later alcohol, tobacco and cannabis use? Addiction, 104(1), 138–149 [DOI] [PubMed] [Google Scholar]