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Original Communication

Relationships Between Social Networks and Mental Health

An Exponential Random Graph Model Approach among Romanian Adolescents

Published Online:https://doi.org/10.1024/1421-0185/a000186

Abstract. Social networks have an important effect on health, and social network analysis has become essential for understanding human behavior and vulnerability. Using exponential random graph models (ERGM), this study explores the associations between mental health and network structure (or more specifically, mental health homophily) and the association between poor mental health and social isolation. Two classes of Romanian adolescents aged 12–14 years participated in the study (n = 26 in each class). We assessed school network, sociodemographic covariates, and mental health using the Strengths and Difficulties Questionnaire (SDQ). ERGM was first used to test the presence of sex and mental health homophily and then to test whether mental health was a predictor of social isolation. The results showed homophily patterns regarding sex and mental health. Moreover, participants with a higher SDQ score had a lower probability of a tie. Overall, this study showed how social networks are structured with different forms of homophily and that adolescents with poor mental health are more likely to be social isolates. Thus, prevention and interventions should focus on these vulnerable adolescents. Methodological advances like ERGM constitute a promising avenue for further research.

References

  • Bollen, J., Gonçalves, B., Ruan, G., & Mao, H. (2011). Happiness is assortative in online social networks. Artificial Life, 17, 237–251. doi 10.1162/artl_a_00034 First citation in articleCrossrefGoogle Scholar

  • Cornwell, B. (2009). Good health and the bridging of structural roles. Social Networks, 31, 92–103. doi 10.1016/j.socnet.2008.10.005 First citation in articleCrossrefGoogle Scholar

  • Daw, J., Margolis, R., & Verdery, A. M. (2015). Siblings, friends, course-mates, club-mates: How adolescent health behavior homophily varies by race, class, gender, and health status. Social Science & Medicine, 125, 32–39. doi 10.1016/j.socscimed.2014. 02.047 First citation in articleCrossrefGoogle Scholar

  • Faris, R., & Ennett, S. (2012). Adolescent aggression: The role of peer group status motives, peer aggression, and group characteristics. Social Networks, 34, 371–378. doi 10.1016/j.socnet.2010.06.003 First citation in articleCrossrefGoogle Scholar

  • Gonet, M. M. (1994). Counseling the adolescent substance abuser: School-based intervention and prevention. Thousand Oaks, CA: Sage. First citation in articleGoogle Scholar

  • Goodman, A., & Goodman, R. (2009). Strengths and Difficulties Questionnaire as a dimensional measure of child mental health. Journal of the American Academy of Child and Adolescent Psychiatry, 48, 400–403. doi 10.1097/CHI.0b013e3181985068 First citation in articleCrossrefGoogle Scholar

  • Goodman, R., Meltzer, H., & Bailey, V. (1998). The Strengths and Difficulties Questionnaire: A pilot study on the validity of the self-report version. European Child & Adolescent Psychiatry, 7, 125–130. doi 10.1007/s007870050057 First citation in articleCrossrefGoogle Scholar

  • 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, 103–125. doi 10.1353/dem.0.0045 First citation in articleCrossrefGoogle Scholar

  • Greenblatt, M., Becerra, R. M., & Serafetinides, E. A. (1982). Social networks and mental health: An overview. The American Journal of Psychiatry, 139, 977–984. doi 10.1176/ajp.139.8.977 First citation in articleCrossrefGoogle Scholar

  • Haas, S. A., Schaefer, D. R., & Kornienko, O. (2010). Health and the structure of adolescent social networks. Journal of Health and Social Behavior, 51, 424–439. doi 10.1177/0022146510386791 First citation in articleCrossrefGoogle Scholar

  • Hall, J. A., & Valente, T. W. (2007). Adolescent smoking networks: The effects of influence and selection on future smoking. Addictive Behaviors, 32, 3054–3059. doi 10.1016/j.addbeh.2007.04.008 First citation in articleCrossrefGoogle Scholar

  • Handcock, M. S., Hunter, D. R., Butts, C. T., Goodreau, S. M., & Morris, M. (2008). statnet: Software tools for the representation, visualization, analysis and simulation of network data. Journal of Statistical Software, 24(1), doi 10.18637/jss.v024.i01 First citation in articleCrossrefGoogle Scholar

  • Harris, J. K. (2013). An introduction to exponential random graph modeling. Thousand Oaks, CA: Sage. First citation in articleGoogle Scholar

  • Jeon, K. C., & Goodson, P. (2015). U. S. adolescents’ friendship networks and health risk behaviors: A systematic review of studies using social network analysis and Add Health data. PeerJ, 3, e1052. doi 10.7717/peerj.1052 First citation in articleGoogle Scholar

  • Krivitsky, P. N., & Kolaczyk, E. D. (2015). On the question of effective sample size in network modeling: An asymptotic inquiry. Statistical Science, 30, 184–198. doi 10.1214/14-STS502 First citation in articleCrossrefGoogle Scholar

  • Larson, R. W., & Verma, S. (1999). How children and adolescents spend time across the world: Work, play, and developmental opportunities. Psychological Bulletin, 125, 701–736. doi 10.1037/0033-2909.125.6.701 First citation in articleCrossrefGoogle Scholar

  • Lavy, V., & Sand, E. (2012). The friends factor: How students’ social networks affect their academic achievement and well-being? [NBER Working Paper No. 18430]. Retrieved from http://www.nber.org/papers/w18430 First citation in articleGoogle Scholar

  • Macdonald, D. I. (1989). Drugs, drinking, and adolescents. Chicago, IL: Year Book Medical Publishers. First citation in articleGoogle Scholar

  • McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001). Birds of a feather: Homophily in social networks. Annual Review of Sociology, 27, 415–444. doi 10.1146/annurev.soc.27.1.415 First citation in articleCrossrefGoogle Scholar

  • Morris, M., Handcock, M. S., & Hunter, D. R. (2008). Specification of exponential-family random graph models: Terms and computational aspects. Journal of Statistical Software, 24, 1548–7660. doi 10.18637/jss.v024.i04 First citation in articleCrossrefGoogle Scholar

  • Prinstein, M. J. (2007). Moderators of peer contagion: A longitudinal examination of depression socialization between adolescents and their best friends. Journal of Clinical Child and Adolescent Psychology, 36, 159–170. doi 10.1080/15374410701274934 First citation in articleCrossrefGoogle Scholar

  • Prinstein, M. J., & Dodge, K. A. (2008). Understanding peer influence in children and adolescents. New York: Guilford. First citation in articleGoogle Scholar

  • Robins, G., Pattison, P., Kalish, Y., & Lusher, D. (2007). An introduction to exponential random graph (p*) models for social networks. Social Networks, 29, 173–191. doi 10.1016/j.socnet.2006.08.002 First citation in articleCrossrefGoogle Scholar

  • Rubin, K. H., Bukowski, W. M., & Parker, J. G. (2006). Peer interactions, relationships, and groups. In N. EisenbergW. DamonR. M. LernerEds., Handbook of child psychology: Vol. 3. Social, emotional and personality development (6th ed., pp. 571–645). Hoboken, NJ: Wiley. First citation in articleGoogle Scholar

  • Schaefer, D. R., Kornienko, O., & Fox, A. M. (2011). Misery does not love company: Network selection mechanisms and depression homophily. American Sociological Review, 76, 764–785. doi 10.1177/0003122411420813 First citation in articleCrossrefGoogle Scholar

  • Schaefer, D. R., & Simpkins, S. D. (2014). Using social network analysis to clarify the role of obesity in selection of adolescent friends. American Journal of Public Health, 104, 1223–1229. doi 10.2105/AJPH.2013.301768 First citation in articleCrossrefGoogle Scholar

  • Scott, J. (2012). Social network analysis (3rd ed.). London, UK: Sage. First citation in articleGoogle Scholar

  • Settersten, R. A. (2015). Relationships in time and the life course: The significance of linked lives. Research in Human Development, 12, 217–223. doi 10.1080/15427609.2015.1071944 First citation in articleCrossrefGoogle Scholar

  • Valente, T. W. (2012). Network interventions. Science, 337, 49–53. doi 10.1126/science.1217330 First citation in articleCrossrefGoogle Scholar

  • Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge, UK: Cambridge University Press. First citation in articleCrossrefGoogle Scholar