Socialization, Selection, or Both? The Role of Gene–Environment Interplay in the Association Between Exposure to Antisocial Peers and Delinquency
To better explain the near-universal association between peer and self-reported delinquency, three frameworks have been offered and have received varying degrees of support: (1) socialization or the social transmission of norms, attitudes, and behaviors among group members; (2) selection or the congregation of youth with similar traits and predispositions; and (3) enhancement or a combination of socialization and selection processes.
Making use of sibling pairs and peer network data from the National Longitudinal Study of Adolescent to Adult Health, the current study compares all three frameworks using modified bivariate Cholesky models to simultaneously examine gene-environment correlations (rGE) and interactions (G × E).
Findings revealed that peer deviance (as reported by peers themselves) moderated underlying influences on delinquency such that genetic influences decreased and environmental influences increased as peer deviance increased. While previous studies have reported additional patterns of moderation (e.g., increases in both genetic and environmental influences), such studies have relied on subjective measures of peer behavior, more restrictive measures of delinquency, and samples comprised of young children.
The results revealed preliminary evidence in favor of the selection hypothesis, but the overall patterns of moderation stemming from the examined G × E fall in line more closely with the enhancement hypothesis of peer influence.
KeywordsPeers Delinquency Developmental theory Gene–environment interplay
The authors would like to thank JC Barnes, Jon Brauer, and Jukka Savolainen for thoughtful comments on previous drafts of this study. We would also like to thank Laura Dugan and the three anonymous reviewers for their suggestions and comments, as they have certainly strengthened the study. The content of this article is the authors’ sole responsibility and any errors or omissions are solely ours. This research uses data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. Special acknowledgment is due Ronald R. Rindfuss and Barbara Entwisle for assistance in the original design. Information on how to obtain the Add Health data files is available on the Add Health website (http://www.cpc.unc.edu/addhealth). No direct support was received from Grant P01-HD31921 for this analysis.
- Akers RL (1973) Deviant behavior: a social learning approach. Wadsworth, BelmontGoogle Scholar
- Akers RL (2008) Self-control and social learning theory. In: Goode E (ed) Out of control: assessing the general theory of crime. Stanford University Press, Stanford, pp 77–89Google Scholar
- Akers RL, Jensen GF (2006) The empirical status of social learning theory: past, present, and future. In: Cullen FT, Wright JP, Blevins KR (eds) Taking stock: the status of criminological theory. Advances in criminological theory, vol 15. Transaction Publishers, New Brunswick, pp 37–76Google Scholar
- Burgess RL, Akers RL (1966) A differential association-reinforcement theory of criminal behavior. Soc Probl 19:101–113Google Scholar
- Caspi A (2002) Social selection, social causation, and developmental pathways: empirical strategies for better understanding how individuals and environments are linked across the life course. In: Pulkkinen L, Caspi A (eds) Paths to successful development. Personality in the life course. Cambridge University Press, Cambridge, pp 281–301CrossRefGoogle Scholar
- Glueck S, Glueck E (1950) Unraveling juvenile delinquency. The Commonwealth Fund, New YorkGoogle Scholar
- Gottfredson MR, Hirschi T (1990) A general theory of crime. Stanford University Press, StanfordGoogle Scholar
- Harris JR (2009) The nurture assumption: why children turn out the way they do. Free Press, New YorkGoogle Scholar
- Harris KM (2011) Design features of add health. Carolina Population Center, University of North Carolina at Chapel Hill, Chapel HillGoogle Scholar
- Harris KM (2013) The add health study: design and accomplishments. Carolina Population Center, University of North Carolina at Chapel Hill, Chapel HillGoogle Scholar
- Harris KM, Halpern CT, Whitsel E, Hussey J, Tabor J, Entzel P, Udry JR (2009) The national longitudinal study of adolescent health: research design. http://www.cpc.unc.edu/projects/addhealth/design
- Hirschi T (1969) Causes of delinquency. University of California Press, BerkeleyGoogle Scholar
- Muthén LK, Muthén BO (1998–2012). Mplus: stataistical analysis with latent variables. User’s guide, 7th edn. Muthén & Muthén, Los AngelesGoogle Scholar
- Plomin R, DeFries JC, Knopik VS, Neiderheiser J (2013) Behavioral genetics, 6th edn. Worth Publishers, New YorkGoogle Scholar
- Scarr S, McCartney K (1983) How people make their own environments: a theory of genotype-environment effects. Child Dev 54:424–435Google Scholar
- Sutherland EH (1947) Principles of criminology, 4th edn. J.B. Lippincott, PhiladelphiaGoogle Scholar
- Sutherland EH, Cressey DR (1955) Principles of criminology, 5th edn. J.B. Lippincott, PhiladelphiaGoogle Scholar
- Turkheimer E, Harden KP (2014) Behavior genetic research methods: testing quasi-causal hypotheses using multivariate twin data. In: Reis HT, Judd CM (eds) Handbook of research methods in social and personality psychology. Cambridge University Press, Cambridge, pp 159–187Google Scholar
- Udry JR (2003) The national longitudinal study of adolescent health (Add Health), waves I and II, 1994–1996; wave III, 2001–2002 [machine-readable data file and documentation]. Carolina Population Center, University of North Carolina at Chapel Hill, Chapel HillGoogle Scholar