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The Interaction Between the Development of Deviant Peer Influence and Resistance to Peer Influence: Relevance for Predicting Offending in Early Adulthood

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Abstract

Objectives

Elucidate susceptibility to peer influence developmental trajectories across adolescence and early adulthood among a sample of juvenile offenders. Examine the relevance of susceptibility to peer influence and the interaction between deviant peer association and susceptibility to peer influence for predicting offending frequency in early adulthood.

Methods

The Pathways to Desistance data was used in analyses. Analyses utilized group-based trajectory modeling to elucidate general patterns of development of susceptibility to peer influence. The second phase of analyses utilized a series of negative binomial regression to estimate the effects of susceptibility group assignment, deviant peer association group assignment, and the interaction between these constructs for predicting offending frequency at age 23.

Results

A two-group model was found to best fit the susceptibility to peer influence data. Negative binomial regression results indicate that the interactions between assignment to the High and Moderate deviant peer association groups and high susceptibility group significantly predicted elevated offending at age 23.

Conclusions

Juvenile offenders with the highest number of deviant peers in early adulthood are at risk for higher offending frequency, but only when they are highly susceptible to peer influence. The implications of results for criminal justice officials are discussed.

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Notes

  1. “Stacking” of the data entails the transformation of data so that a variable is created that is contingent upon a response to another variable. In the Pathways to Desistance study, participants entered at different ages. So, there is no specific observation period in which all participants are 23 years of age. Some participants reported being 23 at observation point 6, while others reported being 23 at observation point 7, etc. This stacking entailed creating a variable which consisted only of reports of offending frequency when a participant was 23 years old, regardless of which observation period this occurred in. The stacked offending variable then just describes offending frequency at age 23.

  2. The frequency of the following 24 crime types were added together to make a cumulative offending frequency score in the Pathways to Desistance study: destroy property, set fire, break-in to steal, shoplift, receive stolen property, use credit card illegally, stole car, sold marijuana, sold other drug, carjack, drive drunk, been paid by someone for sex, forced sex, killed someone, shot someone, shot at someone, robbery with weapon, robbery no weapon, beaten someone, in fight, fight part of gang, carried gun, entered car to steal, gone joyriding.

  3. Proportions of the sample assigned to these groups: Low = 32.1%; Moderate = 45%; High = 22.9%.

References

  1. Akers, R. L. (1973). Deviant behavior: a social learning approach. Belmont: Wadsworth Publishing Company.

    Google Scholar 

  2. Baskin-Sommers, A. R., & Baskin, D. (2016). Psychopathic traits mediate the relationship between exposure to violence and violent juvenile offending. Journal of Psychopathology and Behavioral Assessment, 38(3), 341–349.

    Article  Google Scholar 

  3. Boman IV, J. H. (2016). Do birds of a feather really flock together? Friendships, self-control similarity and deviant behaviour. British Journal of Criminology, 57(5), 1208–1229.

    Google Scholar 

  4. Boman, J. H., & Mowen, T. J. (2018). Same feathers, different flocks: breaking down the meaning of ‘behavioral Homophily’ in the etiology of crime. Journal of Criminal Justice, 54, 30–40.

    Article  Google Scholar 

  5. Broidy, L. M., Stewart, A. L., Thompson, C. M., Chrzanowski, A., Allard, T., & Dennison, S. M. (2015). Life course offending pathways across gender and race/ethnicity. Journal of Developmental and Life-Course Criminology, 1(2), 118–149.

    Article  Google Scholar 

  6. Cochran, J. K., Maskaly, J., Jones, S., & Sellers, C. S. (2017). Using structural equations to model Akers’ social learning theory with data on intimate partner violence. Crime & Delinquency, 63(1), 39–60.

    Article  Google Scholar 

  7. Costello, B. J., & Hope, T. L. (2016). Peer pressure, peer prevention: the role of friends in crime and conformity. Abingdom: Routledge.

    Google Scholar 

  8. DeMartino, C. H., Rice, R. E., & Saltz, R. (2015). An applied test of the social learning theory of deviance to college alcohol use. Journal of Health Communication, 20(4), 479–490.

    Article  Google Scholar 

  9. Dodge, K. A., Dishion, T. J., & Lansford, J. E. (2006). Deviant peer influences in intervention and public policy for youth. Social Policy Report. Volume 20, Number 1. Society for Research in Child Development. Ann Arbor, MI.

  10. Gao, Y., Yu, Y., & Ng, T. K. (2013). A study on the moderating effect of family functioning on the relationship between deviant peer affiliation and delinquency among Chinese adolescents. Advances in Applied Sociology, 3(03), 178.

    Article  Google Scholar 

  11. Gardner, M., & Steinberg, L. (2005). Peer influence on risk taking, risk preference, and risky decision making in adolescence and adulthood: an experimental study. Developmental Psychology, 41(4), 625–635.

    Article  Google Scholar 

  12. Glueck, S., & Glueck, E. (1950). Unraveling juvenile delinquency. Cambridge: Harvard University Press.

    Google Scholar 

  13. Gottfredson, M. R., & Hirschi, T. (1990). A general theory of crime. Palo Alto: Stanford University Press.

    Google Scholar 

  14. Hay, C., & Meldrum, R. (2015). Self-control and crime over the life course. Thousand Oaks: Sage Publications.

    Google Scholar 

  15. Higgins, G. E., & Makin, D. A. (2004). Does social learning theory condition the effects of low self-control on college students’ software piracy. Journal of Economic Crime Management, 2(2), 1–22.

    Google Scholar 

  16. Holt, T. J., Bossler, A. M., & May, D. C. (2012). Low self-control, deviant peer associations, and juvenile cyberdeviance. American Journal of Criminal Justice, 37(3), 378–395.

    Article  Google Scholar 

  17. Huesmann, L. R., Dubow, E. F., & Boxer, P. (2009). Continuity of aggression from childhood to early adulthood as a predictor of life outcomes: implications for the adolescent-limited and life-course-persistent models. Aggressive Behavior, 35(2), 136–149.

    Article  Google Scholar 

  18. Krohn, M. D., Gibson, C. L., & Thornberry, T. P. (2013). Under the protective bud the bloom awaits: a review of theory and research on adult-onset and late-blooming offenders. In Handbook of life-course criminology (pp. 183–200). New York: Springer.

    Chapter  Google Scholar 

  19. Lauritsen, J. L. (2005). Racial and ethnic differences in juvenile offending. In Our children, their children: confronting racial and ethnic differences in American juvenile justice (pp. 83–104).

    Chapter  Google Scholar 

  20. Little, M., & Steinberg, L. (2006). Psychosocial correlates of adolescent drug dealing in the inner city: potential roles of opportunity, conventional commitments, and maturity. Journal of Research in Crime and Delinquency, 43(4), 357–386.

    Article  Google Scholar 

  21. McGee, T. R., Farrington, D. P., Homel, R., & Piquero, A. R. (2015). Advancing knowledge about developmental and life-course criminology. Australian and New Zealand Journal of Criminology, 48(3), 307–313.

    Article  Google Scholar 

  22. McPherson, M., Smith-Lovin, L., & Cook, J. M. (2001). Birds of a feather: homophily in social networks. Annual Review of Sociology, 27(1), 415–444.

    Article  Google Scholar 

  23. Mobarake, R. K., Juhari, R., Yaacob, S. N., & Esmaeili, N. S. (2014). The moderating role of self-control in the relationship between peer affiliation and adolescents antisocial behavior in Tehran, Iran. Asian Social Science, 10(9), 71.

    Article  Google Scholar 

  24. Moffitt, T. E. (1993). Adolescence-limited and life-course-persistent antisocial behavior: a developmental taxonomy. Psychological Review, 100(4), 674–701.

    Article  Google Scholar 

  25. Moffitt, T. E. (2003). Life-course-persistent and adolescence-limited antisocial behavior: A 10-year research review and a research agenda. In B. B. Lahey, T. E. Moffitt, & A. Caspi (Eds.), Causes of conduct disorder and juvenile delinquency (pp. 49–75). New York, NY, US: Guilford Press.

  26. Moffitt, T. E. (2006). A review of research on the taxonomy of life-course persistent versus adolescence-limited antisocial behavior (Vol. 15, p. 277). F. T. Cullen, J. P. Wright, & K. R. Blevins (Eds.). Taking stock: the status of criminological theory. Routledge: New York, NY.

  27. Monahan, K. C., Steinberg, L., & Cauffman, E. (2009). Affiliation with antisocial peers, susceptibility to peer influence, and antisocial behavior during the transition to adulthood. Developmental Psychology, 45(6), 1520–1530.

    Article  Google Scholar 

  28. Mulvey, Edward P. Research on Pathways to Desistance [Maricopa County, AZ and Philadelphia County, PA]: subject measures, 2000–2010. ICPSR29961-v2. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], (2000–2010). 2013-01-07. https://doi.org/10.3886/ICPSR29961.v2.

  29. Nagin, D. (2005). Group-based modeling of development. Cambridge: Harvard University Press.

    Book  Google Scholar 

  30. Nagin, D. S., & Tremblay, R. E. (2005). Developmental trajectory groups: fact or a useful statistical fiction? Criminology, 43(4), 873–904.

    Article  Google Scholar 

  31. Norman, L. B., & Ford, J. A. (2015). Adolescent ecstasy use: a test of social bonds and social learning theory. Deviant Behavior, 36(7), 527–538.

    Article  Google Scholar 

  32. Sampson, R. J., & Groves, W. B. (1989). Community structure and crime: testing social-disorganization theory. American Journal of Sociology, 94(4), 774–802.

    Article  Google Scholar 

  33. Sampson, R. J., & Laub, J. H. (1995). Crime in the making: pathways and turning points through life. Cambridge: Harvard University Press.

    Google Scholar 

  34. Sampson, R. J., & Laub, J. H. (2003). Life-course desisters? Trajectories of crime among delinquent boys followed to age 70. Criminology, 41(3), 555–592.

    Article  Google Scholar 

  35. Schaefer, B. P., Vito, A. G., Marcum, C. D., Higgins, G. E., & Ricketts, M. L. (2015). Examining adolescent cocaine use with social learning and self-control theories. Deviant Behavior, 36(10), 823–833.

    Article  Google Scholar 

  36. Steinberg, L., & Monahan, K. C. (2007). Age differences in resistance to peer influence. Developmental Psychology, 43(6), 1531–1543.

    Article  Google Scholar 

  37. Sumter, S. R., Bokhorst, C. L., Steinberg, L., & Westenberg, P. M. (2009). The developmental pattern of resistance to peer influence in adolescence: will the teenager ever be able to resist? Journal of Adolescence, 32(4), 1009–1021.

    Article  Google Scholar 

  38. Turanovic, J. J., Reisig, M. D., & Pratt, T. C. (2015). Risky lifestyles, low self-control, and violent victimization across gendered pathways to crime. Journal of Quantitative Criminology, 31(2), 183–206.

    Article  Google Scholar 

  39. Warr, M. (2002). Companions in crime: the social aspects of criminal conduct. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  40. Wojciechowski, T. W. (2017a). The development of deviant peer association across the life-course and its relevance for predicting offending in early adulthood. Journal of Developmental and Life-Course Criminology, 4, 73–91. https://doi.org/10.1007/s40865-017-0072-7.

    Article  Google Scholar 

  41. Wojciechowski, T. W. (2018a). Trajectories of binge drinking behavior across adolescence among juvenile offenders and the role of ADHD for predicting development. Deviant Behavior,39(6), 807–821.

  42. Wojciechowski, T. W. (2018b). Victimization recency, development of anger, and violent offending in early adulthood: a developmental test of general strain theory. Deviant Behavior, 1–16. https://doi.org/10.1080/01639625.2018.1443766.

  43. Wolfe, S. E. (2015). Low self-control, gender, race, and offending in late life. Psychology, Crime & Law, 21(5), 426–451.

    Article  Google Scholar 

  44. Zimmerman, G. M., Botchkovar, E. V., Antonaccio, O., & Hughes, L. A. (2015). Low self-control in “bad” neighborhoods: assessing the role of context on the relationship between self-control and crime. Justice Quarterly, 32(1), 56–84.

    Article  Google Scholar 

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Wojciechowski, T.W. The Interaction Between the Development of Deviant Peer Influence and Resistance to Peer Influence: Relevance for Predicting Offending in Early Adulthood. J Dev Life Course Criminology 4, 322–342 (2018). https://doi.org/10.1007/s40865-018-0086-9

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