Journal of Experimental Criminology

, Volume 11, Issue 1, pp 71–95 | Cite as

Gang membership and substance use: guilt as a gendered causal pathway

  • Donna L. Coffman
  • Chris Melde
  • Finn-Aage Esbensen



We examine whether anticipated guilt for substance use is a gendered mechanism underlying the noted enhancement effect of gang membership on illegal drug use. We also demonstrate a method for making stronger causal inferences when assessing mediation in the presence of moderation and time-varying confounding.


We estimate a series of inverse propensity weighted models to obtain unbiased estimates of mediation in the presence of confounding of the exposure (i.e., gang membership) and mediator (i.e., anticipated guilt) using three waves of data from a multi-site panel study of a law-related education program for youth (N = 1,113).


The onset of gang membership significantly decreased anticipated substance use guilt among both male and female respondents. This reduction was significantly associated with increased frequency of substance use only for female respondents, however, suggesting that gender moderates the mechanism through which gang membership influences substance use.


Criminologists are often concerned with identifying causal pathways for antisocial and/or delinquent behavior, but confounders of the exposure, mediator, and outcome often interfere with efforts to assess mediation. Many new approaches have been proposed for strengthening causal inference for mediation effects. After controlling for confounding using inverse propensity weighting, our results suggest that interventions aimed at reducing substance use by current and former female gang members should focus on the normative aspects of these behaviors.


Gangs Inverse propensity weighting Causal mediation Gender moderation Substance use Guilt 



This work was supported by Award Number P50DA010075-16 from the National Institute on Drug Abuse and by Award No. 2003-JN-FX-0003 (October 2003–June 2009) from the National Institute of Justice, Office of Justice Programs, U.S. Department of Justice. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute on Drug Abuse, the National Institutes of Health, or the U.S. Department of Justice.


  1. Babbie, E. R. (1973). Survey research methods. Belmont: Wadsworth.Google Scholar
  2. Barber, J. S., Murphy, S. A., & Verbitsky, N. (2004). Adjusting for time-varying confounding in survival analysis. Sociological Methodology, 34, 163–192.CrossRefGoogle Scholar
  3. Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173–1182.CrossRefGoogle Scholar
  4. Baumeister, R. F., Stillwell, A. M., & Heatherton, T. F. (1994). Guilt: an interpersonal approach. Psychological Bulletin, 115, 243–267.CrossRefGoogle Scholar
  5. Baumeister, R. F., Vohs, K. D., DeWall, C. N., & Zhang, L. (2007). How emotion shapes behavior: feedback, anticipation, and reflection, rather than direct causation. Personality and Social Psychology Review, 11, 167–203.CrossRefGoogle Scholar
  6. Benetti-McQuoid, J., & Bursik, K. (2005). Individual differences in experiences of and responses to guilt and shame: examining the lenses of gender and gender role. Sex Roles, 53, 133–142.CrossRefGoogle Scholar
  7. Bjerregaard, B. (2010). Gang membership and drug involvement: untangling the complex relationship. Crime and Delinquency, 56(1), 3–34.CrossRefGoogle Scholar
  8. Bjerregaard, B., & Smith, C. (1993). Gender differences in gang participation, delinquency, and substance use. Journal of Quantitative Criminology, 9, 329–355.CrossRefGoogle Scholar
  9. Bray, B. C., Almirall, D., Zimmerman, R. S., Lynam, D., & Murphy, S. A. (2006). Assessing the total effect of time-varying predictors in prevention research. Prevention Science, 7, 1–17.CrossRefGoogle Scholar
  10. Campbell, A. (1984). The girls in the gang. New York: Basil Blackwell.Google Scholar
  11. Chesney-Lind, M. (2013). How can we prevent girls from joining gangs? In T. R. Simon, N. M. Ritter, & R. R. Mahendra (Eds.), Changing course: Preventing gang membership. Washington, DC: U.S. Department of Justice and the U.S. Department of Health and Human Services.Google Scholar
  12. Coffman, D. L. (2011). Estimating causal effects in mediation analysis using propensity scores. Structural Equation Modeling, 18, 357–369.CrossRefGoogle Scholar
  13. Coffman, D. L., & Zhong, W. (2012). Assessing mediation using marginal structural models in the presence of confounding and moderation. Psychological Methods, 74, 642–664.CrossRefGoogle Scholar
  14. Coffman, D. L., Caldwell, L., & Smith, E. (2012). Introducing the at-risk average causal effect with application to HealthWise South Africa. Prevention Science, 13, 437–447.CrossRefGoogle Scholar
  15. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale: LEA.Google Scholar
  16. Cole, S. R., & Hernan, M. A. (2008). Constructing inverse probability weights for marginal structural models. American Journal of Epidemiology, 168, 656–664.CrossRefGoogle Scholar
  17. Daly, K. (1998). Gender, crime, and criminology. In M. Tonry (Ed.), The handbook of crime and justice (pp. 85–108). Oxford: Oxford University Press.Google Scholar
  18. Dearing, R. L., Stuewig, J., & Tangney, J. P. (2005). On the importance of distinguishing shame from guilt: relations to problematic alcohol and drug use. Addictive Behaviors, 30, 1392–1404.CrossRefGoogle Scholar
  19. Decker, S. H., Melde, C., & Pyrooz, D. C. (2013). What do we know about gangs and gang membership and where do we go from here? Justice Quarterly, 30, 369–402.CrossRefGoogle Scholar
  20. Elliott, D. S., Huizinga, D., & Ageton, S. S. (1985). Explaining delinquency and drug use. Beverly Hills: Sage.Google Scholar
  21. Else-Quest, N. M., Higgins, A., Allison, C., & Morton, L. C. (2012). Gender differences in self-conscious emotional experience: a meta-analysis. Psychological Bulletin, 138, 947–981.CrossRefGoogle Scholar
  22. Esbensen, F.-A. (2011). Outcome Evaluation of the Teens, Crime, and the Community/ Community Works (TCC/CW) training program in nine cities across four states, 2004–2005 [Computer file]. ICPSR25865-v1. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor]. doi: 10.3886/ICPSR25865.
  23. Esbensen, F.-A., & Deschenes, E. P. (1998). A multi-site examination of gang membership: does gender matter? Criminology, 36, 799–828.CrossRefGoogle Scholar
  24. Esbensen, F.-A., Deschenes, E. P., & Winfree, L. T., Jr. (1999). Differences between gang girls and gang boys: results from a multi-site survey. Youth & Society, 31, 27–53.CrossRefGoogle Scholar
  25. Esbensen, F.-A., Winfree, L. T., Jr., He, N., & Taylor, T. J. (2001). Youth gangs and definitional issues: when is a gang a gang, and why does it matter? Crime and Delinquency, 47, 105–130.CrossRefGoogle Scholar
  26. Esbensen, F.-A., Peterson, D., Freng, A., & Taylor, T. J. (2002). Initiation of drug use, drug sales, and violent offending among a sample of gang and non-gang youth. In C. R. Huff (Ed.), Gangs in America (3rd ed.). Thousand Oaks: Sage.Google Scholar
  27. Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27, 861–874.CrossRefGoogle Scholar
  28. Gordon, R. A., Lahey, B. B., Kawai, E., Loeber, R., Stouthamer-Loeber, M., & Farrington, D. P. (2004). Antisocial behavior and youth gang membership: Selection and socialization. Criminology, 42, 55–88.Google Scholar
  29. Haviland, A., Nagin, D. S., & Rosenbaum, P. R. (2007). Combining propensity score matching and group-based trajectory analysis in an observational study. Psychological Methods, 12, 247–267.CrossRefGoogle Scholar
  30. Holland, P. W. (1986). Statistics and causal inference. Journal of the American Statistical Association, 81, 945–970.CrossRefGoogle Scholar
  31. Hubbard, D. J., & Matthews, B. (2008). Reconciling the differences between the “gender-responsive” and the “what works” literatures to improve services for girls. Crime and Delinquency, 54(2), 225–258.CrossRefGoogle Scholar
  32. Huizinga, D., Esbensen, F.-A., & Weiher, A. W. (1991). Are there multiple routes to delinquency? Journal of Criminal Law and Criminology, 82, 83–118.CrossRefGoogle Scholar
  33. Imai, K., Keele, L., & Tingley, D. (2010). A general approach to causal mediation analysis. Psychological Methods, 15, 309–334.CrossRefGoogle Scholar
  34. Junger-Tas, J., Marshall, I. H., Enzmann, D., Killias, M., Steketee, M., & Gruszczynska, B. (Eds.). (2010). Juvenile delinquency in Europe and beyond. New York: Springer.Google Scholar
  35. Keenan, K., Loeber, R., & Green, S. (1999). Conduct disorder in girls: a review of the literature. Clinical Child and Family Psychology Review, 2(1), 3–19.CrossRefGoogle Scholar
  36. Kruttschnitt, C. (2013). Gender and crime. Annual Review of Sociology, 39, 291–308.CrossRefGoogle Scholar
  37. Lee, B., Lessler, J., & Stuart, E. A. (2009). Improving propensity score weighting using machine learning. Statistics in Medicine, 29, 337–346.Google Scholar
  38. Little, R. J. A., & Rubin, D. B. (2000). Causal effects in clinical and epidemiological studies via potential outcomes: concepts and analytical approaches. Annual Review of Public Health, 21, 121–145.CrossRefGoogle Scholar
  39. Lueptow, L., Mueller, S. A., Hammes, R. R., & Master, L. R. (1977). The impact of informed consent regulations on response rate and response bias. Social Methods Research, 6, 183–204.CrossRefGoogle Scholar
  40. Lumley, T. (2010). Survey: Analysis of complex survey samples [Computer software manual]. Available from (R package version 3.22-1).
  41. Matsuda, K. N., Melde, C., Taylor, T. J., Freng, A., & Esbensen, F.-A. (2013). Gang membership and adherence to the “code of the street”. Justice Quarterly, 30, 440–468.CrossRefGoogle Scholar
  42. McCaffrey, D. F., Ridgeway, G., & Morral, A. R. (2004). Propensity score estimation with boosted regression for evaluating causal effects in observational studies. Psychological Methods, 9, 403–425.CrossRefGoogle Scholar
  43. Mears, D. P., Ploeger, M., & Warr, M. (1998). Explaining the gender gap in delinquency: peer influence and moral evaluations of behavior. Journal of Research in Crime and Delinquency, 35, 251–266.CrossRefGoogle Scholar
  44. Melde, C., & Esbensen, F.-A. (2011). Gang membership as a turning point in the life course. Criminology, 49, 513–552.CrossRefGoogle Scholar
  45. Melde, C., & Esbensen, F.-A. (2014). The relative impact of gang status transitions: identifying the mechanisms of change in delinquency. Journal of Research in Crime and Delinquency 51, 349–376. doi: 10.1177/0022427813507059.
  46. Miller, J. (2001). One of the guys: Girls, gangs, and gender. New York: Oxford University Press.Google Scholar
  47. Papachristos, A. V. (2009). Murder by structure: dominance relations and the social structure of gang homicide. American Journal of Sociology, 115(1), 74–128.CrossRefGoogle Scholar
  48. Petersen, R. D., & Howell, J. C. (2013). Program approaches for girls in gangs: female specific or gender neutral? Criminal Justice Review, 38(4), 491–509.CrossRefGoogle Scholar
  49. Peterson, D. (2009). Girls in gangs and implications for gender-specific programming. Paper presented at the 8th Annual Youth Violence Prevention Conference, St. Louis.Google Scholar
  50. Peterson, D., & Carson, D. C. (2012). The sex composition of groups and youths’ delinquency: A comparison of gang and non-gang peer groups. In F.-A. Esbensen & C. Maxson (Eds.), Youth gangs in international perspective: tales from the eurogang program of research (pp. 189–210). New York: Springer.CrossRefGoogle Scholar
  51. Peterson, D., Miller, J., & Esbensen, F.-A. (2001). The impact of sex composition on gangs and gang members delinquency. Criminology, 39, 411–440.CrossRefGoogle Scholar
  52. Peterson, D., & Panfil, V. R. (2014). Street gangs: The gendered experiences of female and male gang members. In R. Gartner ∓ B. McCarthy (Eds.), Gender, Sex, and Crime (pp. 468–489). New York: Oxford.Google Scholar
  53. Quiles, Z. N., Kinnunen, T., & Bybee, J. (2002). Aspects of guilt and self-reported substance use in adolescence. Journal of Drug Education, 32, 343–362.CrossRefGoogle Scholar
  54. Ridgeway, G. (2006). Assessing the effect of race bias in post-traffic stop outcomes using propensity scores. Journal of Quantitative Criminology, 22, 1–29.CrossRefGoogle Scholar
  55. Ridgeway, G., McCaffrey, D. & Morral, A. (2006). Twang: Toolkit for weighting and analysis of nonequivalent groups. R package version 1.0-1.Google Scholar
  56. Robins, J. M., & Greenland, S. (1992). Identifiability and exchangeability for direct and indirect effects. Epidemiology, 3, 143–155.CrossRefGoogle Scholar
  57. Robins, J. M., Hernan, M., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11, 550–560.CrossRefGoogle Scholar
  58. Rosenbaum, P. R. (1984). The consequences of adjustment for a concomitant variable that has been affected by the treatment. Journal of the Royal Statistical Society, Series A (General), 147, 656–666.Google Scholar
  59. Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70, 41–55.CrossRefGoogle Scholar
  60. Rosenbaum, P. R., & Rubin, D. B. (1985). Constructing a control group using multivariate matched sampling methods that incorporate the propensity score. American Statistician, 39, 33–38.Google Scholar
  61. Rubin, D. B. (1974). Estimating causal effects of treatments in randomized and nonrandomized studies. Journal of Educational Psychology, 66, 688–701.CrossRefGoogle Scholar
  62. Rubin, D. B. (1986). Statistics and causal inference: comment: which ifs have causal answers? Journal of the American Statistical Association, 81, 961–962.Google Scholar
  63. Rubin, D. B. (2005). Causal inference using potential outcomes: design, modeling, decisions. Journal of the American Statistical Association, 100, 322–331.CrossRefGoogle Scholar
  64. Schafer, J. L., & Kang, J. (2008). Average causal effects from non-randomized studies: a practical guide and simulated example. Psychological Methods, 13, 279–313.CrossRefGoogle Scholar
  65. Setoguchi, S., Schneeweiss, S., Brookhart, M. A., Glynn, R. J., & Cook, E. F. (2008). Evaluating uses of data mining techniques in propensity score estimation: a simulation study. Pharmacoepidemiology and Drug Safety, 17(6), 546–555.CrossRefGoogle Scholar
  66. Sewell, W. H., & Hauser, R. M. (1975). Education, occupation and earnings: Achievement in the early career. New York: Academic Press.Google Scholar
  67. Shadish, W. R. (2013). Propensity score analysis: promise, reality, and irrational exuberance. Journal of Experimental Criminology, 9, 129–144.CrossRefGoogle Scholar
  68. Stapley, J. C., & Haviland, J. M. (1989). Beyond depression: gender differences in normal adolescents’ emotional experiences. Sex Roles, 20, 295–308.CrossRefGoogle Scholar
  69. Steffensmeier, D., & Allen, E. (1996). Gender and crime: toward a gendered theory of female offending. Annual Review of Sociology, 22, 459–487.CrossRefGoogle Scholar
  70. Stuewig, J., & McCloskey, L. A. (2005). The relation of child maltreatment to shame and guilt among adolescents: psychological routes to depression and delinquency. Child Maltreatment, 10, 324–336.CrossRefGoogle Scholar
  71. Stuewig, J., & Tangney, J. P. (2007). Shame and guilt in antisocial and risky behaviors. In J. L. Tracy, R. W. Robins, & J. P. Tangney (Eds.), The self-conscious emotions (pp. 371–388). New York: Guilford.Google Scholar
  72. Svensson, R. (2004). Shame as a consequence of the parent–child relationship: a study of gender differences in juvenile delinquency. European Journal of Criminology, 1, 477–504.CrossRefGoogle Scholar
  73. Svensson, R., Weerman, F. M., Lieven, J. R., Pauwels, G., Bruinsma, J. N., & Bernasco, W. (2013). Moral emotions and offending: do feelings of anticipated shame and guilt mediate the effect of socialization on offending. European Journal of Criminology, 10, 22–39.CrossRefGoogle Scholar
  74. Tape, T. (no date). Interpreting diagnostic tests (vol. 2012). Lincoln: University of Nebraska Medical Center. Retrieved December 1, 2013 from
  75. Thornberry, T. P., Krohn, M. D., Lizotte, A. J., Smith, C. A., & Tobin, K. (2003). Gangs and delinquency in developmental perspective. New York: Cambridge University Press.Google Scholar
  76. Tibbetts, S. (2003). Self-conscious emotions and criminal offending. Psychological Reports, 93, 101–126.CrossRefGoogle Scholar
  77. Tracy, J. L., & Robins, R. W. (2007). The self in self-conscious emotions: A cognitive appraisal approach. In J. L. Tracy, R. W. Robins, & J. P. Tangney (Eds.), The self-conscious emotions (pp. 3–20). Guilford: New York.Google Scholar
  78. VanderWeele, T. J. (2009). Marginal structural models for the estimation of direct and indirect effects. Epidemiology, 20, 18–26.CrossRefGoogle Scholar
  79. VanderWeele, T. J., & Vansteelandt, S. (2009). Conceptual issues concerning mediation, interventions, and composition. Statistics and Its Interface, 2, 457–468.CrossRefGoogle Scholar
  80. West, S. G., Biesanz, J. C., & Pitts, S. C. (2000). Causal inference and generalization in field settings: Experimental and quasi-experimental designs. In H. T. J. Reis & C. Judd (Eds.), Handbook of research methods in social and personality psychology (pp. 40–84). New York: Cambridge University Press.Google Scholar
  81. Wikstrom, P.-O. H. (2006). Individuals, settings, and acts of crime: Situational mechanisms and the explanation of crime. In P.-O. H. Wikstrom & R. J. Sampson (Eds.), The explanation of crime: Context, mechanisms, and development. Cambridge: Cambridge University Press.CrossRefGoogle Scholar
  82. Wikstrom, P.-O. H. (2010). Explaining crime as moral action. In S. Hitlin & S. Vaisey (Eds.), Handbook of the sociology of morality. New York: Springer.Google Scholar
  83. Wilcox, P., May, D. C., & Roberts, S. D. (2006). Student weapon possession and the “fear and victimization hypothesis”: unraveling the temporal order. Justice Quarterly, 23, 502–529.CrossRefGoogle Scholar
  84. Wimer, C., Sampson, R. J., & Laub, J. H. (2008). Estimating time-varying causes and outcomes with application to incarceration and crime. In P. Cohen (Ed.), Applied data analytic techniques for turning points research (pp. 37–59). New York: Routledge.Google Scholar
  85. Winship, C., & Morgan, S. L. (1999). The estimation of causal effects from observational data. Annual Review of Sociology, 25, 659–706.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Donna L. Coffman
    • 1
  • Chris Melde
    • 2
  • Finn-Aage Esbensen
    • 3
  1. 1.The Pennsylvania State UniversityState CollegeUSA
  2. 2.Michigan State UniversityEast LansingUSA
  3. 3.University of Missouri-St. LouisSt LouisUSA

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