Drawing from general strain and self-control perspectives, the role of maladaptive coping (i.e., substance use) in the causal pathway between victimization and offending is explored. Specifically, the present study investigates: (1) the extent to which self-control influences substance use in response to victimization, and (2) whether victims with low self-control and who engage in substance use are more likely to commit violent offenses in the future.
Three waves of panel data from the Gang Resistance Education and Training program are used (N = 1,463), and negative binomial regression models are estimated to explore the interactive effects of low self-control, victimization, and substance use on violent offending.
Victims with low self-control are more likely to engage in substance use post-victimization, and low self-control and substance use are found to exert significant conditional effects on the pathway between victimization and offending. These results remained robust even after controlling for prior violent offending, peer influences, prior substance use, and other forms of offending.
The causal pathway between victimization and offending can be explained by drawing upon key concepts drawn from self-control (i.e., how self-control shapes coping responses) and general strain (i.e., how those responses influence offending above and beyond self-control) theories, indicating that these two perspectives can and should be integrated more explicitly to explain the dynamics of victimization and offending.
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For a more detailed description of the GREAT program’s methodology and data collection procedures, see Esbensen et al. (2001).
Sample demographic characteristics of age, gender, and race are distributed similarly across all six cities. On average, however, respondents in Portland were slightly younger, and Philadelphia contained a higher proportion of black respondents relative to other cities.
Wave one of the data was excluded to maintain consistency across measures over time. Specifically, wave one of the GREAT data contains items which ask respondents to report incidents of substance use and offending during the last 12 months, whereas all subsequent waves ask respondents to report during the last 6 months. For the purposes of controlling for prior levels of these behaviors, it was imperative that measurement remained consistent over time.
Time one data were used for the key measures of violent victimization and low self-control, while time two data included substance use, and time three data included violent offending. This temporal ordering was essential to assess the effects of victimization on substance use and violence, since reported incidents of victimization preceded the reports of both substance use and violent offending. While the one-year time lag between each of the waves is not unusual for longitudinal tests of general strain theory (e.g., Hoffman and Miller 1998; Mazerolle 1998; Mazerolle and Maahs 2000; Paternoster and Mazerolle 1994), it should be noted that the theory is often interpreted to imply more immediate, short-term effects of strain (see also the discussion in Hay and Evans 2006). Nevertheless, a central theme in the victimization literature is that victimization can produce negative consequences that persist for many years (e.g., Macmillan 2001; Macmillan and Hagan 2004; Miller et al. 1996). Violent victimization is a form of strain most likely to have effects that persist over the three-year period considered in the present study, and thus we deem our use of these data appropriate.
Multiple imputation with ten iterations was conducted to compensate for missing data using the command for multiple imputation by chained equations available in Stata 12.0 (Allison 2002; Carlin et al. 2008; McKnight et al. 2007; Royston 2004, 2005). This involved a procedure in which 10 imputed datasets were generated and pooled parameter estimates were calculated to account for possible underestimation of standard errors that may have been observed in single imputation procedures (Acock 2005; Schafer 1997). It is important to note that previous studies have reported that individuals lost after wave one in the GREAT data demonstrate higher levels of victimization and delinquency than those who participated in later waves (Agnew et al. 2011; Schreck et al. 2006), and that item nonresponse rates in the GREAT dataset have been shown to be higher among those with lower levels of self-control (Watkins and Melde 2007). As a result, the findings reported below may represent conservative estimates since variation in the “tails” of the distributions of key variables of interest—which may otherwise serve to inflate the relationships of theoretical interest (particularly the relationships surrounding self-control, substance use, and violence)—has been somewhat truncated. In using the imputed data, however, the possibility of making such an inferential error is minimized considerably over simple listwise deletion methods for missing values.
We recognize, given the relatively young age of the sample, that substance use is only one form of maladaptive behavioral coping and that other—perhaps less severe forms (e.g., expressing anger verbally)—would be more common among these subjects. Nevertheless, over one-third of respondents reported drug and alcohol use and studies have shown that youths who engage in such behavior are at a higher risk for delinquency (Pratt et al. 2010a)—a finding wholly consistent with Agnew’s (2006) discussion of substance abuse as a problematic behavioral response to strain.
Our construct of victimization and inclusion of physical assault (i.e., “hitting”) in combination with other violent incidents of robbery and assault with a weapon is consistent with previous research using this data (e.g., Agnew et al. 2011; Esbensen and Osgood 1999; Esbensen et al. 2001; Schreck et al. 2006) and equivalent to the one previously used by Jennings et al. (2010). Although we recognize that physical assault may be a less serious and more common form of victimization than other forms of violence, we are confident in our operationalization of victimization given the high factor loadings and eigenvalues of the three items used to construct our measure, demonstrated by principal components analysis.
As some may argue, a potential drawback of the GREAT data is that it relies on respondents’ knowledge of their friends’ behaviors. For instance, some researchers have speculated that respondents’ peer delinquency measures may be biased to a certain extent by the tendency of individuals to project their own tendencies onto their friends (e.g., Haynie 2001; Gottfredson and Hirschi 1987; Schreck et al. 2004), a limitation also noted by Schreck et al. (2006). Regardless of these potential shortcomings, respondent-generated peer measures remain the standard for investigating peer delinquency and violence in criminological research (e.g., Lauritsen et al. 1992; Schreck et al. 2002, 2006), and these items influence the likelihood of substance use and violence in theoretically expected ways. To examine in greater detail the impact of peer groups on substance use and violence—a focus well beyond that of the present examination—researchers may wish to use network data from other sources such as the National Longitudinal Study of Adolescent Health (Add Health).
The natural logarithm of substance use (+1) was taken before it was centered and interacted with victimization to induce a more uniform distribution and guard against the potentially harmful effects of outliers (skewness of substance use was reduced from 3.47 to 1.26).
Clustered robust standard errors are intended to make the standard errors robust to both serial correlation (due to the non-independence of observations within clusters) and to heteroskedasticity (due to differing variance estimates emerging from the observations between clusters) without having to make any assumptions about the functional form of either (Rogers 1993; Wooldridge 2002). Targeting a larger unit of analysis for clustering (e.g., a city) where serial correlation would disappear and/or heteroskedasticity would pass undetected would fail to address the very problems that clustered robust standard errors are assumed to fix.
Although in the present study our interests lie in exploring how low self-control shapes problematic responses to victimization, we recognize that self-control may also influence the likelihood of victimization. We found that low self-control is a significant predictor of violent victimization among respondents in the sample, net of demographic controls (b = .06, p < .001; model not shown here)—a finding consistent with the larger body of self-control and victimization research (e.g., Higgins et al. 2009; Piquero et al. 2005; Schreck 1999; Schreck et al. 2002; Stewart et al. 2004).
As Agnew (1992:71) argued, those high in self-esteem and self-efficacy may be more resistant to stress and more likely to feel that their strain can be alleviated by “behavioral coping of a non-delinquent nature.”
A series of diagnostic tests similar to those described previously were first conducted to ensure that the models estimated for sensitivity analyses were not biased due to collinearity. Condition indices were below 20, and VIF scores did not exceed 2.40.
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The authors are grateful to Michael D. Reisig and Robert J. Fornango for their guidance and comments on earlier drafts.
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Turanovic, J.J., Pratt, T.C. The Consequences of Maladaptive Coping: Integrating General Strain and Self-Control Theories to Specify a Causal Pathway Between Victimization and Offending. J Quant Criminol 29, 321–345 (2013). https://doi.org/10.1007/s10940-012-9180-z