Abstract
Prior studies have documented linkages between mental disorder and both offending and victimization. However, few studies have examined the violent offending–violent victimization overlap among mentally disordered individuals and none have examined the factors that are jointly related to their covariation. Here, we assess this overlap during the first ten weeks following hospital discharge among a large sample of psychiatric patients from three large cities. Findings indicate that: (1) violent offending and violent victimization show substantial covariation; (2) although each of the two outcomes were predicted by a few unique risk factors, several risk factors were similarly predictive of both outcomes; and (3) even after adjusting for demographic, clinical, and social risk factors, the correlation between violent offending and violent victimization remained robust. Implications for theory, research, and policy are highlighted.
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Notes
Several differences regarding Teasdale’s recent analysis and the current study should be noted. First, Teasdale only examined victimization as an outcome, while we examine the joint covariation between offending and victimization. Second, Teasdale used five waves of follow-up data with significant sample attrition, while we rely only on the first follow-up assessment largely because that is when the risk of offending and victimization are highest and attrition is lowest. Third, Teasdale’s study utilized a mixture of variables and employed hierarchical linear modeling while our study considers theoretically driven, domain-specific variables in a stepwise manner and employs the bivariate probit model, which is necessitated because of our interest in the joint covariation between offending and victimization. In short, while both studies use data from the MacArthur project, the two are quite different in many respects, but primarily because Teasdale focused on victimization only while we focus on both offending and victimization.
Unlike the other clinical measures included in this study, which were measured during the first 10 weeks following hospital discharge, the psychopathy scale was administered in the community typically during Follow-Up 1, and, to a lesser extent, Follow-Up 2 (e.g., Skeem, Mulvey, & Grisso, 2003; Skeem, Miller, Mulvey, Monahan, & Tiemann, 2005). This measurement strategy served two purposes. First, it enabled the research team to administer the PCL-SV during a follow-up interview at which the respondent’s clinical condition appeared relatively stable. Second, unlike other clinical symptoms, psychopathy is generally believed to be an enduring personality characteristic rather than a fluctuating clinical symptom, so that its exact time of measurement is less important than for other clinical symptoms.
In addition to the total BPRS symptom score, we also performed a supplemental analysis where we included the Hostility subscale score. Hostility is an important symptom to measure separately because of its links to violence and victimization. Including the hostility subscale along with the total symptom score enabled us to examine the effect of a broad range of symptoms on violence and victimization, net of hostility, while at the same time enabling us to pay special attention to the role that hostility plays in the victimization–offending overlap, net of other symptoms. Not surprisingly, the hostility subscale and the full BPRS are positively and highly correlated (r = .664). This strong correlation raises a potential concern regarding multicollinearity and our analyses point to this. For example, when we included both the hostility subscale and full BPRS in the same model, we found that the hostility subscale was not significantly related to either violent offending or violent victimization but that the full BPRS measure had a positive and significant effect on violent victimization but not violent offending. Of course, because the hostility subscale is included in the total BPRS scale, we needed to re-score the total score without the hostility items included because this introduces partially redundant variables (essentially variance from hostility twice) into the analysis. After performing this adjustment, we found that both the hostility subscale and the total BPRS score had a positive and significant effect on violent victimization, but neither significantly predicted violent offending. Finally, we also re-estimated all of the models with the hostility subscale in lieu of the full BPRS and were led to the same sets of findings generated with the full BPRS scale. That is, including the hostility subscale did not alter any of the findings presented in this study in terms of coefficient size, strength, and significance compared to use of the full BPRS scale, nor did inclusion of the hostility subscale result in any substantive alteration to the disturbance parameter. Thus, we opted to retain the results using the full BPRS subscale and these are presented in the text and tables.
We also estimated two separate probit equations, one for each of the two outcomes. A log-likelihood ratio test revealed that the bivariate probit model fit the data better than the two separate probit models. The LL for the offending model was −318.43, while the LL for the victimization model was −406.02. The sum of these LL’s was −724.45. The LL for the bivariate probit was −704.53. Twice the difference of these two LLs yields a chi-square estimate of 39.85, which is significant at p < .05.
When interpreting the magnitude of the significant effects reported in this study, it should be noted that bivariate probit coefficients are still probit coefficients. The usual interpretation of a probit coefficient is the following: (1) The “true” dependent variable is considered to be latent, i.e., y*; (2) y* is a standard normally distributed variable (M = 0, SD = 1); (3) if y* > 0 then the observed y = 1; if y* < 0 then the observed y = 0; and (4) the probit coefficient can therefore be interpreted as the expected amount of change in y* given a unit change in x. In the case of a statistically significant effect of b = 0.03, the interpretation would be for each increase in x there is an expected 0.03 units change in y*, keeping in mind that y* is standard normal with M = 0 and SD = 1.
An anonymous reviewer raised the interesting question about why might PCL-2 relate to both offending and victimization while simultaneously not accounting for much of the variance in the two outcomes. Here, we note several potential possibilities. First, the PCL-2 taps into a series of more general risk factors that have previously been found to be related to an increased risk for both offending and victimization (e.g., attitudinal and behavioral features of psychopathy such as poor behavioral controls, lacking goals, irresponsibility, and adolescent and/or adult antisocial behavior), and given the strong overlap between offenders/victims and offending/victimization noted in the literature this could be what is underlying the observed relationship between the PCL-2 and both violent offending and violent victimization. In short, many of the same items and characteristics (e.g., lack of goals, temper, risk-taking, impulsivity, and lack of remorse) found in the PCL-2 have also been theoretically and empirically linked to both offending and victimization within Gottfredson and Hirschi’s (1990) self-control perspective. Second, the lack of the PCL-2’s ability to explain much of the variance in the two outcomes could be because there are other variables that influence both offending and victimization. Much of the empirical literature in criminology fails to find a high amount of explained variance when predicting these two outcomes more generally (Weisburd & Piquero, 2008). This may be due, in part, to the observation that both offending and victimization are influenced by situational factors and individual/personality characteristics which, while related to the two outcomes, are not very strongly related to them and thus do not explain the lion’s share of the variance.
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Silver, E., Piquero, A.R., Jennings, W.G. et al. Assessing the Violent Offending and Violent Victimization Overlap Among Discharged Psychiatric Patients. Law Hum Behav 35, 49–59 (2011). https://doi.org/10.1007/s10979-009-9206-8
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DOI: https://doi.org/10.1007/s10979-009-9206-8