Key Risk Factors for Relapse and Rearrest Among Substance Use Treatment Patients Involved in the Criminal Justice System

Substance use treatment programs for criminal justice populations have great potential for crime reduction, if they can effectively manage patients’ risk for relapse and rearrest. The current study used data drawn from the Comprehensive Assessment and Treatment Outcome Research (CATOR) system, a national registry of substance use treatment programs, which collected patient outcome data at 6- and 12-month intervals following discharge from treatment. The primary objective was to examine sets of factors that may compromise relapse and rearrest outcomes among patients who were court mandated to participate in treatment. Findings demonstrated that patients’ clinical severity of substance use was associated with relapse, which also significantly increased the probability of post-treatment arrest. Adolescent risk behaviors represented another set of risk factors, particularly among patients who experienced the most severe pattern of relapse and arrest outcomes. Additionally, demographic risk factors, including age, marital status (i.e., single or unmarried relative to married), employment (i.e., being unemployed compared to employed), and lower educational attainment were consistently linked to higher probabilities of relapse and rearrest. Treatment programs for criminal justice populations should consider incorporating appropriate clinical risk assessment measures, behavioral risk assessments, and appropriate employment interventions into standard treatment programming in an effort to improve outcomes.     

Legal Consciousness and Dispute Resolution: Different Disputing Behavior at Two Similar Taxicab Companies

This article examines how workers perceive the laws and rules that regulate their workplaces and how these perceptions differ depending on whether one works in an organization with a high level of worker-manager cooperation versus one with a more conventional hierarchy. Using two cab companies as examples, this article explores how these divergent organizational structures generate different grievance cultures that in turn encourage alternate understanding of availavle choices and appropriate means for resolving such disputes.
This work expands the current sociolegal literature on legal consciousness by focusing on formal and informal workplace grievance resolution and perceptions of workplace conflict. In exploring the critical decision making regarding grievance resolution, this article begins an important discussion about workplace empowerment and legal consciousness. This study uses qualitative methods to examine 33 open-ended interviews. The use of qualitative methods permits a vibrant dialog that illustrates the legal consciousness of the subjects, The subjects'own words reveal their comprehension of rules, regulations, and procedures as well as their individual relationships with the grievance-resolution options in their workplaces.     

Growth curves of deviant behavior in early adolescence: A multilevel analysis

Multilevel growth curve models provide a means of analyzing individual differences in the growth of deviance, allow a number of theories to be integrated in a single model, and can help to unify research on deviant/delinquent/criminal careers at different stages of the life cycle. Building on the distinction between population heterogeneity and state dependence as alternative explanations of persistent individual differences in deviance (Heckman, 1981; Nagin and Paternoster, 1991), we show that models with two levels can be used to represent and analyze a variety of criminological theories. The first level (level 1) uses repeated measurements on individuals to estimate individual-level growth curves. The second level treats the level 1 growth curve parameters (e.g., slope, intercept) as outcome variables and uses time-invariant factors to explain variation in these parameters across individuals. We illustrate this approach by estimating a model of growth in deviance drawn from Gottfredson and Hirschi's deviant propensity theory. An innovative feature is the assumption that adolescents' expected growth curves of deviance follow a classical Pearl-Verhulst logistic growth model (Pearl, 1930). The results suggest that five risk factors—parental psychiatric problems, lack of parental support, living arrangements with zero or one parent in residence, low family income, and male gender—have strongly positive effects on deviant propensity. For example, adolescents with no supportive parents, and no other risk factors, have expected asymptotic levels of deviance (peak levels attained at about age 18) that are about twice as high as those of adolescents with no risk factors. Yet more than two-thirds of the individual-level variability in growth curves is unexplained by the five risk factors. This unobserved heterogeneity would remain hidden in analyses using conventional structural equations models and the same explanatory variables.     

Predictors of re-offending in German substance-abusers in legal detention: a prospective population-based cohort study

This study aimed to evaluate whether the elapsed time after release to first re-offense is longer for those who complete coerced forensic addiction treatment than for those who fail to complete the treatment. It is also aimed to identify predictors of re-offending for both those who complete such treatments as compared with those who do not. Two hundred and sixty-one patients discharged from five German forensic addiction clinics were investigated on 65 anamnestic, socio-demographic, and therapeutic process variables. One hundred and fifty-one patients were prematurely discharged and returned to prison (group A; time at risk [TAR] = 58.7 months), 110 finished treatment successfully (group B; TAR = 44.2 months). Federal Criminal Register data were used for follow-up. Univariate survival analyses and multivariate stepwise Cox-regression models were computed. Twelve predictors in group A revealed a four-factor model: age at admission to treatment, duration of concurrent prison sentence, number of entries in the criminal register, and attendance at prior substitution programs. The model for group B covered five out of eight predictors: regular working activities before first diagnosis of mental illness, type of main offense, (secondary) traffic offenses, outpatient rehabilitation treatments, and escapes during treatment. Successful completers of forensic addiction treatment are slower to re-offend than non-completers.