1. Different Pathways To Offending and Violence: An Examination Of The Differences Among Youths With Varying Histories Of Contact With The Juvenile Justice System ¹ Mitchell Sartin, ²Daniel L. Ullman, and ¹David J. Hansen, ¹University of Nebraska-Lincoln and ²Adolescent and Family Services Unit - Lincoln Regional Center Introduction Highly publicized occurrences of violence and increased media attention to juvenile crime and delinquency have contributed to an upsurge in research and funding to address what is seen by many as a growing problem. Juvenile problem behaviors result in tremendous costs to society in terms of capital and resources. In fact, a minority of juveniles commit a disproportionate percentage of offenses. Research on conduct problems and subsequent delinquency in adolescence has tended to implicate several factors. For instance, parental substance abuse, family conflict, child abuse, and various socio- cognitive variables have been found to be related to the development of conduct problems. It is believed that an understanding of how these variables interact in different pathways across differing groups of youths could permit enhanced prevention and intervention of conduct problems and subsequent delinquency. The current study is an attempt to differentiate between youthful offenders who experience minimal contact with the juvenile justice system and those who experience repeated and prolonged contact with the juvenile justice system. Research has shown that a small percentage of youth accounts for a large percentage of the crimes and costs. In addition, some delinquency in adolescence has even been hypothesized by some to be normative. The current study is an effort to identify the “non-normative” delinquents, so that prevention and intervention programs could be more targeted. Prevention and intervention programs are costly and largely ineffective. Perhaps part of the problem lies in trying to utilize one approach for vastly differing groups. The identification of different pathways would allow for better-targeted treatments. More thorough and effective interventions could be implemented if those who are at high risk to be continually involved with the juvenile justice system could be identified. Moreover, given the tendency for the same youths to engage in multiple problem behaviors (e.g., legal offenses, violence, substance abuse, and other risky behaviors), prevention and early intervention could provide large savings in terms of capital and resources. Methods Participants Participants in the study are 726 youths (57% male and 43% female), between ages 11 and 18, who have undergone evaluation at the Adolescent and Family Services Unit of the Lincoln Regional Center after being referred by the juvenile court. Demographic information for this sample is presented in Table 1. Measures The youths completed the Millon Adolescent Clinical Inventory (MACI), a Wechsler intelligence scale (i.e., Wechsler Adult Intelligence Scale-III (WAIS-III), Wechsler Intelligence Scale for Children-III (WISC-III), or Wechsler Abbreviated Scale of Intelligence (WASI)), and the Wechsler Individual Achievement Test (WIAT). Procedures The youths were given a clinical interview by a licensed clinical psychologist and a chemical dependency evaluation by an alcohol and drug counselor. Several variables which have previously been found to be related to conduct problems were coded from the file and the clinical interview by individuals working at the Adolescent and Family Services unit of the Lincoln Regional Center: parental legal history, parental substance abuse, age of first legal charge, and abuse history. These variables were coded based on the files and substantiation by police, court, Child Protective Services (CPS), or other institutional records. For this study a few additional variables were coded from the files: number of offenses (based on number of non- status offenses) and violence rating. A reliability check by an independent rater was performed for the coding of these two variables on 111 cases (~ 15% of the cases). The correlations between the two raters for number of offenses and violence rating were.984 (p <.01) and.979 (p <.01), respectively. Results In an attempt to find subgroups of juvenile delinquents, particularly groups with high numbers of offenses and a history of violence, cluster analysis was utilized. Because preliminary results (univariate and multivariate) and previous literature suggest significant differences across gender, males and females were clustered separately. For both the males and females, the variables used in the cluster analysis were Z-scores of violence rating and a function of number of offenses. That is, instead of inserting merely number of offenses, a separate variable (the square root of the dividend resulting from dividing number of offenses by age at time of admission) was utilized. This coding was utilized for two reasons. First, in order to understand the implications of an individual’s number of offenses it is essential to factor in the individuals age. Second, the square root was utilized because the difference between no offenses and 1 offense is more important than the difference between 22 offenses and 23 offenses. The profiles from the resulting clusters are contained Figure 1 (males) and Figure 2 (females). Several variables with significant differences across clusters are also presented in Figure 1 and Figure 2. It appears that the very high offenses, high violence groups across gender are the most easily differentiated. For instance, in comparison to other clusters of the same gender, both of the very high offenses, low violence clusters have the lowest age of first legal charge and lowest written achievement scores. Conclusions The results of the cluster analysis give support to the idea that there are subgroups of delinquents who differ in the tendency to engage in delinquent behavior. There appear to be groups of delinquents who have infrequent contact with the legal system, groups with moderate levels of contact with the legal system, and groups who have frequent contact with the legal system due to a pervasive tendency to engage in delinquent behavior. Further, based on the results, the subgroups of delinquents have differing histories, abilities, and problems (e.g., age of first legal charge, achievement test scores, prevalence of conduct disorder). If subgroups can be reliably determined, the implication is that interventions can be more targeted. That is, it would seem worthwhile to target more potent interventions for those who have had frequent contact with the legal system or those who are likely to have frequent contact with the legal system. Future research should focus on ways to increase the reliability with which subgroups can be determined. Moreover, it will be important to understand how the pathways to delinquency differ for the various subgroups. Table 1. Demographics of the Study Participants MalesFemales MeanS.D.MeanS.D. Number of Offenses6.104.603.392.72 Violence Rating.75.81.55.74 Age of 1 st Legal12..952.6613.611.96 Non-alcohol Substance Abuse.49.50.49.50 Conduct Disorder.67.47.36.48 Writing83.4914.7388.3714.12 Reading87.1315.3088.5714.73 Parent Legal History.43.66.51.67 Special Education1.32.471.22.41 Table 2. Descriptive Statistics for Variables Included in the Cluster Profile