The problems posed by persons with mental illness involved with the criminal justice system are vexing ones that have received attention at the local, state and national levels. The conceptual model currently guiding research and social action around these problems is shaped by the "criminalization" perspective and the associated belief that reconnecting individuals with mental health services will by itself reduce risk for arrest. This paper argues that such efforts are necessary but possibly not sufficient to achieve that reduction. Arguing for the need to develop a services research framework that identifies a broader range of risk factors for arrest, we describe three potentially useful criminological frameworks-the "life course," "local life circumstances" and "routine activities" perspectives. Their utility as platforms for research in a population of persons with mental illness is discussed and suggestions are provided with regard to how services research guided by these perspectives might inform the development of community-based services aimed at reducing risk of arrest.

This paper offers a criminologically-informed framework to guide research on the relationship between mental disorder and violence. Criminological theories examined include social learning, social stress, social control, rational choice, and social disorganization. In addition, the “criminal careers” and “local life circumstance” methodologies are reviewed. It is argued that adopting a criminologically-informed framework that takes into account within-person changes over time will contribute greatly to our understanding of the factors that affect violence among people with mental disorder living in the community, and enhance the capacity of research to support effective evidenced-based case management programs aimed at reducing violence.

OBJECTIVE: We examined the association between mental disorder and violent victimization in a general population sample. METHODS: We performed a multivariate analysis of violent victimization in a 12-month period on a total birth cohort with follow-up data that assessed, during their 21st year, males and females born in Dunedin, New Zealand, in the early 1970s. RESULTS: Compared with people with no mental disorder, (1) people with anxiety disorders experienced more sexual assaults, (2) people with schizophreniform disorders experienced more threatened and completed physical assaults, (3) people with alcohol dependence disorders experienced more completed physical assaults, and (4) people with marijuana dependence disorders experienced more attempted physical assaults. These results held after control for psychiatric comorbidity, demographic characteristics, and the study participants' own violent behavior. CONCLUSION: Mentally disordered young adults tend to experience more violent victimization in the community than those without a mental disorder.

Research on the relationship between metal disorder and violence has focused largely on the effects of clinical characteristics, such as treatment adherence and psychotic symptoms, with little attention given to the potentially important role of stressful life events and impaired social support. Yet, stressful life events and impaired social support have been found to be significantly associated with the onset and course of mental disorder and with the occurrence of violence. This raises the question: Do stressful life events and impaired social support contribute to the association between mental disorder and violence? The current study addresses this question using general population data from the Durham site of the National institute of Mental Health's Epidemiological Catchment Area Surveys (n=3,437). Results indicate then when stressful life events and impaired social support were controlled, the association between mental disorder and violence was substantially reduced. Implications for future research on the relationship between mental disorder and violence are discussed.

Actuarial models for violence risk assessment have proliferated in recent years. In this article, we describe an approach that integrates the predictions of many actuarial risk-assessment models, each of which may capture a different but important facet of the interactive relationship between the measured risk factors and violence. Using this multiple-models approach, we ultimately combined the results of five prediction models generated by the Iterative Classification Tree (ICT) methodology developed in the MacArthur Violence Risk Assessment Study. This combination of models produced results not only superior to those of any of its constituent models, but superior to any other actuarial violence risk-assessment procedure reported in the literature to date.

Drawing on Agnew's (1992) general strain theory, this study seeks to determine whether depressed mood and anger mediate the effects of family conflict on delinquency. Drawing on earlier research, survey data were gathered from 7,758 ninth and tenth graders, aged 14 to 16, in Iceland. Structural equation modeling showed that exposure to arguments and fights at home are positively related to both depressed mood and anger. A positive association emerged between anger and delinquent behavior, whereas depressed mood had no effect on delinquency.

Why do youth in structurally disadvantaged neighborhoods experience lower levels of informal social control? To answer this question, we examined multilevel data from the Project on Human Development in Chicago Neighborhoods. Using hierarchical regression, we found that (1) neighborhood attachment & satisfaction with police contributed significantly to neighborhood levels of informal social control; (2) neighborhood attachment & satisfaction with police mediated a substantial portion of the association between informal social control & neighborhood levels of concentrated disadvantage & immigrant concentration.

This study provides an elaborated view of the types of high-risk patients identified by the multiple Iterative Classification Tree (ICT; Banks et al., in press). In particular, because clinicians must assess and treat patients before they are involved in violence, the investigation focuses on identifying subtypes of high-risk patients rather than violent patients in order to determine whether there are meaningful subtypes of patients at high risk for violence. Data were obtained from interviews with 165 patients identified as at risk by the multiple ICT in the MacArthur Risk Assessment Study (Monahan et al., 2001). Overall, these high-risk patients are best classified into 1 of 3 groups: (a) alpha patients (48%), who generally are depressed and abuse drugs heavily, but manifest multiple core traits of psychopathy and have extensive histories or arrest, including those for property crimes; (b) beta patients (38%), who typically are dysphoric, dependent on alcohol and other drugs, and sensitive to personal problems; and (c) delta patients (14%), who typically are delusional, have less drug and alcohol involvement, often experience command hallucinations, and have histories of intensive treatment. These 3 groups are largely consistent with hypothesized subtypes. Moreover, they were identified by applying multiple methods of cluster analyses, integrating the most stable results to develop a consensus cluster solution, and validating that solution on external variables. In short, the groups make theoretical sense, have some sound empirical grounding, and have implications for future research and treatment development efforts. For example, the demonstration that these 3 groups appear to exist provides direction for the next set of advances in risk management and intervention with particularly high-risk patients. Specifically, it provides a framework for systematically investigating the differential effects of particular types of interventions with these patients. Risk assessment and management requires this richer, more differentiated view of high-risk patients to achieve its potential.