Substantial strides have been made in the field of violence risk assessment. Numerous robust risk factors have been identified and incorporated into structured violence risk assessment instruments. The concepts of violence prevention, management, and treatment have been infused into contemporary thinking on risk assessment. This conceptual development underscores the necessity of identifying, measuring, and monitoring changeable (dynamic) risk factors-the most promising targets for risk reduction efforts. However, empirical investigation of dynamic risk is virtually absent from the literature. In this article, the authors (a) differentiate risk status (interindividual risk level based largely on static risk factors) from risk state (intraindividual risk level determined largely by current status on dynamic risk factors), (b) analyze the relevance of contemporary risk assessment measures for capturing dynamic risk, and (c) distill potentially important dynamic risk factors from the literature in order to facilitate future research. Suggestions for theory development and research design are provided.

The potential association between psychosis and violence to others has long been debated. Past research findings are mixed and appear to depend on numerous potential moderators. As such, the authors conducted a quantitative review (meta-analysis) of research on the association between psychosis and violence. A total of 885 effect sizes (odds ratios) were calculated or estimated from 204 studies on the basis of 166 independent data sets. The central tendency (median) of the effect sizes indicated that psychosis was significantly associated with a 49%-68% increase in the odds of violence. However, there was substantial dispersion among effect sizes. Moderation analyses indicated that the dispersion was attributable in part to methodological factors, such as study design (e.g., community vs. institutional samples), definition and measurement of psychosis (e.g., diagnostic vs. symptom-level measurement, type of symptom), and comparison group (e.g., psychosis compared with externalizing vs. internalizing vs. no mental disorder). The authors discuss these findings in light of potential causal models of the association between psychosis and violence, the role of psychosis in violence risk assessment and management, and recommendations for future research.

This study evaluated the predictive validity of the HCR-20 (Historical, Clinical, and Risk Management) violence risk assessment scheme and the Psychopathy Checklist: Screening Version (PCL:SV). Files of 193 civilly committed patients were coded. Patients were followed up in the community for an average of 626 days. Receiver operating characteristic analyses with the HCR-20 yielded strong associations with violence (areas under curve [AUCs] = .76-.80). Persons scoring above the HCR-20 median were 6 to 13 times more likely to be violent than those scoring below the median. PCL:SV AUCs were more variable (.68-.79). Regression analyses revealed that the HCR-20 added incremental validity to the PCL:SV and that only HCR-20 subscales predicted violence. Implications for risk assessment research, and the clinical assessment and management of violence, are discussed.

Narrative reviews have raised several questions regarding the predictive validity of the Hare Psychopathy Checklist-Revised (PCL-R; R. D. Hare, 2003) and related scales in institutional settings. In this meta-analysis, the authors coded 273 effect sizes to investigate the association between the Hare scales and a hierarchy of increasingly specific forms of institutional misconduct. Effect sizes for Total, Factor 1, and Factor 2 scores were quite heterogeneous overall and weakest for physically violent misconduct (r-sub(w) = .17, .14, and .15, respectively). Moderator analyses suggested that physical violence effect sizes were smaller in U.S. prison samples (r-sub(w) = .11) than in non-U.S. prison samples (r-sub(w) = .23). Findings are discussed in terms of the utility of the Hare measures for decision-making in institutional and other contexts.

The rationale for this article was to outline and describe an emerging model of prevention-based violence risk assessment and management and to discuss attendant clinical and research implications. This model draws on structured professional judgment rather than on actuarial prediction or unstructured clinical prediction. Its purpose is to prevent violence through the assessment of relevant violence risk factors and the application of risk management and intervention strategies that flow directly from these factors. The authors discuss the nature of the clinical tasks that stem from the model as well as a four-step validation procedure required to evaluate it.