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Schizophr Bull. 2011 Sep;37(5):899-912. doi: 10.1093/schbul/sbr093.

Structured assessment of violence risk in schizophrenia and other psychiatric disorders: a systematic review of the validity, reliability, and item content of 10 available instruments.

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Department of Psychiatry, University of Oxford, Warneford Hospital, OX3 7JX, UK.



To undertake a systematic review on structured violence risk assessment tools in individuals with schizophrenia.


A systematic search was conducted from 1990 to 2011 to identify violence risk assessment tools and studies examining their predictive validity. Item content of the identified instruments was analyzed, and areas under the curve (AUC) from the studies were extracted. In addition, an 11-item checklist was developed to assess the utility and psychometric properties of these tools.


Ten risk assessment tools designed to predict community violence in psychiatric patients were identified, but only 2 studies reporting predictive validity estimates in patients with schizophrenia were found (median AUC = 0.69; interquartile range = 0.60-0.77). When inclusion criteria was broadened to include studies measuring accuracy for any diagnostic group, mixed evidence of predictive validity was found, with median AUCs ranging from 0.62 to 0.85 depending on the population. Item content included mostly clinical, sociodemographic, and criminal history factors. As only 1 tool included a neurobiological item, a structured review of brain-based and cognitive risk factors for violence was included, and 3 clusters (neurocognitive ability, neurocognitive awareness, and attitudinal cognition) were identified.


While a number of violence risk assessment tools exist that can be used to predict the likelihood of community violence in psychiatric patients, there is currently little direct evidence for their utility in individuals with schizophrenia. In addition, there is large variation in item content between instruments, and further research is necessary to determine whether the inclusion of alternative factors could improve risk assessment.

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