Clinical prediction of violence among inpatients with schizophrenia using the Chinese modified version of Violence Scale: A prospective cohort study

Abstract

Background: A standard measure to assess and predict violence is important for psychiatric services. No prospective study has examined the history of violence and heterogeneity of violence in predicting specific types of violence among inpatient with schizophrenia. Objectives: This study aimed to prospectively examine the accuracy of prediction of types of violence using the Chinese modified version of Violence Scale (VS-CM) among inpatients with schizophrenia based on their past history of violence and the real occurrence of violence during hospitalization. Design: A prospective cohort study design. Setting and participants: A total of 107 adult patients with schizophrenia spectrum disorders, consecutively admitted to an acute psychiatric ward of a university hospital in Taiwan, were recruited. Method: In addition to data about demographics and clinical illness, count records of the history of violence within one month prior to admission by interview and the actual occurrence of violence during the whole course of hospitalization by participant observation were collected using the VS-CM. Multivariate logistic analysis and area under the Receiver Operating Characteristic curve (AUC) analysis were applied to examine the predictive ability of the VS-CM. Results: A patient's history of violence assessed by the VS-CM predicted the actual occurrence of violence during hospitalization with the Odds Ratio of 17.5 (. p=. 0.001). The predictive accuracy of the VS-CM had high sensitivity (97.0%), moderate positive predictive value (71.4%), and high negative predictive value (87.5%); however, the specificity was relatively low (35.0%). The AUC was 79.5% using the total scale of the VS-CM and 70.7-74.5% using the subscales in predicting corresponding types of violence. Conclusion: The VS-CM is a valid and reliable measure of potential violence. It can be applied to assess and predict specific types of violence among inpatient with schizophrenia. © 2013 Elsevier Ltd.