Violent Crimes

While risk assessment tools exist to identify individuals with mental illness who are likely to commit violent crimes, they are time-consuming and often inaccurate. A new study published in The Lancet Psychiatry has developed the Oxford Mental Illness and Violence tool (OxMIV) and validated it in a population of Swedish patients.


Individuals with mental health conditions often undergo a great deal of stigma and discrimination; these individuals are often criticized for developing mental illnesses and viewed unfavorably due to fear of them being violent and/or dangerous to themselves or others. Despite these views, the risk of individuals with schizophrenia or bipolar disorder (two of the most stigmatized mental illnesses) committing violent crimes is only 5-10%, with most patients never becoming violent in their lifetime. However, understanding violence committed by individuals with mental illness can prevent crimes and morbidity and help reduce the large number of individuals in prison who have mental conditions.

The most prevalent approach to target this issue is to use risk assessment tools. These tools vary from checklists to more complex stratifications to identify individuals who are high versus low risk. Identifying risk of violence can help target resources to these individuals, tailor treatment accordingly and inform decisions about hospital and community initiatives. However, current risk assessment tools have low-to-moderate accuracy, inconsistent definitions of ‘high-risk’, and are time-consuming to complete. Therefore, there is a great need for more simple and accurate violence risk assessment tools.

A new study published in The Lancet Psychiatry developed a clinical prediction score and web calculator called the Oxford Mental Illness and Violence tool (OxMIV) to assess risk for violent crime in individuals with schizophrenia or bipolar disorder. To make this tool, they assessed 75,000 Swedish individuals between the ages of 15 to 65 who had a diagnosis of severe mental illness. With these patients, they determined predictors of violence and modeled the risk of violent crimes being committed within one year of hospital discharge.

Of the cohort studied, they assigned 58,000 individuals to the derivation sample and 16,000 to the validation sample. Within the derivation sample, 830 (1%) individuals committed a violent crime within the first year of discharge. Using patient information, they developed a 16-item model of predictors for violent crime. The strongest predictor was conviction for violent crime, followed by male sex and age. Other predictors included drug and alcohol use, previous self-harm, education level, and parental crimes committed. They then tested this model on their validation group – the model showed 62% sensitivity and 94% specificity in identifying individuals at risk of committing violent crime.

The results from this study support the use of the author’s new prediction score, OxMIV, in identifying individuals with mental illness who are at a high risk of committing a violent crime. They suggest that clinicians begin to use OxMIV to identify these patients and help inform decisions about risk management. Notably, this study only assessed Swedish individuals; therefore, validation of OxMIV in other countries and cultures is ideal. Nonetheless, this study is a step forward for clinical management of high-risk individuals with mental illness.


Written By: Neeti Vashi, BSc

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