Dr Li Eriksson1, Dr Shilan Caman, Dr Clair Alston-Knox, Dr Samara McPhedran, Professor Paul Mazerolle, Professor Richard Wortley
1Griffith University, ,
A growing body of literature has identified a range of risk factors for intimate partner violence against women, including – but not limited to – past violence toward the victim, controlling behaviour, relationship separation, substance abuse, prior offending, and mental health problems. Based on these known factors, several tools have been developed that assess the risk of non-lethal violent recidivism or lethal violence. The outcome of interest in such assessments is the level of risk (high/low) to the victim, which is based on the summated scores. This is important, given that factors associated with intimate partner femicide are rarely presented independently of other factors. For example, death review data from Ontario show that male offenders of intimate partner femicide displayed on average 10.5 of the 40 risk factors, and rarely (14%) did offenders display three or fewer risk factors (Office of the Chief Coroner, 2017). Nevertheless, given that some research suggests that intimate partner femicide may be a heterogeneous phenomenon, it is also important to examine combinations of factors. Yet relatively few studies have examined whether, how, and which risk factors cluster together. We address this knowledge gap by using a data-driven approach (profile regression) to examine clusters of intimate partner femicide offenders based on known risk factors.
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