A Comprehensive Meta-Analysis on Predictors of Domestic Violence Recidivism: The Role of Universal and Specialized Risk Factors - Te Puna Haumaru Seminar Series

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  • Thursday 29 May 2025
  • 2pm - 4pm
  • Online
  • Dr Apriel Jolliffe Simpson, Te Puna Haumaru
  • apriels@waikato.ac.nz
  • Free

A Comprehensive Meta-Analysis on Predictors of Domestic Violence Recidivism: The Role of Universal and Specialized Risk Factors - Te Puna Haumaru Seminar Series.

Despite the proliferation of general risk assessment tools designed to predict any recidivism, numerous tools have been developed for specialized sub-populations, including perpetrators of domestic violence. This is predicated on the assumption that there are unique risk factors for domestic violence compared to general offending. An early meta-analysis, however, suggested that this assumption may not be supported, as generic violence risk tools predicted domestic violence recidivism equally if not better than specialized tools. This meta-analysis coded over 1,800 effect sizes from 120 studies to examine predictors of domestic violence recidivism. Results will compare the predictive accuracy of the generic Central 8 risk factors for crime alongside more specialized factors specific to domestic violence (e.g., dynamics of the relationship, jealousy, stalking behaviour), as well as variables related to personality, mental health, criminal justice system processing, and treatment behaviour. Implications for the relative contribution of generic versus specialized risk factors for this population will be discussed.

Dr L. Maaike Helmus is an Associate Professor in Criminology at Simon Fraser University in Vancouver, British Columbia, Canada. She is also the Vice-President (Research) for the non-profit organization SAARNA (the Society for the Advancement of Actuarial Risk Needs Assessment). Her research has focused on assessing risk of reoffending, particularly for people charged with sexual offences and intimate partner violence. Her research also examines risk assessment topics such as tool development and validation, risk communication, biases in decision-making, and cross-cultural validity.