CJB189
Assessing the risk of domestic violence recidivism
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Summary
Aim
To determine what factors independently predict violent DV-related re-offending among a cohort of people convicted of a(ny) DV offence and given a non-custodial penalty.
Method
Data from the NSW Bureau of Crime Statistics and Research (BOCSAR) Reoffending Database were used to examine violent DV-related reconviction. A cohort of DV offenders convicted in 2011-12 was first identified using domestic violence lawpart codes, and followed up for two years. To identify the best fitting model we first examined bi-variate relationships between explanatory variables and the dependent variable. We then estimated a multivariate logistic regression model to determine which variables independently predicted reconviction. Finally, we tested the predictive validity of the model using a range of cross-validation strategies.
Results
Among the cohort of adult offenders (n = 14,660), 8% were reconvicted of a violent DV-related offence within two years of the index conviction. Eleven explanatory variables were found to best predict reconviction – representing offender demographic, index offence, and criminal history characteristics. The resulting model showed acceptable levels of predictive validity.
Conclusion
To the extent that they direct appropriate interventions, risk assessment tools could be one part of a more complete community safety strategy aimed at violent DV recidivism. Limitations of the current study are discussed.
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