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Record ID: f526d08d-931d-4c31-9b5e-0f769106adfb
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Type: Report
Title: Actuarial assessment of domestic violence recidivism risk among custody-based males: The Domestic Violence – Triage Risk Assessment Scale (DV-TRAS)
Authors: Howard, Mark
Wei, Zhigang
Zhang, Yun
Corben, Simon
Year: 2022
Publisher: Corrective Services NSW
Abstract:  Aim To develop an automated risk assessment tool that can be used to rapidly estimate custody-based DV offenders’ likelihood of DV recidivism, using official administrative data that are routinely collected by Corrective Services NSW. Method The model development sample included all males in NSW who served a custodial sentence associated with one or more DV convictions between January 2013 and June 2017 (n = 6,100). A series of regression models were used to test predictors of DV recidivism and develop optimal estimates of recidivism probability. The final model was validated using bootstrapping techniques and various tests of predictive validity. Results Significant predictors of DV recidivism included age; alcohol and other drug problems; markers of a more extensive general criminal history; being released without the possibility of parole; and Indigenous status, as well as DV-specific variables such as prior sentences involving DV convictions and breaches of protection orders. The final estimation model, which we named the DV-TRAS, showed acceptable discrimination performance for DV recidivism (AUC = .660; 95% CI = .646-.675) that was significantly better than routine assessments of general recidivism risk. Bootstrapping techniques indicated satisfactory stability of the model across simulated samples. Conclusion The DV-TRAS appears to be a viable tool to support case management decision making for custody-based DV offenders in NSW. Key tests of predictive validity indicated accuracy in discriminating DV recidivists that was significantly better than general risk assessments, and similar to that of established manual assessments of offence-specific risk, while allowing for substantial time and resource savings in generating estimates.
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