The Average Predictive Validity of Intimate Partner Violence Risk Assessment Instruments

Abstract

The field of intimate partner violence (IPV) risk assessment (predicting recidivism, lethality) is fast growing, and the majority of research examining the predictive validity of IPV risk assessment instruments has been conducted in the past decade. This study examines the average predictive validity weighted by sample size of five stand alone IPV risk assessment instruments that have been validated in multiple research studies using the Receiver Operating Characteristic Area Under the Curve (AUC). The Ontario Domestic Assault Risk Assessment (ODARA) has the highest average weighted AUC (=.666, k=5) followed, in order of most to least predictive, by the Spousal Assault Risk Assessment (SARA; AUC=.628, k=6), the Danger Assessment (DA; AUC=.618, k=4), the Domestic Violence Screening Inventory (DVSI; AUC=.582, k=3), and the Kingston Screening Instrument for Domestic Violence (K-SID; AUC=.537, k=2). The effect size for the average AUCs for IPV risk assessment instruments is small, with the exception of a medium effect size for the ODARA. Of the 20 measures of predictive validity included in this analysis, the risk assessment was administered correctly in nine (45%). IPV risk assessment is relatively new, and the use of proxy instruments and utilization of risk assessment instruments in settings for which they were not created is widespread. While waiting for a more rigorous body of research, factors in addition to predictive validity must be taken into consideration (e.g., setting, outcome, skills of the assessor, access to information) when choosing which risk assessment instrument is appropriate for use in a particular practice setting.

Police as Alert Responders? Lessons Learned about Perceived Roles and Responses from Pretrial GPS Supervision of Domestic Violence Defendants

“…Such tools are utilized to identify defendants who may be at greater risk of recidivism or failure to appear in court as well as maximize efficiency with limited resources (Andrews and Bonta, 1998). The predictive validity of these tools continues to be refined and has increased over time (Messing et al, 2015;Messing and Thaller, 2013). Consistent shortcomings of these risk instruments include failure to accurately collect the required information and the perception of criminal justice personnel that such tools undermine their professional skills and judgment (Andrews and Bonta, 1998;Aubrey and Hough, 1997).…”

“…Research has demonstrated that a large and expanding proportion of U.S. police agencies employ some form of IPV/DV risk assessment instrument (Messing et al, 2015;Police Executive Research Forum, 2015) while police in the U.K. have utilized the Domestic Abuse, Stalking, and Honor Based Violence risk assessment tool since 2009 (Robinson et al, 2016). Despite wide recognition that police should, and have been, adopting risk-led approaches to IPV/DV, the utility of this approach continues to be hindered by practical shortcomings (Bland and Ariel 2015;Hoyle, 2007).…”

The “Golden Thread”: Coercive Control and Risk Assessment for Domestic Violence

“…The majority of research studies on risk assessment for domestic violence have focused on the accuracy with which specific tools can predict future assaults. A meta-analyses by Messing and Thaller (2013) concluded broadly that existing risk assessment tools had moderate levels of predictive validity and that it was difficult to advocate one over another due to methodological variability in the validation studies and the different stated purposes of the tools themselves.…”

Risk assessment of intimate partner violence in a police setting : reliability and predictive accuracy

“…Knowledge on the predictive validity of IPV risk assessments has been examined and summarized in a number of recent review studies, e.g. Helmus andBourgon (2011), Messing andThaller (2013) and Nicholls, Pritchard, Reeves and Hilterman (2013), all of which are described below. However, I have not been able to find any previous reviews examining the predictive validity of IPV assessments conducted by practitioners in different settings specifically, and this will be the focus of the present study.…”

“…For instance, Nicholls et al (2013) presented AUC values ranging between .48 and .92, and Helmus andBourgon (2011) between .59 and.87. Messing andThaller (2013) presented the average AUCs of different tools, which had a smaller range (.54-.67). As was mentioned previously, predictive validity is influenced by many factors, which makes it difficult to compare results from different studies.…”