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The effect of discordance among violence and general recidivism risk estimates on predictive accuracy
Author(s) -
Mills Jeremy F.,
Kroner Daryl G.
Publication year - 2006
Publication title -
criminal behaviour and mental health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.63
H-Index - 54
eISSN - 1471-2857
pISSN - 0957-9664
DOI - 10.1002/cbm.623
Subject(s) - recidivism , psychopathy checklist , psychology , checklist , risk assessment , psychopathy , predictive validity , term (time) , sample (material) , predictive power , poison control , actuarial science , injury prevention , clinical psychology , statistics , medicine , computer science , social psychology , environmental health , computer security , personality , antisocial personality disorder , mathematics , economics , philosophy , cognitive psychology , chemistry , quantum mechanics , physics , chromatography , epistemology
Previous research has shown that the prediction of short‐term inpatient violence is negatively affected when clinicians' inter‐rater agreement is low and when confidence in the estimate of risk is low. This study examined the effect of discordance between risk assessment instruments used to predict long‐term general and violence risk in offenders. Methods The Psychopathy Checklist – Revised (PCL–R), Level of Service Inventory – Revised (LSI–R), Violence Risk Appraisal Guide (VRAG), and the General Statistical Information on Recidivism (GSIR) were the four risk‐prediction instruments used to predict post‐release general and violent recidivism within a sample of 209 offenders. Results The findings lend empirical support to the assumption that predictive accuracy is threatened where there is discordance between risk estimates. Discordance between instruments had the impact of reducing predictive accuracy for all instruments except the GSIR. Further, the influence of discordance was shown to be greater on certain instruments over others. Discordance had a moderating effect on both the PCL–R and LSI–R but not on the VRAG and GSIR. Conclusions There is a distinct advantage when attempting to predict recidivism to employing measures such as the LSI‐R, which includes dynamic variables and intervention‐related criminogenic domains, over a measure purely of fixed characteristics, such as the GSIR; however, if there is discordance between the risk estimates, caution should be exercised and more reliance on the more static historically based instrument may be indicated. Copyright © 2006 John Wiley & Sons, Ltd.