To appraise the “real-world” implementation of the risk principle, this study examined the predictive validity of a Risk-Need-Responsivity assessment in the Swedish Prison and Probation Service. Reconviction rates at 24 months follow-up in a cohort of 2,442 offenders were used to assess calibration and discrimination indices. Results indicated acceptable predictive accuracy (AUC = .68–.74), with scope for improvement among young adult offenders. The tool's utility was supported foremost by its ability to screen out low-risk offenders, while over-prediction of recidivism among medium- and high-risk offenders calls for more comprehensive assessment to inform the effective planning of rehabilitative service intensity.
ÆgisdóttirS.WhiteM. J.SpenglerP. M.MaughermanA. S.AndersonL. A.CookR. S.RushJ. D. (2006). The meta-analysis of clinical judgment project: Fifty-six years of accumulated research on clinical versus statistical prediction. The Counseling Psychologist, 34(3), 341–382. https://doi.org/10.1177/0011000005285875
2.
AltmanD. G. (1991). Practical statistics for medical research. Chapman & Hall.
3.
AndrewsD. A.BontaJ.HogeR. D. (1990). Classification for effective rehabilitation: Rediscovering psychology. Criminal Justice and Behavior, 17, 19–52. https://doi.org/10.1177/0093854890017001004
4.
AndrewsD. A.BontaJ.WormithJ. S. (2006). The recent past and near future of risk and/or need assessment. Crime & Delinquency, 52(1), 7–27. https://doi.org/10.1177/0011128705281756
BontaJ.AndrewsD. A. (2007). Risk-Need-Responsivity model for offender assessment and rehabilitation. Rehabilitation, 6(1), 1–22.
8.
BontaJ.AndrewsD. A. (2017). The psychology of criminal conduct (6th ed.). Routledge.
9.
BrennanT.BreitenbachM.DieterichW.SalisburyE. J.Van VoorhisP. (2012). Women’s pathways to serious and habitual crime: A person-centered analysis incorporating gender responsive factors. Criminal Justice and Behavior, 39(11), 1481–1508. https://doi.org/10.1177/0093854812456777
10.
BrownJ.SinghJ. P. (2014). Forensic risk assessment: A beginner’s guide. Archives of Forensic Psychology, 1(1), 49–59.
11.
CampbellM. A.FrenchS.GendreauP. (2009). The prediction of violence in adult offenders: A meta-analytic comparison of instruments and methods of assessment. Criminal Justice and Behavior, 36(6), 567–590. https://doi.org/10.1177/0093854809333610
CookeD. J.MichieC. (2010). Limitations of diagnostic precision and predictive utility in the individual case: A challenge for forensic practice. Law and Human Behavior, 34(4), 259–274. https://doi.org/10.1007/s10979-009-9176-x
14.
CottleC. C.LeeR. J.HeilbrunK. (2001). The prediction of criminal recidivism in juveniles: A meta-analysis. Criminal Justice and Behavior, 28(3), 367–394. https://doi.org/10.1177/0093854801028003005
15.
DaffernM. (2007). The predictive validity and practical utility of structured schemes used to assess risk for aggression in psychiatric inpatient settings. Aggression and Violent Behavior, 12, 116–130. https://doi.org/10.1016/j.avb.2006.03.005
16.
DavidsonJ. T.Chesney-LindM. (2009). Discounting women: Context matters in risk and need assessment. Critical Criminology, 17(4), 221–245. https://doi.org/10.1007/s10612-009-9084-x
17.
DesmaraisS. L.Van DornR. A.TelfordR. P.PetrilaJ.CoffeyT. (2012). Characteristics of START assessments completed in mental health jail diversion programs. Behavioral Sciences & the Law, 30, 448–469. https://doi.org/10.1002/bsl.2022
18.
de VogelV.BruggemanM.LancelM. (2019). Gender-sensitive violence risk assessment: Predictive validity of six tools in female forensic psychiatric patients. Criminal Justice and Behavior, 46(4), 528–549. https://doi.org/10.1177/0093854818824135
FarringtonD. P.PiqueroA. R.JenningsW. G. (2013). Offending from childhood to late middle age: Recent results from the cambridge study in delinquent development. Springer.
21.
FazelS.ChangZ.FanshaweT.LångströmN.LichtensteinP.LarssonH.MallettS. (2016). Prediction of violent reoffending on release from prison: Derivation and external validation of a scalable tool. The Lancet Psychiatry, 3(6), 535–543. https://doi.org/10.1016/S2215-0366(16)00103-6
22.
FazelS.SinghJ. P.DollH.GrannM. (2012). Use of risk assessment instruments to predict violence and antisocial behaviour in 73 samples involving 24 827 people: Systematic review and meta-analysis. BMJ, 345, e4692–e4692. https://doi.org/10.1136/bmj.e4692
23.
GendreauP.LittleT.GogginC. (1996). A meta-analysis of the predictors of adult offender recidivism: What works!. Criminology; An Interdisciplinary Journal, 34(4), 575–608. https://doi.org/10.1111/j.1745-9125.1996.tb01220.x
24.
GönenM. (2007). Analyzing receiver operating CharacteristicCurveswith SAS. SAS Institute Inc.
HoT.RocheleauG. C. (2021). Gender differences in risk assessment among youth adjudicated to juvenile correctional facilities. Women & Criminal Justice, 31, 463–475. https://doi.org/10.1080/08974454.2020.1727819
ImreyP. B.DawidA. P. (2015). A commentary on statistical assessment of violence recidivism risk. Statistics and Public Policy, 2(1), 1–18. https://doi.org/10.1080/2330443X.2015.1029338
29.
LuongD.WormithJ. S. (2011). Applying risk/need assessment to probation practice and its impact on the recidivism of young offenders. Criminal Justice and Behavior, 38(12), 1177–1199. https://doi.org/10.1177/0093854811421596
30.
MartinsonR. (1974). What works?-Questions and answers about prison reform. The Public Interest, 35, 22–54.
31.
MillsJ. F. (2017). Violence risk assessment: A brief review, current issues, and future directions. Canadian Psychology/Psychologie Canadienne, 58(1), 40–49. https://doi.org/10.1037/cap0000100
32.
RiceM. E.HarrisG. T. (2005). Comparing effect sizes in follow-up studies: ROC area, Cohen’s d, and r. Law and Human Behavior, 29(5), 615–620. https://doi.org/10.1007/s10979-005-6832-7
33.
SalisburyE. J.BoppreB.KellyB. (2016). Implications for the treatment of justice-involved women. In TaxmanF. S. (Ed.), Handbook on risk and need assessment: Theory and practice (pp. 220–243). Routledge.
34.
SinghJ. P. (2013). Predictive validity performance indicators in violence risk assessment: A methodological primer. Behavioral Sciences & the Law, 31(1), 8–22. https://doi.org/10.1002/bsl.2052
35.
SkeemJ. L.MonahanJ. (2011). Current directions in violence risk assessment. Current Directions in Psychological Science, 20(1), 38–42. https://doi.org/10.1177/0963721410397271
36.
Starfelt SuttonL.DynevallM.WennerholmJ.ÅhlénS.RuggeT.BourgonG.RobertsonC. (2021). Evaluation of the implementation of a risk-need-responsivity service in community supervision in Sweden. Criminal Justice and Behavior, 48(5), 617–636. https://doi.org/10.1177/0093854820958744
37.
The Swedish National Audit Office. (2011). The work of the Swedish Prison and probation service to prevent reoffending (RiR 2009:27). The Swedish National Audit Office.
38.
van der PutC. E.AssinkM.GubbelsJ. (2020). Differences in risk factors for violent, nonviolent, and sexual offending. Journal of Forensic Psychology Research and Practice, 20(4), 341–361. https://doi.org/10.1080/24732850.2020.1735248
39.
Van VoorhisP.BrownK. (1996). Risk classification in the 1990s. National Institute of Corrections.
40.
ViljoenJ. L.CochraneD. M.JonnsonM. R. (2018). Do risk assessment tools help manage and reduce risk of violence and reoffending? A systematic review. Law and Human Behavior, 42(3), 181–214. https://doi.org/10.1037/lhb0000280
41.
World Health Organization. (2001). AUDIT. The alcohol disorders identification test. Guidelines for use in primary care (2nd ed.). World Health Organization.
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
