Violence risk assessment instruments are used to inform key decisions about treatment planning and delivery, release on parole, and intensity of supervision in the community. Yet, limited published information is available about psychometric properties other than predictive validity. The purpose of this study was to examine the factor structure and measurement invariance across pretreatment to posttreatment and cultural groups of one of the most widely used violence risk assessment instruments, the Violence Risk Scale (VRS). Data from 366 completed assessments at preintervention and postintervention phases for adults serving custodial sentences for violent offenses in an Australian jurisdiction were subject to confirmatory factor analysis. The results indicated four intercorrelated but conceptually independent dimensions. Furthermore, measurement invariance was established across pretreatement and posttreatment occasions and different cultural groups. However, latent means comparison revealed significant difference across cultural groups, raising questions about sensitivity and generalizability of the VRS when used with diverse cultural groups.
BontaJ.WormithJ. S. (2013). Applying the risk-need-responsivity principles to offender assessment. In CraigL. A.DixonL.GannonT. A. (Eds.), What works in offender rehabilitation: An evidence-based approach to assessment and treatment (pp. 71–93). Wiley Blackwell. https://doi.org/10.1002/9781118320655.ch4
6.
Brouillette-AlarieS.BabchishinK. M.HansonR. K.HelmusL. M. (2016). Latent constructs of the Static-99R and Static-2002R: A three-factor solution. Assessment, 23(1), 96–111. https://doi.org/10.1177/1073191114568114
7.
Brouillette-AlarieS.ProulxJ.HansonR. K. (2018). Three central dimensions of sexual recidivism risk: Understanding the latent constructs of Static-99R and Static-2002R. Sexual Abuse, 30(6), 676–704. https://doi.org/10.1177/1079063217691965
8.
BrunnerM.SüßH.-M. (2005). Analyzing the reliability of multidimensional measures: An example from intelligence research. Educational and Psychological Measurement, 65(2), 227–240. https://doi.org/10.1177/0013164404268669
9.
ByrneB. M.ShavelsonR. J.MuthénB. (1989). Testing for the equivalence of factor covariance and mean structures: The issue of partial measurement invariance. Psychological Bulletin, 105(3), 456–466. https://doi.org/10.1037/0033-2909.105.3.456
10.
CarminesE. G.McIverJ. P. (1981). Analyzing models with unobserved variables: Analysis of covariance structures. In BohrnstedtG. W.BorgattaE. F. (Eds.), Social measurement: Current issues (pp. 65–115). SAGE.
11.
CraigL. A.BeechA. R. (2010). Towards a best practice in conducting actuarial risk assessments with adult sexual offenders. Aggression and Violent Behavior, 15(4), 278–293. https://doi.org/10.1016/j.avb.2010.01.007
12.
DayA.DaffernM.PolaschekD. L. L.DunneA.SennA. (2020). The classification of people with a history of interpersonal violence for correctional treatment purposes: Possibilities for a schema-informed approach. Aggression and Violent Behavior, 59, Article 101450. https://doi.org/10.1016/j.avb.2020.101450
13.
DayA.TamateaA. J.CaseyS.GeiaL. (2018). Assessing violence risk with Aboriginal and Torres Strait Islander offenders: Considerations for forensic practice. Psychiatry, Psychology and Law, 25(3), 452–464. https://doi.org/10.1080/13218719.2018.1467804
14.
DouglasK. S.SkeemJ. L. (2005). Violence risk assessment: Getting specific about being dynamic. Psychology, Public Policy, and Law, 11(3), 347–383. https://doi.org/10.1037/1076-8971.11.3.347
15.
DuncanR. D.KennedyW. A.PatrickC. J. (1995). Four-factor model of recidivism in male juvenile offenders. Journal of Clinical Child Psychology, 24(3), 250–257. https://doi.org/10.1207/s15374424jccp2403_1
16.
FullerG. (2015). The serious impact and consequences of physical assault. Trends & Issues in Crime and Criminal Justice, 496. Australian Institute of Criminology. https://www.aic.gov.au/publications/tandi/tandi496
17.
HairJ. F.BlackW. C.BabinB. J.AndersonR. E. (2010). Multivariate data analysis (7th ed.). Pearson.
18.
HartS. D. (2016). Culture and violence risk assessment: The case of Ewert v. Canada. Journal of Threat Assessment and Management, 3(2), 76–96. https://doi.org/10.1037/tam0000068
19.
HuL. T.BentlerP. M. (1995). Evaluating model fit. In HoyleR. H. (Ed.), Structural equation modeling: Concepts, issues, and applications (pp. 76–99). SAGE.
20.
HunsleyJ.MashE. J. (2008). Developing criteria for evidence-based assessment: An introduction to assessments that work. In HunsleyJ.MashE. J. (Eds.), Oxford series in clinical psychology. A guide to assessments that work (pp. 3–14). Oxford University Press. https://doi.org/10.1093/med:psych/9780195310641.003.0001
21.
IBM Corporation (2019). IBM SPSS statistics for Windows (Version 26).
22.
JöreskogK. G.SörbomD. (1981). LISREL V: Analysis of linear structural relationships by maximum likelihood and least squares methods (Research Report 81−88). Department of Statistics, University of Uppsala.
23.
KlineR. B. (2016). Methodology in the social sciences: Principles and practice of structural equation modeling (4th ed.). Guilford Press.
24.
LewisK.OlverM. E.WongS. C. P. (2013). The Violence Risk Scale: Predictive validity and linking changes in risk with violent recidivism in a sample of high-risk offenders with psychopathic traits. Assessment, 20(2), 150–164. https://doi.org/10.1177/1073191112441242
25.
MercerG.ZierschE.SowerbuttsS.DayA.PharoH. (2021). The violence prevention program in South Australia: A recidivism and cost–benefit analysis pilot study. Criminal Justice and Behavior, 42(1), 20–36. https://doi.org/10.1177/00938548211038333
MurrayJ.FarringtonD. P.EisnerM. P. (2009). Drawing conclusions about causes from systematic reviews of risk factors: The Cambridge Quality Checklists. Journal of Experimental Criminology, 5(1), 1–23. https://doi.org/10.1007/s11292-008-9066-0
28.
MuthénL. K.MuthénB. O. (1998–2017). Mplus user’s guide (6th ed.).
29.
OlverM. E.LewisK.WongS. C. P. (2013). Risk reduction treatment of high-risk psychopathic offenders: The relationship of psychopathy and treatment change to violent recidivism. Personality Disorders: Theory, Research, and Treatment, 4(2), 160–167. https://doi.org/10.1037/a0029769
30.
OlverM. E.NeumannC. S.KingstonD. A.NicholaichukT. P.WongC. P. (2016). Construct validity of Violence Risk Scale-Sexual Offender version scores in a multisite sample of treated sexual offenders. Assessment, 25(1), 40–55. https://doi.org/10.1177/1073191116643819
31.
OlverM. E.NeumannC. S.WongS. C. P.HareR. D. (2013). The structural and predictive properties of the Psychopathy Checklist–Revised in Canadian Aboriginal and non-Aboriginal offenders. Psychological Assessment, 25(1), 167–179. https://doi.org/10.1037/a0029840
32.
OlverM. E.SowdenJ. N.KingstonD. A.NicholaichukT. P.GordonA.Beggs ChristoffersonS. M.WongS. C. P. (2018). Predictive accuracy of Violence Risk Scale-Sexual Offender version risk and change scores in treated Canadian Aboriginal and non-Aboriginal sexual offenders. Sexual Abuse: A Journal of Research and Treatment, 30(3), 254–275. https://doi.org/10.1177/1079063216649594
33.
OlverM. E.StockdaleK. C.WormithJ. S. (2014). Thirty years of research on the Level of Service Scales: A meta-analytic examination of predictive accuracy and sources of variability. Psychological Assessment, 26(1), 156–176. https://doi.org/10.1037/a0035080
34.
OlverM. E.WongS. C. P. (2019). Offender risk and need assessment: Theory, research and application. In PolaschekD. L. L.DayA.HollinC. R. (Eds.), The international handbook of correctional psychology (pp. 461–475). Wiley. https://doi.org/10.1002/9781119139980.ch28
35.
PolaschekD. L. L. (2006). Violent offender programmes: Concept, theory, and practice. In HollinC. R.PalmerE. J. (Eds.), Offending behaviour programmes: Development, application, and controversies (pp. 113–154). John Wiley. https://doi.org/10.1002/9780470713341.ch4
36.
PolaschekD. L. L. (2019). The psychology of violent offending. In PolaschekD. L. L.DayA.HollinC. R. (Eds.), The international handbook of correctional psychology (pp. 185–205). Wiley. https://doi.org/10.1002/9781119139980.ch12
37.
ProchaskaJ. O.DiClementeC. C.NorcrossJ. C. (1992). In search of how people change: Applications to addictive behaviors. American Psychologist, 47(9), 1102–1114. https://doi.org/10.1037/0003-066X.47.9.1102
38.
RaykovT. (1997). Estimation of composite reliability for congeneric measures. Applied Psychological Measurement, 21(2), 173–184. https://doi.org/10.1177/01466216970212006
39.
RosseggerA.GerthJ.SeewaldK.UrbaniokF.SinghJ. P.EndrassJ. (2013). Current obstacles in replicating risk assessment findings: A systematic review of commonly used actuarial instruments. Behavioral Sciences & the Law, 31(1), 154–164. https://doi.org/10.1002/bsl.2044
40.
SchmidtS.HeffernanR.WardT. (2020). Why we cannot explain cross-cultural differences in risk assessment. Aggression and Violent Behavior, 50, 1359–1789. https://doi.org/10.1016/j.avb.2019.101346
41.
ShepherdS. M.Lewis-FernandezR. (2016). Forensic risk assessment and cultural diversity: Contemporary challenges and future directions. Psychology, Public Policy, and Law, 22(4), 427–438. https://doi.org/10.1037/law0000102
42.
TabachnickB. G.FidellL. S. (2007). Using multivariate statistics (5th ed.). Allyn & Bacon/Pearson Education.
TuckerL. R.LewisC. (1973). A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38(1), 1–10. https://doi.org/10.1007/BF02291170
45.
UgwudikeP. (2020). Digital prediction technologies in the justice system: The implications of a ‘race-neutral’ agenda. Theoretical Criminology, 24(3), 482–501. https://doi.org/10.1177/1362480619896006
46.
VandenbergR. J.LanceC. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practice and recommendations for organizational research. Organizational Research Methods, 3(1), 4–70. https://doi.org/10.1177/109442810031002
47.
van de VijverF.TanzerN. K. (2004). Bias and equivalence in cross-cultural assessment: An overview. European Review of Applied Psychology/Revue Européenne de Psychologie Appliquée, 54(2), 119–135. https://doi.org/10.1016/j.erap.2003.12.004
48.
WaltersG. D. (2017). Beyond dustbowl empiricism: The need for theory in recidivism prediction research and its potential realization in causal mediation analysis. Criminal Justice and Behavior, 44(1), 40–58. https://doi.org/10.1177/0093854816677566
49.
WidamanK. F.ReiseS. P. (1997). Exploring the measurement invariance of psychological instruments: Applications in the substance use domain. In BryantK. J.WindleM.WestS. G. (Eds.), The science of prevention: Methodological advances from alcohol and substance abuse research (pp. 281–324). American Psychological Association. https://doi.org/10.1037/10222-009
50.
WilsonH. A.GutierrezL. (2014). Does one size fit all? A meta-analysis examining the predictive ability of the Level of Service Inventory (LSI) with Aboriginal offenders. Criminal Justice and Behavior, 41(2), 196–219. https://doi.org/10.1177/0093854813500958
51.
WoldgabrealY.DayA.TamateaA. (2020). Do risk assessments play a role in the enduring “color line”?Advancing Corrections: Journal of the International Corrections and Prisons Association, 10, 18–28. https://icpa.org/resources/advancing-corrections-journal.html
52.
WongS. C. P.GordonA. (2003). Violence Risk Scale manual. Department of Psychology, University of Saskatchewan.
53.
WongS. C. P.GordonA. (2006). The validity and reliability of the Violence Risk Scale: A treatment-friendly violence risk assessment tool. Psychology, Public Policy, and Law, 12(3), 279–309. https://doi.org/10.1037/1076-8971.12.3.279
54.
WongS. C. P.ParharK. K. (2011). Evaluation of the predictive validity of the Violence Risk Scale in a paroled offender sample: A seven-year prospective study. Journal of Forensic Psychiatry & Psychology, 22(6), 790–808. https://doi.org/10.1080/14789949.2011.623172
55.
WooditchA.TangL. L.TaxmanF. S. (2014). Which criminogenic need changes are most important in promoting desistance from crime and substance use?Criminal Justice and Behavior, 41(3), 276–299. https://doi.org/10.1177/0093854813503543
56.
YangM.WongS. C.CoidJ. (2010). The efficacy of violence prediction: A meta-analytic comparison of nine risk assessment tools. Psychological Bulletin, 136(5), 740–767. https://doi.org/10.1037/a0020473
