In the assessment world, risk determines “who” to treat and needs determine “what” (Bonta & Andrews, 2016). Yet, for youth, greater emphasis is placed on needs that target recidivism reduction interventions. Unlike risk, needs represent dynamic domains, or latent constructs, requiring testing to assure adequate measurement. We conducted a multi-level, multi-group analysis of the Modified Positive Achievement Change Tool (MPACT) with a 10-state sample of youth (N = 258,464). Findings confirm the validity and reliability of needs domains, and the development of a novel “Global Needs Factor,” a composite summary of needs. Created without criminal history/static measures, needs scales demonstrate predictive accuracy. Further, measurement invariance and aspects of gender and race/ethnicity prediction parity are observed.
American Educational Research Association, American Psychological Association, National Council on Measurement in Education. (2014). Standards for educational and psychological testing. American Educational Research Association.
2.
Andrews. (1982). A personal, interpersonal and community-reinforcement perspective on devoant behaviour (PIC-R). Ontario Ministry of Correctional Services.
3.
AndrewsD. A.BontaJ. (1995). The level of service inventory—Revised. Multi-Health Systems.
4.
AndrewsD. A.BontaJ. (2010). The psychology of criminal conduct (5th ed.). Lexis Nexis/Anderson Pub.
5.
AndrewsD. A.BontaJ.WormithJ. S. (2006). The recent past and near future of risk and/or need assessment. Crime and Delinquency, 52(1), 7–27.
6.
AngwinJ.LarsonJ.MattuS.KirchnerL. (2016). Machine bias. In Martin K. (Ed.), Ethics of data and analytics (pp. 254–264). Auerbach Publications.
7.
BaglivioM. T.JackowskiK. (2013). Examining the validity of a juvenile offending risk assessment instrument across gender and race/ethnicity. Youth Violence and Juvenile Justice, 11(1), 26–43.
8.
BarnoskiR. (1997). Washington State juvenile court recidivism estimates: Fiscal year 1994 youth. Washington Institute for Public Policy.
9.
BarnoskiR. (2004a). Assessing risk for re-offense: Validating the Washington State Juvenile Court Assessment (Report No. 04-03-1201). Washington State Institute for Public Policy.
10.
BarnoskiR. (2004b). Washington State Juvenile Court Assessment manual, Version 2.1 (Report No. 04-03-1203). Washington State Institute for Public Policy.
11.
BelisleL. A.SalisburyE. J. (2021). Starting with girls and their resilience in mind: Reconsidering risk/needs assessments for system-involved girls. Criminal Justice and Behavior, 48(5), 596–616.
12.
BontaJ. (2002). Offender risk assessment: Guidelines for selection and use. Criminal Justice and Behavior, 29(4), 355–379.
13.
BontaJ.AndrewsD. A. (2016). The psychology of criminal conduct. Routledge.
14.
BrennanT.DieterichW.EhretB. (2009). Evaluating the predictive validity of the COMPAS risk and needs assessment system. Criminal Justice and Behavior, 36(1), 21–40.
15.
BrownT. A. (2015). Confirmatory factor analysis for applied research. New York, NY: Routledge.
16.
ButlerL. C.HamiltonZ.KrushasA. E.KigerlA.KowalskiM. (2023). Racial bias and amelioration strategies for juvenile risk assessment. In AhlinE. M.MitchellO.Atkin-PlunkC. (Eds.), Handbook on inequalities in sentencing and corrections among marginalized populations (Division on Corrections Sentencing Handbook, Vol. 7, pp. 70–118). New York, NY: Routledge.
17.
ByrneB. M.StewartS. M. (2006). Teacher's corner: The MACS approach to testing for multigroup invariance of a second-order structure: A walk through the process. Structural Equation Modeling, 13(2), 287–321.
18.
CampbellC. A.BarnesA.PappJ.D’amatoC.AndersonV. R.MosesN. (2020). Understanding the role of neighborhood typology and sociodemographic characteristics on time to recidivism among adjudicated youth. Criminal Justice and Behavior, 47(9), 1079–1096.
19.
CampbellD. T.FiskeD. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56(2), 81–105.
20.
CatalánH. E. N. (2019). Reliability, population classification and weighting in multidimensional poverty measurement: A Monte Carlo Study. Social Indicators Research, 142, 887–910. 2019.
21.
CaudyM. S.DursoJ. M.TaxmanF. S. (2013). How well do dynamic needs predict recidivism? Implications for risk assessment and risk reduction. Criminal Justice Journal, 41(6), 458–466.
22.
ChenF. F.SousaK. H.WestS. G. (2005). Teacher's Corner: Testing measurement invariance of second-order factor models. Structural Equation Modeling, 12, 471–492.
23.
CheungG. W.RensvoldR. B. (2002). Evaluating goodness-of-fit indexes for testing measurement invariance. Structural Equation Modelling, 9(2), 233–255.
24.
ChildsK. K.PeckJ. H.BradyC. M. (2022). Predictive bias in juvenile risk assessment: Considering race/ethnicity and sex. Crime and Delinquency, 00111287221143936.
25.
DengL.ChanW. (2017). Testing the difference between reliability coefficients alpha and omega. Educational and Psychological Measurement, 77(2), 185–203. https://doi.org/10.1177/0013164416658325
26.
ElkingtonK. S.RobsonG.SichelC. E.LeeJ.WassermanG. A. (2023). Family Connect: The Pilot Test of a cross-systems behavioral health treatment referral and linkage intervention for youth on probation. Criminal Justice and Behavior, 50(1), 22–39.
27.
HamiltonZ.CampagnaM.TollefsbolE.van WormerJ.BarnoskiR. (2017). A more consistent application of the RNR model: The STRONG-R needs assessment. Criminal Justice and Behavior, 44(2), 261–292.
28.
HamiltonZ.KigerlA.KowalskiM. (2022). Prediction is local: The benefits of risk assessment optimization. Justice Quarterly, 39(4), 722–744.
29.
HamiltonZ.KowalskiM. A.KigerlA.RouthD. (2019). Optimizing youth risk assessment performance: Development of the modified positive achievement change tool in Washington State. Criminal Justice and Behavior, 46(8), 1106–1127.
30.
HenningK. N. (2012). Criminalizing normal adolescent behavior in communities of color: The role of prosecutors in juvenile justice reform. Cornell Law Review, 98(2), 383–462.
HollinC. R.PalmerE. J.ClarkD. (2003). The level of service inventory-revised profile of English prisoners: A needs analysis. Criminal Justice and Behavior, 30, 422–440.
33.
HsuC. I.CaputiP.ByrneM. K. (2010). Level of Service Inventory–Revised: Assessing the risk and need characteristics of Australian indigenous offenders. Psychiatry, Psychology and Law, 17(3), 355–367.
34.
JungS.RawanaE. P. (1999). Risk and need assessment of juvenile offenders. Criminal Justice and Behavior, 26(1), 69–89.
KapoorA.Peterson-BadaliM.SkillingT. (2018). Barriers to service provision for justice-involved youth. Criminal Justice and Behavior, 45(12), 1832–1851.
37.
KitzmillerM. K.ParukJ. K.CavanaghC. (2022). Criminogenic risk score trajectories of Justice-involved youth: An investigation across Race/ethnicity (p. 00938548221098985). Criminal Justice and Behavior.
38.
KronerD. G. (2005). Issues in violent risk assessment: Lessons learned and future directions. Journal of Interpersonal Violence, 20(2), 231–235.
MatsuedaR. L.DrakulichK. M. (2016). Measuring collective efficacy: A multilevel measurement model for nested data. Sociological Methods & Research, 45(2), 191–230.
43.
MeiX.HamiltonZ.KowalskiM.KigerlA. (2021). Redesigning the Central Eight: Introducing the M-PACT Six. Youth Violence and Juvenile Justice, 19(4), 445–470.
44.
MillerJ.MaloneyC. (2013). Practitioner compliance with risk/needs assessment tools: A theoretical and empirical assessment. Criminal Justice and Behavior, 40(7), 716–736.
45.
MillerW. T.CampbellC. A.PappJ.RuhlandE. (2022). The contribution of static and dynamic factors to recidivism prediction for black and White youth offenders. International Journal of Offender Therapy and Comparative Criminology, 66, 1779–1795.
National Academies of Sciences, Engineering, and Medicine. (2022). The limits of recidivism: Measuring success after prison.
48.
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.
49.
OnifadeE.DavidsonW.CampbellC. (2009). Risk assessment: The predictive validity of the youth level of service case management inventory with African Americans and girls. Journal of Ethnicity in Criminal Justice, 7(3), 205–221.
50.
PalmerE. J.HollinC. R. (2007). The level of service inventory— Revised with English women prisoners. Criminal Justice and Behavior, 34(8), 971–984.
51.
PardoelK. (2020). An examination of the influence of gender and race on dynamic risk assessment [Doctoral dissertation, Carleton University].
52.
PedersenG.HagtvetK. A.KarterudS. (2007). Generalizability studies of the Global Assessment of functioning-split version. Comprehensive Psychiatry, 48(1), 88–94.
53.
PutnickD. L.BornsteinM. H. (2016). Measurement invariance conventions and reporting: The state of the art and future directions for psychological research. Developmental Review, 41, 71–90.
54.
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
55.
RiosJ.WellsC. (2014). Validity evidence based on internal structure. Psicothema, 26(1), 108–116.
56.
RudnevM.LytkinaE.DavidovE.SchmidtP.ZickA. (2017). Testing measurement invariance for a second-order factor: A cross-national test of the alienation scale. Methods, data, analyses, 12(1), 47–76.
57.
SchmidtF.HogeR. D.GomesL. (2005). Reliability and validity analyses of the youth level of service/case management inventory. Criminal Justice and Behavior, 32(3), 329–344.
58.
SchmidtN.LienE.VaughanM.HussM. T. (2017). An examination of individual differences and factor structure on the LS/CMI: Does this popular risk assessment tool measure up?Deviant Behavior, 38(3), 306–317.
59.
SchmidtS.HeffernanR.WardT. (2020). Why we cannot explain cross-cultural differences in risk assessment. Aggression and Violent Behavior, 50, 101346.
60.
SchmittN.KuljaninG. (2008). Measurement invariance: Review of practice and implications. Human Resource Management Review, 18(4), 210–222.
61.
ScottT.BrownS. L.SkillingT. A. (2019). Predictive and convergent validity of the youth assessment and screening instrument in a sample of male and female justice-involved youth. Criminal Justice and Behavior, 46(6), 811–831. https://doi.org/10.1177/0093854819842585
62.
SinghJ. (2013). Predictive validity performance indicators in violence risk assessment: A methodological primer. Behavioral Sciences & the Law, 31.
63.
SinghJ. P.DesmaraisS. L.SellersB. G.HyltonT.TirottiM.Van DornR. A. (2014). From risk assessment to risk management: Matching interventions to adolescent offenders’ strengths and vulnerabilities. Children and Youth Services Review, 47, 1–9.
64.
SkeemJ.MonahanJ.LowenkampC. (2016). Gender, risk assessment, and sanctioning: The cost of treating women like men. Law and Human Behavior, 40(5), 580–593.
65.
SkeemJ. L.KennealyP. J.HernandezI. (2013). CA-YASI construct validity: To what extent do the domains measure the risk factors they’re supposed to measure? Division of Juvenile Justice. California Department of Corrections and Rehabilitation. Rsilience.berkeley.edu/content/publications-1.
66.
StevensonH. E.WormithJ. S. (1987). Psychopathy and the level of supervision inventory (User Report 1987-25). Ministry of the Solicitor General of Canada.
67.
SteyerbergE. W.BleekerS. E.MollH. A.GrobbeeD. E.MoonsK. G. (2003). Internal and external validation of predictive models: A simulation study of bias and precision in small samples. Journal of Clinical Epidemiology, 56(5), 441–447.
68.
SullivanC. J.McCaffertyJ.NewsomeJ.MandalariA. (2022). Predictive validity and measurement invariance in juvenile risk assessment: Implications for racial and ethnic disparities in juvenile justice. Journal of Crime and Justice, 45, 409–429.
69.
SullivanC. J.StrangeC.SullivanC.NewsomeJ.LugoM.MuellerD.McCaffertyJ. (2019). Multi-method study on risk assessment implementation and youth outcomes in the juvenile justice system. University of Cincinnati, Center for Criminal Justice Research.
70.
TabachnickB. G.FidellL. S. (2007). Using multivariate statistics (5th ed.). Allyn & Bacon/Pearson Education.
71.
TaxmanF. S. (2017). Handbook of recidivism risk/needs assessment tools. In SinghJ. P.KronerD.WormithS.DesmaraisS.HamiltonL. & Z. (Eds.), Risk assessment: Where do we go from here? (pp. 269–284). Wiley-Blackwell.
72.
TaxmanF. S.CaudyM. S. (2015). Risk tells us who, but not what or how: Empirical assessment of the complexity of criminogenic needs to inform correctional programming. Criminology & Public Policy, 14(1), 71–103.
73.
TaxmanF. S.SmithL. (2021). Risk-need-responsivity (RNR) classification models: Still evolving. Aggression and Violent Behavior, 59, 101459. https://doi.org/10.1016/j.avb.2020.101459
74.
ThompsonM. (2004). The value of item response theory in clinical assessment: A review. Assessment, 18(3), 291–307.
75.
Van VoorhisP.WrightE. M.SalisburyE.BaumanA. (2010). Women’s risk factors and their contributions to existing risk/needs assessment: The current status of a gender-responsive supplement. Criminal Justice and Behavior, 37(3), 261–288.
76.
ViglioneJ.RudesD. S.TaxmanF. S. (2015). The myriad of challenges with correctional change: From goals to culture. European Journal of Probation, 7(2), 103–123.
77.
VincentG. M.ChapmanJ.CookN. E. (2011). Risk-needs assessment in juvenile justice: Predictive validity of the SAVRY, racial differences, and the contribution of needs factors. Criminal Justice and Behavior, 38(1), 42–62.
78.
VincentG. M.GuyL. S.GrissoT. (2012). Assessment in juvenile justice: A guidebook for implementation. John D. and Catherine T. MacArthur Foundation.
79.
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.
80.
WormithS. J.BontaJ. (2018). The level of service (LS) instruments. Handbook of recidivism risk/needs assessment tools (pp. 117–145). John Wiley & Sons.
81.
ZottolaS. A.DesmaraisS. L.LowderE. M.Duhart ClarkeS. E. (2022). Evaluating fairness of algorithmic risk assessment instruments: The problem with forcing dichotomies. Criminal Justice and Behavior, 49(3), 389–410.
Supplementary Material
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.
