To purpose of the current study was to inform system level decision-making about the value of integrating clinically relevant personality information with criminogenic need risk appraisal in justice-involved youth. Using a Canadian sample of youth referred for court-ordered psychological assessments (N = 201, Mage=15.62 years; 70% male), we examined the patterns of association and differentiation between youths’ Youth Level of Service/Case Management Inventory (YLS/CMI) criminogenic need/risk profiles with personality profiles derived from the personality scales of the Millon Adolescent Clinical Inventory (MACI, Millon, Millon adolescent clinical inventory. National Computer Systems, 1993). Specifically, latent profile analysis identified four MACI based personality profiles: externalizing, internalizing, dependent/followers, and complex dysregulated personality profiles. These groups varied significantly on YLS/CMI risk-need profiles. Although both externalizing and complex dysregulated sub-types represented higher criminal risk, their intervention needs diverged meaningfully. These results provide insight into the heterogeneity of justice-involved youth and point to the need for system resources that allow for appropriate intervention matching to maximize the goal of recidivism risk reduction in youth.
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References
1.
AkaikeH. (1987). Factor analysis and AIC. Psychometrika, 52(3), 317–332. 10.1007/BF02294359
2.
AllyA. K.LovattM.MeierP. S.BrennanA., & HolmesJ. (2016). Developing a social practice-based typology of British drinking culture in 2009–2011: Implications for alcohol policy analysis. Addiction (Abingdon, England), 111(9), 1568–1579. 10.1111/add.13397
3.
American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders. (5th ed.). American Psychiatric Association.
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. 10.1177/0011128705281756
5.
BaumL. J.ArcherR. P.ForbeyJ. D., & HandelR. W. (2009). A review of the Minnesota Multiphasic Personality Inventory-Adolescent (MMPI-A) and the Millon Adolescent Clinical Inventory (MACI) with an emphasis on juvenile justice samples. Assessment, 16(4), 384–400. 10.1177/1073191109338264
6.
BlumentrittT. L., & Van VoorhisC. R. W. (2004). The Millon adolescent clinical inventory: Is it valid and reliable for Mexican American youth?Journal of Personality Assessment, 83(1), 64–74. 10.1207/s15327752jpa8301_06
7.
BontaJ., & AndrewsD. A. (2017). The psychology of criminal conduct (6th ed.).Anderson.
8.
BontaJ.BlaisJ., & WilsonH. A. (2014). A theoretically informed meta-analysis of the risk for general and violent recidivism for mentally disordered offenders. Aggression and Violent Behavior, 19(3), 278–287. 10.1016/j.avb.2014.04.014
9.
BontaJ.LawM., & HansonK. (1998). The prediction of criminal and violent recidivism among mentally disordered offenders: A meta-analysis. Psychological Bulletin, 123(2), 123–142. 10.1037/0033-2909.123.2.123
10.
Bonta, J., Rugge, T., Scott, T., Bourgon, G., & Yessine, A. K. (2008). Exploring the black box of community supervision.Journal of Offender Rehabilitation, 47(3), 248–270.
11.
BorghuisJ.DenissenJ. J. A.OberskiD.SijtsmaK.MeeusW. H. J.BranjeS.KootH. M., & BleidornW. (2017). Big five personality stability, change, and codevelopment across adolescence and early adulthood. Journal of Personality and Social Psychology, 113(4), 641–657. 10.1037/pspp0000138
12.
BroganL.Haney-CaronE.NeMoyerA., & DeMatteoD. (2015). Applying the Risk-Needs-Responsivity (RNR) Model to juvenile justice. Criminal Justice Review, 40(3), 277–302. 10.1177/0734016814567312
13.
Brusman-Lovins, L., Lowenkamp, C. T., Latessa, E. J., & Smith, P. (2007). Application of the risk principle to female offenders.Journal of Contemporary Criminal Justice, 23(4), 383–398.
14.
ChanenA. M.TackettJ. L., & ThompsonK. N. (2018). Personality pathology and disorder in children and youth. In LivesleyW. J. & LarstoneR. (Eds.), Handbook of personality disorders: Theory, research, and treatment (2nd ed.; pp. 215–228). Guilford Press.
15.
ChenQ.LuoW.PalardyG. J.GlamanR., & McEnturffA. (2017). The efficacy of common fit indices for enumerating classes in growth mixture models when nested data structure is ignored: A Monte Carlo study. Sage Open, 7(1), 215824401770045. 10.1177/2158244017700459
16.
CeleuxG., & SoromenhoG. (1996). An entropy criterion for assessing the number of clusters in a mixture model. Journal of Classification, 13(2), 195–212. 10.1007/BF01246098
17.
DamianR. I.SpenglerM.SutuA., & RobertsB. W. (2019). Sixteen going on sixty-six: A longitudinal study of personality stability and change across 50 years. Journal of Personality and Social Psychology, 117(3), 674–695. 10.1037/pspp0000210
18.
DouglasK. S.GuyL. S., & HartS. D. (2009). Psychosis as a risk factor for violence to others: A meta-analysis. Psychological Bulletin, 135(5), 679–706. 10.1037/a0016311
19.
Espelage, D. L., Cauffman, E., Broidy, L., Piquero, A. R., Mazerolle, P., & Steiner, H. (2003). A cluster-analytic investigation of MMPI profiles of serious male and female juvenile offenders.Journal of the American Academy of Child & Adolescent Psychiatry, 42(7), 770–777.
20.
FazelS.DollH., & LångströmN. (2008). Mental disorders among adolescents in juvenile detention and correctional facilities: A systematic review and metaregression analysis of 25 surveys. Journal of the American Academy of Child and Adolescent Psychiatry, 47(9), 1010–1019. 10.1097/CHI.0b013e31817eecf3
21.
GendreauP.LittleT., & GogginC. (1996). A meta‐analysis of the predictors of adult offender recidivism: What works!. Criminology, 34(4), 575–608. 10.1111/j.1745-9125.1996.tb01220.x
22.
GudjonssonG. H., & SigurdssonJ. F. (2007). Motivation for offending and personality: A study among young offenders on probation. Personality and Individual Differences, 42(7), 1243–1253. 10.1016/j.paid.2006.10.003
23.
GuebertA. F., & OlverM. E. (2014). An examination of criminogenic needs, mental health concerns, and recidivism in a sample of violent young offenders: Implications for risk, need, and responsivity. International Journal of Forensic Mental Health, 13(4), 295–310. 10.1080/14999013.2014.955220
24.
Hathaway, S. R., & McKinley, J. C. (1989).MMPI-2: Minnesota Multiphasic Personality Inventory-2: Manual for administration and scoring. University of Minnesota Press.
25.
HaqaneeZ.Peterson-BadaliM., & SkillingT. (2015). Making “what works” work: Examining POs’ experiences addressing the criminogenic needs of juvenile offenders. Journal of Offender Rehabilitation, 54(1), 37–59. 10.1080/10509674.2014.980485
26.
HiattM. D., & CornellD. G. (1999). Concurrent validity of the Millon Adolescent Clinical Inventory as a measure of depression in hospitalized adolescents. Journal of Personality Assessment, 73(1), 64–79. 10.1207/S15327752JPA730105
27.
HogeR. D. (2008). Assessment in juvenile justice systems. In HogeR. D.GuerraN. G., & BoxerP. (Eds.), Treating the juvenile offender (pp. 54–75). Guilford Press.
28.
HogeR. D. (2012). Forensic assessments of juveniles: Practice and legal considerations. Criminal Justice and Behavior, 39(9), 1255–1270. 10.1177/0093854812444024
29.
HogeR. D., & AndrewsD. A. (2002). The youth level of service/case management inventory. Multi-Health Systems.
30.
HogeR. D., & AndrewsD. A. (2011). Youth level of service/case management inventory 2.0: User’s manual. Multi-Health Systems.
31.
HubbardD. J. (2007). Getting the most out of correctional treatment: Testing the responsivity principle on male and female offenders. Federal Probation, 71, 2–8.
32.
Jung, S., & Rawana, E. P. (1999). Risk and need assessment of juvenile offenders.Criminal Justice and Behavior, 26(1), 69–89.
33.
KennedyS. M. (2000). Treatment responsivity: Reducing recidivism by enhancing treatment effectiveness. Forum on Corrections Research, 12, 19–23.
34.
Latessa, E., Brusman-Lovins, L., & Smith, P. (2010).Follow-up evaluation of Ohio’s community based correctional facility and halfway house programs—Outcome study. Cincinnati, OH: University of Cincinnati.
35.
Lipsey, M. W. (2009). The primary factors that characterize effective interventions with juvenile offenders: A meta-analytic overview.Victims & Offenders, 4(2), 124–147.
36.
LoY.MendellN. R., & RubinD. B. (2001). Testing the number of components in a normal mixture. Biometrika, 88(3), 767–778. 10.1093/biomet/88.3.767
37.
López-RomeroL.RomeroE., & AndershedH. (2015). Conduct problems in childhood and adolescence: Developmental trajectories, predictors and outcomes in a six-year follow up. Child Psychiatry and Human Development, 46(5), 762–773. 10.1007/s10578-014-0518-7
38.
Lovins, B., Lowenkamp, C. T., & Latessa, E. J. (2009). Applying the risk principle to sex offenders: Can treatment make some sex offenders worse?The Prison Journal, 89(3), 344–357.
39.
Lowenkamp, C. T., & Latessa, E. J. (2004). Understanding the risk principle: How and why correctional interventions can harm low-risk offenders.Topics in Community Corrections, 2004, 3–8.
40.
Lowenkamp, C. T., & Latessa, E. J. (2005). Increasing the effectiveness of correctional programming through the risk principle: Identifying offenders for residential placement.Criminology & Public Policy, 4(2), 263–290.
41.
LowenkampC. T.LatessaE. J., & SmithP. (2006). Does correctional program quality really matter? The impact of adhering to the principles of effective intervention. Criminology & Public Policy, 5(3), 575–594. 10.1111/j.1745-9133.2006.00388.x
42.
McCormickS.Peterson-BadaliM., & SkillingT. A. (2017). The role of mental health and specific responsivity in juvenile justice rehabilitation. Law and Human Behavior, 41(1), 55–67.
43.
McTeagueL. M.GoodkindM. S., & EtkinA. (2016). Transdiagnostic impairment of cognitive control in mental illness. Journal of Psychiatric Research, 83, 37–46. 10.1016/j.jpsychires.2016.08.001
44.
MillonT. (1993). Millon adolescent clinical inventory. National Computer Systems.
45.
MillonT. (2006). Millon adolescent clinical inventory. National Computer Systems.
46.
MooreS. A.DowdyE.Nylund-GibsonK., & FurlongM. J. (2019). An empirical approach to complete mental health classification in adolescents. School Mental Health, 11(3), 438–453. 10.1007/s12310-019-09311-7
47.
Muthén, L. K., & Muthén, B. O. (1998–2015).Mplus user’s guide. Eighth Edition. Los Angeles, CA: Muthén & Muthén.
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. 10.1037/a0035080
49.
Onifade, E., Davidson, W., Livsey, S., Turke, G., Horton, C., Malinowski, J., … Wimberly, D. (2008). Risk assessment: Identifying patterns of risk in young offenders with the youth level of Service/Case management inventory.Journal of Criminal Justice, 36(2), 165–173.
50.
OxnamP., & VessJ. (2006). A personality-based typology of adolescent sexual offenders using the Millon Adolescent Clinical Inventory. New Zealand Journal of Psychology, 35(1), 36–44.
51.
OxnamP., & VessJ. (2008). A typology of adolescent sexual offenders: Millon adolescent clinical inventory profiles, developmental factors, and offence characteristics. Journal of Forensic Psychiatry & Psychology, 19(2), 228–242. 10.1080/14789940701694452
52.
PardiniD., & FrickP. J. (2013). Multiple developmental pathways to conduct disorder: Current conceptualisztions and clinical implications. Journal of the Canadian Academy of Child and Adolescent Psychiatry = Journal de L'Academie Canadienne de Psychiatrie de L'enfant et de L'adolescent, 22(1), 20–25.
53.
PetersonJ. K.SkeemJ.KennealyP.BrayB., & ZvonkovicA. (2014). How often and how consistently do symptoms directly precede criminal behavior among offenders with mental illness?Law and Human Behavior, 38(5), 439–449. 10.1037/lhb0000075
54.
PintoM., & GriloC. M. (2004). Reliability, diagnostic efficiency, and validity of the Millon adolescent clinical inventory: Examination of selected scales in psychiatrically hospitalized adolescents. Behaviour Research and Therapy, 42(12), 1505–1519. 10.1016/j.brat.2003.10.006
55.
PrinsS. J., & DraperL. (2009). Improving outcomes for people with mental illnesses under community corrections supervision: A guide to research-informed policy and practice. Council of State Governments Justice Centre.
56.
PuschN., & HoltfreterK. (2018). Gender and risk assessment in juvenile offenders: A meta-analysis. Criminal Justice and Behavior, 45(1), 56–81. 10.1177/0093854817721720
57.
PurcellR.FraserR.Greenwood-SmithC.BaksheevG. N.McCarthyJ.ReidD.LemphersA., & SullivanD. H. (2012). Managing risks of violence in a youth mental health service: A service model description. Early Intervention in Psychiatry, 6(4), 469–475. 10.1111/j.1751-7893.2012.00372.x
58.
RichardsonG.KellyT. P.GrahamF., & BhateS. R. (2004). A personality-based taxonomy of sexually abusive adolescents derived from the Millon Adolescent Clinical Inventory (MACI). The British Journal of Clinical Psychology, 43(Pt 3), 285–298. 10.1348/0144665031752998
59.
SalekinR. T. (2002). Factor-analysis of the Millon Adolescent Clinical Inventory in a juvenile offender population: Implications for treatment. Journal of Offender Rehabilitation, 34(3), 15–29. 10.1300/J076v34n03_02
60.
SawyerA. M., & BorduinC. M. (2011). Effects of multisystemic therapy through midlife: A 21.9-year follow-up to a randomized clinical trial with serious and violent juvenile offenders. Journal of Consulting and Clinical Psychology, 79(5), 643–652. 10.1037/a0024862
61.
SchmidtF.CampbellM. A., & HouldingC. (2011). Comparative analyses of the YLS/CMI, SAVRY, and PCL: YV in adolescent offenders: A 10-year follow-up into adulthood. Youth Violence and Juvenile Justice, 9(1), 23–42. 10.1177/1541204010371793
62.
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. 10.1177/0093854804274373
63.
SchwarzG. (1978). Estimating the dimension of a model. The Annals of Statistics, 6(2), 461–464. 10.1214/aos/1176344136
64.
ScloveS. L. (1987). Application of model-selection criteria to some problems in multivariate analysis. Psychometrika, 52(3), 333–343. 10.1007/BF02294360
65.
ScottJ.ScottE. M.HermensD. F.NaismithS. L.GuastellaA. J.WhiteD.WhitwellB.LagopoulosJ., & HickieI. B. (2014). Functional impairment in adolescents and young adults with emerging mood disorders. British Journal of Psychiatry, 205(5), 362–368. 10.1192/bjp.bp.113.13426
66.
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(Pt 1), 1–9. 10.1016/j.childyouth.2013.09.015
67.
SkeemJ. L.ManchakS., & PetersonJ. K. (2011). Correctional policy for offenders with mental illness: Creating a new paradigm for recidivism reduction. Law and Human Behavior, 35(2), 110–126. 10.1007/s10979-010-9223-7
68.
SkeemJ. L.WinterE.KennealyP. J.LoudenJ. E.TatarJ. R.II. (2014). Offenders with mental illness have criminogenic needs, too: Toward recidivism reduction. Law and Human Behavior, 38(3), 212–224. 10.1037/lhb0000054
69.
SpaansM.BarendregtM.MullerE.de BeursE.NijmanH., & RinneT. (2009). MMPI profiles of males accused of severe crimes: A cluster analysis. Psychology, Crime & Law, 15(5), 441–450. 10.1080/10683160802356704
70.
SperberK. G.LatessaE. J., & MakariosM. D. (2013). Examining the interaction between level of risk and dosage of treatment. Criminal Justice and Behavior, 40(3), 338–348. 10.1177/0093854812467942
71.
Stefurak, T., & Calhoun, G. B. (2007). Subtypes of female juvenile offenders: A cluster analysis of the millon adolescent clinical inventory.International Journal of Law and Psychiatry, 30(2), 95–111.
72.
StefurakT.CalhounG. B., & GlaserB. A. (2004). Personality typologies of male juvenile offenders using a cluster analysis of the Millon Adolescent Clinical Inventory introduction. International Journal of Offender Therapy and Comparative Criminology, 48(1), 96–110. 10.1177/0306624X03258478
73.
SteinerH.CauffmanE., & DuxburyE. (1999). Personality traits in juvenile delinquents: Relation to criminal behavior and recidivism. Journal of American Academy of Child and Adolescent Psychiatry, 38, 256–262.
74.
SwansonJ. W.SwartzM. S.Van DornR. A.ElbogenE. B.WagnerH. R.RosenheckR. A.StroupT. S.McEvoyJ. P., & LiebermanJ. A. (2006). A national study of violent behavior in persons with schizophrenia. Archives of General Psychiatry, 63(5), 490–499. 10.1001/archpsyc.63.5.490
75.
TaylorJ.KemperT. S.LoneyB. R., & KistnerJ. A. (2006). Classification of severe male juvenile offenders using the MACI clinical and personality scales. Journal of Clinical Child and Adolescent Psychology, 35(1), 90–102. 10.1207/s15374424jccp3501_8
76.
TeinJ. Y.CoxeS., & ChamH. (2013). Statistical power to detect the correct number of classes in latent profile analysis. Structural Equation Modeling, 20(4), 640–657.
77.
van DamC.De BruynE. E. J., & JanssensJ. M. A. M. (2007). Personality, delinquency, and criminal recidivism. Adolescence, 42(168), 763–777.
78.
VincentG. M.PerraultR. T.DrawbridgeD. C.LandryG. O., & GrissoT. (2021). Risk-need responsivity meets mental health: Implementing challenges in probation case planning. Criminal Justice and Behavior, 48(9), 1187–1207.
79.
VitopoulosN. A.Peterson-BadaliM.BrownS., & SkillingT. A. (2019). The relationship between trauma, recidivism risk, and reoffending in male and female juvenile offenders. Journal of Child & Adolescent Trauma, 12(3), 351–364. 10.1007/s40653-018-0238-4
80.
WibbelinkC. J. M.HoeveM.StamsG. J. J. M., & OortF. J. (2017). A meta-analysis of the association between mental disorders and juvenile recidivism. Aggression and Violent Behavior, 33, 78–90. 10.1016/j.avb.2017.01.005
