Clinicians have at their disposal a variety of instruments with which to evaluate the risk presented by sex offenders. These measures yield similar predictive potency, and combining them does not appear to enhance prediction. The present study examined whether classification and regression tree analysis could identify new combinations of predictors that would improve predictive validity. Items from seven actuarial instruments were used to construct classification trees. Overall, classification trees achieved slightly higher predictive accuracy than did actuarial instruments. In addition, these analyses highlight the heterogeneity among sex offenders. Despite this improvement, one should consider the incorporation of other predictors into the instruments—including dynamic factors, protective factors, and measures with strong theoretical justification.
AbelG. G.BeckerJ. V.Cunningham-RatherJ. (1984). Complications, consent, and cognitions in sex between children and adults. International Journal of Law and Psychiatry, 7, 89-103.
2.
AbelG. G.GoreD. K.HollandC. L.CampN.BeckerJ.RatherJ. (1989). The measurement of the cognitive distortions of child molesters. Annals of Sex Research, 2, 135-153.
3.
AegisdottirS.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.
4.
AndrewsD. A.BontaJ. (1995). The Level of Service Inventory–Revised. Toronto, Canada: Multi-Health Systems.
5.
BarbareeH. E.LangtonC. M.PeacockE. J. (2006). The factor structure of static actuarial items: Its relation to prediction. Sexual Abuse, 18(2), 207-226.
6.
BarbareeH. E.SetoM.LangtonC. M.PeacockE. J. (2001). Evaluating the predictive accuracy of six risk assessment instruments for adult sex offenders. Criminal Justice and Behavior, 28, 490-521.
7.
BartoshD. L.GarbyT.LewisD.GrayS. (2003). Differences in the predictive validity of actuarial risk assessments in relation to sex offender type. International Journal of Offender Therapy and Comparative Criminology, 47(4), 422-438.
8.
BengstonS.LångströmN. (2007). Unguided clinical and actuarial assessment of re-offending risk: A direct comparison with sex offenders in Denmark. Sexual Abuse, 19, 135-153.
9.
BoerD. P.WilsonR. J.GauthierC. M.HartS. D. (1997). Assessing risk of sexual violence : Guidelines for clinical practice. In WebsterC. D.JacksonM. A. (Eds.), Impulsivity: Theory, assessment, and treatment (pp. 326-342). New York, NY: The Guilford Press.
10.
BoltD. M.HareR. D.VitaleJ. E.NewmanJ. P. (2004). A multigroup item response theory analysis of the Psychopathy Checklist–Revised. Psychological Assessment, 16, 155-168.
11.
BontaJ. (1996). Risk-needs assessment and treatment. In HarlandA. T. (Ed.), Choosing correctional options that work (pp. 18-32). Thousand Oaks, CA: Sage.
12.
BreimanL.FriedmanJ. H.OlshenR. A.StoneC. G. (1998). Classification and regression trees. Belmont, CA: Wadsworth.
13.
BurgessE. (1928). Factors determining success or failure on parole. In BruceA. H. A.BurgessE.LandescoJ. (Eds.), The workings of the undetermined-sentence law and the parole system in Illinois (pp. 205-249). Springfield, IL: State Board of Parole.
14.
CraigL. A.BrowneK. D.StringerI.BeechA. (2004). Limitations in actuarial risk assessment of sexual offenders: A methodological note. British Journal of Forensic Practice, 6(1), 16-32.
15.
CraigL. A.BrowneK. D.StringerI.BeechA. (2005). Sexual recidivism: A review of static, dynamic and actuarial predictors. Journal of Sexual Aggression, 11(1), 65-84.
16.
CraigL. A.BrowneK. D.StringerI.HogueT. E. (2008). Sexual reconviction rates in the United Kingdom and actuarial risk estimates. Child Abuse and Neglect, 32, 121-138.
17.
DaversaM. T.KnightR. A. (2007). A structural examination of the predictors of sexual coercion against children in adolescent sexual offenders. Criminal Justice and Behavior, 34(10), 1313-1333.
18.
DorenD. M. (2002). Evaluating sex offenders: A manual for civil commitments and beyond. Thousand Oaks, CA: Sage.
19.
DorenD. M. (2004). Toward a multidimensional model for sexual recidivism risk. Journal of Interpersonal Violence, 19(8), 835-856.
20.
EherR.MatthesA.SchillingF.Haubner-MacLeanT.RettenbergerM. (2012). Dynamic risk assessment in sexual offenders using STABLE-2000 and the STABLE-2007: An investigation of predictive and incremental validity. Sexual Abuse, 24(1), 5-28.
FinkelhorD. (1984). Child sexual abuse: New theory and research. New York, NY: Free Press.
23.
FrancisB.HarrisD. A.WallaceS.KnightR. A.SoothillK. (2012). Sexual and general offending trajectories of men prior to referral for civil commitment, Manuscript submitted for publication.
24.
GroveW. M.ZaldD. H.LebowB. S.SnitzB. E.NelsonC. (2000). Clinical versus mechanical prediction: A meta-analysis. Psychological Assessment, 12(1), 19-30.
25.
HallG. C. N.HirschmanR. (1992). Sexual aggression against children: A conceptual perspective of etiology. Criminal Justice and Behavior, 19, 8-23.
26.
HamdiN.KnightR. A. (in press). The effects of perpetrator and victim intoxication on the sexual aggressiveness of rapists and child molesters. Sexual Abuse.
27.
HansonK. R. (1997). Établissement d’une échelle actuarielle sommaire du risque de récidive sexuelle [The development of a brief actuarial risk scale for sexual offense recidivism] (User Rep. 1997-04). Ottawa, Canada: Ministère du Solliciteur général du Canada.
28.
HansonK. R.BussièreM. T. (1998). Predicting relapse: A meta-analysis of sexual offender recidivism studies. Journal of Consulting and Clinical Psychology, 66(2), 348-362.
29.
HansonK. R.HarrisA. J. R. (1998). Les prédicteurs dynamiques de la récidive sexuelle [Dynamic predictors of sexual recidivism] (User Rep. 1998-01). Ottawa, Canada: Ministère du Solliciteur général du Canada.
30.
HansonK. R.HarrisA. J. R. (2000). Where should we intervene? Dynamic predictors of sexual offense recidivism. Criminal Justice and Behavior, 27, 6-35.
31.
HansonK. R.HarrisA. J. R.ScottT. L.HelmusL. (2007). Assessing the risk of sexual offenders on community supervision: The Dynamic Supervision Project. Ottawa: Sécurité Publique du Canada.
32.
HansonK. R.ThorntonD. (2000). Improving risk assessments for sex offenders: A comparison of three actuarial scales. Law and Human Behavior, 24(1), 119-136.
33.
HansonK. R.ThorntonD. (2003). Notes sur l’élaboration de la Statique-2002 [Notes on the development of Static-2002] (User Rep. 2003-01). Ottawa: Ministère du Solliciteur général du Canada & Department of Health and Family Services of Wisconsin.
34.
HansonK. R.MortonK. E.HarrisK. E. (2003). Sexual offender recidivism risk: What we know and what we need to know. Annals of the New York Academy of Sciences, 989, 154-166.
35.
HansonK. R.Morton-BourgonK. E. (2004). Les prédicteurs de la récidive sexuelle: une méta-analyse à jour [Predictors of sexual recidivism: An up-to-date meta-analysis] (User Rep. 2004-02). Ottawa: Sécurité publique et Protection civile Canada.
36.
HansonK. R.Morton-BourgonK. E. (2007). L’exactitude des évaluations du risque de récidive chez les délinquants sexuels: une méta-analyse [The accuracy of recidivism risk assessments for sexual offenders] (User Rep. 2007-01). Ottawa: Sécurité publique et Protection civile Canada & Ministère de la Justice du Canada.
37.
HansonK. R.Morton-BourgonK. E. (2009). The accuracy of recidivism risk assessments for sexual offenders: A meta-analysis of 118 prediction studies. Psychological Assessment, 21(1), 1-21.
38.
HareR. D. (1991). Manual for the Psychopathy Checklist–Revised. Toronto, Canada: Multi-Health Systems.
39.
HareR. D. (2003). The Hare Psychopathy Checklist-Revised. Toronto, Ontario: Multi-Health Systems.
40.
HarrisA. J. R.HansonK. R. (2004). Sex offender recidivism: A simple question. Ottawa: Public Safety and Emergency Preparedness Canada.
41.
HarrisD. A.SmallboneS.DennisonS.KnightR. A. (2009). Specialization and versatility in sexual offenders referred for civil commitment. Journal of Criminal Justice, 37, 37-44.
42.
HarrisG. T.RiceM. E.QuinseyV. L. (1993). Violent recidivism of mentally disordered offenders: The development of a statistical prediction instrument. Criminal Justice and Behavior, 20, 315-335.
43.
HarrisG. T.RiceM. E.QuinseyV. L.LalumièreM. L.BoerD.LangC. (2003). A multisite comparison of actuarial risk instruments for sex offenders. Psychological Assessment, 15, 413-425.
44.
HawkinsJ. D.Van HornM. L.ArthurM. W. (2004). Community variation in risk and protective factors and substance use outcomes. Prevention Science, 5, 213-220.
45.
HerrenkohlT. I.HillK. G.ChungI.-J.GuoJ.AbbottR. D.HawkinsJ. D. (2003). Protective factors against serious violent behavior in adolescence: A prospective study of aggressive children. Social Work Research, 27, 179-189.
46.
KnightR.Sims-KnightJ. E. (2003). The developmental antecedents of sexual coercion against women: Testing alternative hypotheses with structural equation modeling. Annals of New York Academy of Science, 989, 72-85.
47.
KnightR. A. (1999, September). Unified theory of sexual coercion. Paper presented at the 18th annual conference of the Association for Treatment of Sexual Abusers, Lake Buena Vista, FL.
48.
KnightR. A.CarterD. L.PrentkyR. A. (1989). A system for the classification of child molesters: Reliability and application. Journal of Interpersonal Violence, 4(1), 3-23.
49.
KnightR. A.GuayJ. P. (2006). The role of psychopathy in sexual coercion against women. In PatrickC. J. (Ed.), Handbook of psychopathy (pp. 512-532). New York, NY: Guilford.
50.
KnightR. A.GuayJ.-P.GrabellA.ThorntonD. (2007, October). Creating distinct actuarial techniques for rapists and child molesters. Paper presented at the 21st annual meeting of the Society for Research in Psychopathology, Iowa City, IA.
51.
KnightR. A.PrentkyR. A. (1990). Classifying sexual offenders: The development and corroboration of taxonomic models. In MarshallW. L.LawsD. R.BarbareeH. E. (Ed.), The handbook of sexual assault: Issues, theories, and treatment of the offender (pp. 23-52). New York, NY: Plenum.
52.
KnightR. A.RonisS. T.KafkaM. P. (2012). The role of sexual motivation in sexual offending behavior. Manuscript submitted for publication.
53.
KnightR. A.RonisS. T.ZakirehB. (2009). Bootstrapping persistence risk indicators for juveniles who sexually offend. Behavioral Sciences and the Law, 27, 878-909.
54.
KnightR. A.RosenbergR.SchneiderB. A. (1985). Classification of sexual offenders: Perspectives, methods, and validation. In BurgessA. W. (Ed.), Rape and sexual assault (pp. 222-293). New York, NY: Garland.
55.
KnightR. A.Sims-KnightJ. E. (2003). The development antecedents of sexual coercion against women in adolescents. In FraneyR. G. K. (Ed.), Sex offenders: Assessment and treatment (pp. 72-85). New York, NY: Haworth.
56.
KnightR. A.ThorntonD. (2007, March). Do different variables predict recidivism in rapists and child molesters?Paper presented at the Academy of Criminal Justice Sciences, Seattle, WA.
57.
KronerD. G.MillsJ. F.ReddonJ. R. (2005). A coffee can, factor analysis, and prediction of antisocial behavior: The structure of criminal risk. International Journal of Law and Psychiatry, 28, 360-374.
58.
LangtonC. M.BarbareeH.HansenK. T.HarkinsL.PeacockE. J. (2007). Reliability and validity of the Static-2002 among adult sexual offenders with reference to treatment status. Criminal Justice and Behavior, 34, 616-640.
59.
LangtonC. M.BarbareeH.SetoM.PeacockE. J.HarkinsL.HansenK. T. (2007). Actuarial assessment of risk for reoffense among adult sex offenders: Evaluating the predictive accuracy of the Static-2002 and five other instruments. Criminal Justice and Behavior, 34, 37-59.
60.
LaubJ. H.SampsonR. J. (1993). Turning point in the life course: Why change matters to the study of crime. Criminology, 31(3), 301-325.
61.
LaubJ. H.SampsonR. J. (2003). Shared beginnings, divergent lives: Delinquent boys to age 70. Cambridge, MA: Harvard University Press.
62.
LussierP.LeblancM.ProulxJ. (2005). The generality of criminal behavior: A confirmatory factor analysis of the criminal activity of sex offenders in adulthood. Journal of Criminal Justice, 33, 177-189.
63.
MalamuthN. M.MalamuthE. Z. (1999). Integrating multiple levels of scientific analysis and the confluence model of sexual coercers. Jurimetrics, 39, 157-179.
64.
MarshallD. R.BarbareeH. E. (1990). An integrated theory of the etiology of sexual offending. In MarshallW. L.LawsD. R.BarbareeH. E. (Ed.), Handbook of sexual assault (pp. 257-275). New York, NY: Plenum.
65.
MarshallD. R.MarshallL. E. (2000). The origins of sexual offending. Trauma, Violence & Abuse, 1, 250-263.
66.
McGrawK. O.WongS. P. (1996). Forming Inferences about Some Intraclass Correlation Coefficients. Psychological Methods, 1(1), 30-46.
67.
MeehlP. E. (1954). Clinical versus statistical prediction. Minneapolis: University of Minnesota Press.
68.
MeehlP. E.RosenA. (1955). Antecedent probability and the efficiency of psychometrics signs, patterns, or cutting scores. Psychological Bulletin, 52(3), 194-216.
69.
MossmanD. (1994). Assessing predictions of violence: Being accurate about accuracy. Journal of Consulting and Clinical Psychology, 62(4), 783-792.
70.
MurrieD. C.BoccacciniM. T.TurnerD. B. (2010). Ethical challenges in sex offender civil commitment evaluations—Applying imperfect science in adversarial proceedings. In SchlankA. (Ed.), The sexual predator (Vol. 4, pp. 8.1-8.35). New York, NY: Civic Research Institute.
71.
NeuillyM. A.ZgobaK. M.TitaG. E.LeeS. S. (2011). Predicting recidivism in homicide offenders using classification tree analysis. Homicide Studies, 15(2), 154-176.
72.
NuffieldJ. (1982). Parole decision-making in Canada: Research towards decision guidelines. Ottawa: Ministry of Supply and Services Canada.
73.
ParentG.GuayJ. P.KnightR. A. (2011). An assessment of long-term risk of recidivism by adult sex offenders: One size doesn’t fit all. Criminal Justice and Behavior, 38, 188-209.
74.
ProulxJ.PerreaultC.OuimetM.GuayJ. P. (1999). Les agresseurs sexuels d’enfants: Scénarios délictuels et troubles de la personnalité [Child molesters: Modus operandi and personality disorders]. In ProulxJ.CussonM.OuimetM. (Ed.), Les violences criminelles (pp. 187-216). Québec, Canada: Les Presses de l’Université Laval.
75.
ProulxJ.St-YvesM.GuayJ. P.OuimetM. (1999). Les agresseurs sexuels de femmes: Scénarios délictuels et troubles de la personnalité [Rapists: Modus operandi and personality disorders]. In ProulxJ.CussonM.OuimetM. (Ed.), Les violences criminelles (pp. 157-185). Québec, Canada: Les Presses de l’Université Laval.
76.
QuinseyV. L.HarrisG. T.RiceM. E.CormierC. A. (1998). Actuarial prediction of violence. In QuinseyV. L.HarrisG. T.RiceM. E.CormierC. A.Violent offenders: Appraising and managing risk (pp. 141-169). Washington, DC: American Psychological Association.
77.
RobertsC. F.DorenD. M.ThorntonD. (2002). Dimensions associated with assessments of sex offender recidivism risk. Criminal Justice and Behavior, 29, 569-589.
78.
RosenfeldB.LewisC. (2005). Assessing violence risk in stalking cases: A regression tree approach. Law and Human Behavior, 29(3), 343-349.
79.
SetoM. C. (2005). Is more better? Combining actuarial risk scales to predict recidivism among adult sex offenders. Psychological Assessment, 17(2), 156-167.
80.
SitnikovL.GoldbergJ.DaversaM. T.KnightR. A. (2007, April). The interplay of the factors of psychopathy and borderline personality disorder in predicting violence in sexual offenders. Poster presented at the 2nd biannual meeting of the Society for the Scientific Study of Psychopathy, St. Petersburg, FL.
81.
SjöstedtG.GrannM. (2002). Risk assessment: What is being predicted by actuarial prediction Instruments?International Journal of Forensic Mental Health, 1(2), 179-183.
82.
SjöstedtG.LångströmN. (2001). Actuarial assessment of sex offender recidivism risk: A cross-validation of the RRASOR and the Static-99 in Sweden. Law and Human Behavior, 25(6), 629-645.
83.
SjöstedtG.LångströmN. (2002). Assessment of risk for criminal recidivism among rapists: A comparison of four different measures. Psychology, Crime and Law, 8, 25-40.
84.
SmokowskiP. R.MannE. A.ReynoldsA. J.FraserM. W. (2004). Childhood risk and protective factors and late adolescent adjustment in inner city minority youth. Children and Youth Services Review, 26, 63-91.
85.
StalansL. J.YarnoldP. R.SengM.OlsonD. E.ReppM. (2004). Identifying three types of violent offenders and predicting violent recidivism while on probation: A classification tree analysis. Law and Human Behavior, 28(3), 253-271.
86.
SteadmanH. J.SilverE.MonahanJ.AppelbaumP. S.RobbinsP. C.MulveyE. P.. . . BanksS. (2000). A classification tree approach to the development of actuarial violence risk assessment tools. Law and Human Behavior, 24(1), 83-100.
87.
ThorntonD. (2002). Constructing and testing a framework for dynamic risk assessment. Sexual Abuse, 14(2), 139-153.
88.
ThorntonD.MannR.WebsterS.BludL.TraversR.FriendshipC.EriksonM. (2003). Distinguishing and combining risk for sexual and violent recidivism. Annals of the New York Academy of Sciences, 989, 225-235.
89.
VogelV. D.RuiterC. D.BoumanY. H. A.Vries RobbéM. D. (2009). SAPROF: Guideline for the assessment of protective factors for violence risk (English version). Utrecht, Netherlands: Forum Educatief.
90.
Vries RobbéM. D. (2011, November). Protective factors for sexual offenders? Research results with the SAPROF. Paper presented at the 29th annual conference of the Association for the Treatment of Sexual Abusers, Toronto, Canada.
91.
Vries RobbéM. D.VogelV. D.SpaE. D. (2011). Protective factors for violence risk in forensic psychiatric patients: A retrospective validation study of the SAPROF. International Journal of Forensic Mental Health, 10, 178-186.
92.
WardT.KeenanT.HudsonS. M. (2000). Understanding cognitive, affective, and intimacy deficits in sexual offenders: A developmental perspective. Aggression and Violent Behavior, 5, 41-62.
93.
WrightB. R. E.CaspiA.MoffittT. E.SilvaP. A. (2001). The effects of social ties on crime vary by criminal propensity: A life-course model of interdependence. Criminology, 39(2), 321-352.
