Predicting Risk of Sexual Recidivism in Juveniles: Predictive Validity of the J‐SOAP‐II

Prentky, Robert A.; Pimental, Ann; Cavanaugh, Deborah J.; Righthand, Sue

doi:10.1002/9780470714362.ch15

Cited by 9 publications

(9 citation statements)

References 73 publications

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“…In their widely published Dunedin Multidisciplinary Health and Development Study of 1,037 New Zealand children, Terrie Moffit, Avshalom Caspi, Phil Silva and their colleagues found clear evidence that the temporal stability of delinquency was attributable to roughly 5% of the youth whose behavior was most persistent. We have similarly found in our 7-year follow-up study of 667 boys in the child welfare system that had been flagged for sexually inappropriate and coercive behaviors that the same power-law distribution was evident, with 3.6% of the youth persisting with further sexual, victim-involved offenses during a 7-year follow-up (Prentky et al, 2009; Prentky et al, 2010). This “severe 5%” has been generally defined by their engagement in a variety of externalizing behaviors, greater internalizing, poorer grades in school, and less parental oversight, as compared to children and adolescents outside of this group (Vaughn et al, 2014).…”

Section: Discussionsupporting

confidence: 59%

Retrospective Study of Fire Setting Among Boys in a Child Welfare Sample

Brereton

Lamade

Lee

et al. 2020

Youth Violence and Juvenile Justice

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This study aimed to assess fire-setting behaviors within a child welfare sample. The youth were divided into four groups based on their fire-setting behavior (e.g., no incidents, one incident, multiple minor incidents, and multiple severe incidents). Groups were compared based on five factors: overt antisocial behavior, covert antisocial behavior, global adjustment, psychiatric history, and learning deficits. Fire setters displayed more delinquent behavior and had more extensive psychiatric histories than non-fire-setting youth. Further, the youth with multiple serious incidents of fire-setting behavior displayed more delinquent behavior and had more extensive psychiatric histories than any of the fire-setting groups. These findings clearly suggest that fire setters, as a group, are not homogeneous with respect to antisocial behavior or psychiatric impairment and that gravity of fire setting increased as a function of greater psychopathology and greater delinquency when compared to their peers.

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Section: Discussionsupporting

confidence: 59%

Retrospective Study of Fire Setting Among Boys in a Child Welfare Sample

Brereton

Lamade

Lee

et al. 2020

Youth Violence and Juvenile Justice

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“…Age was not a factor in treatment effectiveness, which was an intriguing discovery. One study had shown that personality development was a significant factor in the rate of recidivism and the presence of empathy (Prentky et al, 2009). Thus, it was anticipated that this would impact treatment effectiveness on victim empathy within treatment groups.…”

Section: Discussionmentioning

confidence: 99%

Treatment Impact of an Integrated Sex Offender Program as Measured by J-SOAP-II

Rehfuss

Underwood

Enright

et al. 2013

Journal of Correctional Health Care

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Despite the increase in juvenile sex offending in society and the significant growth in the number of treatment programs, relatively few studies have examined the effectiveness of these programs. This study examined the effectiveness of an integrated sex offender program on a sample of 309 adjudicated male sex offenders in a juvenile correctional facility using the dynamic scale score of the Juvenile Sex Offender Assessment Protocol II (J-SOAP-II). The youth participated in one of the three treatment groups characterized by length of treatment and risk of recidivism: low risk (0 to 9 months), moderate risk (9 to 23 months), and high risk (23 to 56 months). A significant decrease in the dynamic scale scores of the J-SOAP-II was found only for the moderate treatment group (9 to 23 months).

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“…Of those screened in, 33 were included. Nine cases were excluded because they were identical or overlapping with other studies, such as when a conference presentation was later published as an article (Aebi & Bessler, 2010;Dahle, Janka, Gallasch-Nemitz, & Lehmann, 2008;Martinez, Rosenfeld, & Flores, 2004;Parks, 2004;Prentky, 2006;Prentky, Pimental, Cavanaugh, & Righthand, 2009;Ralston & Epperson, 2007;Viljoen, Elkovitch, Bader, Scalora, & Ullman, 2008). In these instances, only the most recent and/or comprehensive version of the study was included.…”

Section: Methodsmentioning

confidence: 99%

“…The aggregated correlations and AUCs for the J-SOAP-II total score decreased somewhat but remained significant (r = .19 to .17, p's < .01; AUC = .67 to .66), indicating that the inclusion of this study would not have changed the findings to non-significant. Second, because the study conducted by Prentky et al (2009) was classified as an outlier (zscore > 5.00) the results were re-run excluding this study. The aggregated correlations and AUCs for the J-SOAP-II total score decreased somewhat but the aggregated correlation remain significant (r = .19 to .15, p's < .001; AUC = .67 to .65).…”

Section: Sexual Reoffendingmentioning

confidence: 99%

Prediction of adolescent sexual reoffending: A meta-analysis of the J-SOAP-II, ERASOR, J-SORRAT-II, and Static-99.

Viljoen

Mordell

Beneteau

2012

Law and Human Behavior

103

121

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Several risk assessment tools, including the Juvenile Sex Offender Assessment Protocol-II (Prentky & Righthand, 2003), the Estimate of Risk of Adolescent Sexual Offense Recidivism (Worling & Curwen, 2001), the Juvenile Sexual Offense Recidivism Risk Assessment Tool-II (Epperson, Ralston, Fowers, DeWitt, & Gore, 2006), and the Static-99 (Hanson & Thornton, 1999), have been used to assess reoffense risk among adolescents who have committed sexual offenses. Given that research on these tools has yielded somewhat mixed results, we empirically synthesized 33 published and unpublished studies involving 6,196 male adolescents who had committed a sexual offense. We conducted two separate meta-analyses, first with correlations and then with areas under the receiver operating characteristic curve (AUCs). Total scores on each of the tools significantly predicted sexual reoffending, with aggregated correlations ranging from .12 to .20 and aggregated AUC scores ranging from .64 to .67. However, in many cases heterogeneity across studies was moderate to high. There were no significant differences between tools, and although the Static-99 was developed for adults, it achieved similar results as the adolescent tools. Results are compared to other meta-analyses of risk tools used in the area of violence risk assessment and in other fields.

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Predicting Risk of Sexual Recidivism in Juveniles: Predictive Validity of the J‐SOAP‐II

Cited by 9 publications

References 73 publications

Retrospective Study of Fire Setting Among Boys in a Child Welfare Sample

Retrospective Study of Fire Setting Among Boys in a Child Welfare Sample

Treatment Impact of an Integrated Sex Offender Program as Measured by J-SOAP-II

Prediction of adolescent sexual reoffending: A meta-analysis of the J-SOAP-II, ERASOR, J-SORRAT-II, and Static-99.

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