Treatment of Sex Offenders

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R.J.B. Lehmann et al.
these constructs. In a first step Lehmann and colleagues were able to demonstrate
the construct validity of the behavioral themes through correlational analyses with
known sexual offending measures, criminal histories, offenders’ motivation, and
offense characteristics. For stranger rapists (Lehmann, Goodwill, Gallasch-Nemitz,
Biedermann, & Dahle, 2013 ), the analyses revealed three behavioral offender propensities:
sexuality, criminality, and hostility. Statistical analyses indicated that the
behavioral theme of criminality significantly predicted sexual recidivism
(AUC = 0.64) and added incrementally to Static-99. For acquaintance rapists
(Lehmann, Goodwill, Hanson, & Dahle, 2015 ), results indicated that the behavioral
themes of hostility (AUC = 0.66) and pseudo-intimacy (AUC = 0.69) predicted sexual
recidivism, with the latter adding incrementally to Static-99. For child molesters
(Lehmann, Goodwill, Hanson, & Dahle, 2014 ), the behavioral themes of fixation on
child victims (AUC = 0.65) and (sexualized) aggression (AUC = 0.59) significantly
predicted sexual recidivism and added incrementally to Static-99. Recently, the predictive
validity of the behavioral theme of fixation was cross validated with an independent
sample (Pedneault, 2014 ). In sum, the results indicate that crime scene
information can be used to assess risk-relevant constructs. Also, crime scene information
seems to be relevant external information to the results of actuarial scales.
What Types of Information Can Actuarial
Risk Scales Provide?
Risk assessment can include static, dynamic, protective, or crime scene behavior
factors as indicators of risk-relevant propensities. Regardless of what types of risk
factors are used, how they are combined, or how accurate the scale is, appropriately
reporting risk assessment results make little difference if the decision makers do not
understand the information, which is a serious possibility (e.g., Varela, Boccaccini,
Cuervo, Murrie, & Clark, 2014 ). Consequently, there have been essential developments
in actuarial risk assessment research regarding optimal ways to report and
interpret risk assessment information in clinical practice (for a review, see Hilton,
Scurich, and Helmus, 2015 ). Hence, an important advantage of actuarial risk assessment
instruments is that they allow their scores to be linked to different types of
empirically derived quantitative indicators of risk. In contrast, other approaches to
risk assessment (e.g., SPJ) solely provide nominal risk categories (e.g., low, moderate,
and high risk) 1 with research indicating that nominal risk categories are interpreted
inconsistently by professionals (Hilton, Carter, Harris, & Sharpe, 2008 ;
Monahan & Silver, 2003 ). Three important metrics for risk communication are percentile
ranks, risk ratios, and absolute recidivism rates.
1
The only exception we are aware of is that the Spousal Assault Risk Assessment guide (SARA)
includes percentile distributions for the total scores and number of risk factors present, although
not for the overall summary judgment (Kropp & Gibas, 2010 ).