Risk Assessment of Sexual Offenders. Mr Steven M Wright University of South Australia 2001. Why the current emphasis ?. Media reporting Political pressures community notification; Megan’s Law (USA); Sarah’s Law (UK) Guide Intervention– who and what to target
Mr Steven M Wright
University of South Australia
community notification; Megan’s Law (USA); Sarah’s Law (UK)
Guide Intervention– who and what to target
Legal obligations / Ethical concerns
Sexual predator legislation (United States)
Duty to warn/protect
We never know an individual’s risk for violence; we merely estimate it assuming various conditions.
Evaluations of individuals to
(a) Characterise the risk that they will commit violence in the future, and
(b) Develop interventions to manage or reduce that risk
The task is to understand the factors associated with how and why individuals chose to offend in the past, and to determine whether these or other factors might lead the individual to make similar choices in the future.
Static – historical and unchangeable
age, criminal history, demographic characteristics
Stable dynamic (sexual preferences, cognitive distortions)
Acute dynamic (intoxication, emotional states)
Although there is a rich clinical literature on sexual offenders, there has been relatively little work on assessing sexual violence risk among sexual offenders, particulary with regard to sexual-reoffending.
Hanson & Bussiere (1998) meta-analysis of the scientific literature (28,972 offenders) highlighted the importance of historical or static factors in sexual violence recidivism risk.
sexual deviance (phallometric assessment) Age (young)
prior sexual offences Never married
early onset of sexual offending Personality disorders
victim choices (family members<acquaintances<strangers)
failed to attend/dropped out of treatment
Concluded that recidivism rate for sexual violence low contrary to popular opinion. 13.4 percent of offenders committed a new sexual offense within the 4-5 year follow up period.
Among sexual offenders, non sexual recidivism was best predicted by the same variables that predict recidivism among nonsexual criminals (Andrews & Bonta, 1994). Often these offenders tended to be young, single and have antisocial/psychopathic personality disorders, and have a history of prior violent and nonviolent offenses. Factors not related to sexual offense recidivism included having a history of sexual abuse as a child, substance abuse and general psychological problems (anxiety, depression, low self-esteem etc.)It is suggested that whilst the extent to which sexual offenders are distressed does not predict recidivism, such offenders may react deviantly when distressed.
Hanson & Harris (2000) predicted by the same variables that predict recidivism among nonsexual criminals (Andrews & Bonta, 1994). Often these offenders tended to be young, single and have antisocial/psychopathic personality disorders, and have a history of prior violent and nonviolent offenses. Dynamic risk factors in sexual offendingThe purpose of this study was to identify factors that could be useful for officers supervising sexual offenders in the community. Overall, substantial differences were observed between the 208 sexual offenders who sexually recidivated while on community supervision and a comparison group of 201 non-recidivists. In comparison to the non-recidivists, the recidivists had a greater history of sexual deviance, such as diverse types of victims, stranger victims, juvenile offenses and paraphilias (e.g., exhibitionism, cross-dressing). As well, the recidivists showed more signs of an antisocial lifestyle than did the non-recidivists. The recidivists were more likely to meet criteria for antisocial personality, psychopathy (PCL-R), and had higher scores on objective risk scales (SIR and VRAG).
Officer interviews indicated that the recidivists displayed more problems while on supervision than did the non-recidivists. In particular, the recidivists were generally considered to have poor social supports, attitudes tolerant of sexual assault, antisocial behaviour, poor self-management strategies and difficulties cooperating with supervision as indicated by being disengaged, manipulative or absent. The overall mood of the recidivists and non-recidivists was similar, and each had equivalent levels of life stress and negative affect, but the recidivists tended to show an increase in anger and subjective distress just prior to re-offending. In other words, psychological symptoms appeared as acute, but not stable, risk factors. With rare exceptions, the same risk factors applied to both rapists and child molesters.
ROC – AUCs (receiver operating characteristic analysis)
Unstructured or clinical
Actuarial decision making
Clinically Adjusted Actuarial Prediction
Multifactorial approaches and classification trees (to come)
Un-structured based on idiosyncratic impressions
Poor predictive validity, unreliable and false positive bias
Predictive accuracy only slightly better than chance
(r=.10, Hanson & Bussiere, 1998)
Structured Imposes structure on evaluation
Must refer to at minimum a fixed and explicit set of risk factors. Combine ratings on such to guide
assessment of risk.
Sexual Violence Risk – 20
(SVR-20; Boer, Hart, Kropp & Webster, 1997)
Structured Risk Assessment – 99 (SRA-99; Thornton, 1999)
Matrix 2000 (Thornton, 2000)
20 standard risk factors
Three main areas Psychosocial adjustment
Rate as ‘present’, ‘possibly present’ or ‘not present’
Translate into ‘low’, ‘moderate’, or ‘high’ risk categories
Based on a comprehensive risk assessment, it is my opinion that should he be released into the community Mr Smith poses a high risk for sexual violence relative to other sex offenders incarcerated in the Correctional Service.
According to the available information, all of Mr Smith’s sexual offences have been paedophilic in nature, involving the non-coercive sexual contact of young boys with whom he was acquainted through casual contact. There is no information to lead me to believe that his offences will change in nature or escalate in severity in the near future.
Based on his past offences, if Mr Smith recidivates his victims are most likely to be boys between the ages of 6-12 years who live within a few miles of his residence. Given the long standing nature of Mr Smith’s paraphilia, its resistance to treatment, and his extensive history of sexual offending, the most effective way to manage his risk of sexual violence is through incapacitation, that is, by denying his request for parole. Should Mr Smith by released into the community, risk management strategies should focus on intensive supervision. Electronic monitoring, frequent meetings with a parole officer might be effective supervision strategies.
Any violence Sexual violence
r AUC r AUC
PCL-R .45* .76* .20 .69*
VRAG .56* .83* .26* .71*
SORAG .64* .88* .36* .77*
RRASOR .40* .73* .48* .77*
SVR-20 .52* .81* .31* .74*
Commonly-used adjunctive method for violence risk assessment
Utilise statistical techniques to generate risk predictors
Generally equal or superior to clinical judgement with respect to consistency (reliability) and accuracy (validity)
Objective – limited role of discretion, empirically based and ‘scientific’
Rapid Risk Assessment for Sexual Offense Recidivism
(RRASOR; Hanson, 1997)
Sexual Offence Risk Appraisal Guide
(SORAG; Quinsey, Harris, Rice & Cormier, 1998)
Minnesota Sex Offender Screening Tool (Revised)
(MnSOST-R; Epperson, Kaul & Huot, 1995)
Static – 99 (Hanson & Thornton, 1999)
4 item actuarial instrument rated from official records
Intended to be relatively brief screening instrument for predicting sexual offense recidivism
Based on meta-analytic research and re-analysis of existing data sets.
Items weighted according to ability to predict likelihood of recidivism over periods of 5-10 years. Total scores range from 0 – 6 with a 10 year estimated likelihood of recidivism ranging from 6.5 – 73.1 percent. Most offenders have scores which range between 1 and 4.
Items Prior sex offenses (not including index offenses)
Age at release (current age)
Relationship to victim
Minimal peer reviewed studies
Doesn’t consider deviant sexual preferences, personality, treatment compliance or other dynamic variables.
Insensitive to context, change
Utility in assessing post-treatment changes in risk status limited.
Potentially useful psychological instrument for establishing elevated risk of sexual violence
Good predictive accuracy in development and validation samples (Hanson & Thornton, 2000)
r= 0.27 AUC = 0.71 (Hanson, 1997) sexual recidivism
r= 0.22 AUC = 0.72 (Sjostedt & Langstron, 2000)
sexual recidivism 4 year follow up
Authors strongly pro-actuarial – based on Penetanguishene studies
Modification of the VRAG (Quinsey et al, 1998)
Do the findings generalise ?
‘the universe is homogenous with respect to forensic institutions’ (Quinsey et al, 1998)
14 item actuarial instrument, with range of scores from 1 – 9.
Includes both static and dynamic factors
At least four of the factors included in the items have received little empirical support (ie history of alcohol abuse; history of non-violent offenses; marital status; diagnosis of schizophrenia) (Campbell, 2000)
Living with biological parents until age 16
Elementary school maladjustment
History of alcohol problems
Nonviolent offense history
Violent offense history
Sexual offense history
Sex and age of index victim
Failure on prior conditional release
Age at index offense
DSM-III criteria for any personality disorder
DSM-III criteria for schizophrenia
Phallometrically measured deviant sexual interests
SORAG (1998): Summary accuracy of risk predictions
Likelihood of recidivism is estimated for only general violence
Restricted in clinical usage due to inclusion of PCL-R (training requirements)
Lack of peer reviewed support.
0.82 (Belanger & Earls, 1996) parole failure or recidivism of any kind.
0.63 (Firestone, Bradford, Greenberg, Nunes & Broom, 2001)
violent (including sexual) recidivism follow up 7 years
The SORAG (1998) is available in accuracy of risk predictionsQuinsey, V.L., Harris, G.T., Rice, M.E. & Cormier, C.A. (1998). Violent Offenders : Appraising and Managing Risk. The American Psychological Association:http://www.apa.org/books/431604A.html
16 item actuarial instrument, constructed applying retrospective methods
Incorporates both historical and institutional information (ie treatment participation).
Designed specifically to predict sexual recidivism (unlike the VRAG and SORAG)
Scores divided into 4 categories, with estimated recidivism rates from 16 – 88 percent over 6 years.
Correlations/ ROC – AUCs accuracy of risk predictions
More accurate at discriminating between sexual recidivists and non-recidivists than the RRASOR.
r = 0.45 0.77 AUC (Epperson et al, 1998)
sexual recidivism follow up 6 years
r = 0.35 0.73 AUC (Epperson et al, 2000)
sexual recidivism follow up 6 years
Actuarial instrument consisting of 10 items
Combination of items from 2 scales (RRASOR; Hanson, 1997) and Thornton’s Structured Anchored Clinical Judgement Scale (SAJC; Grubin, 1998)
Sample N = 1,301 (Canada & UK)
Moderate predictive accuracy for sexual recidivism (r=.33, AUC = .71) and violent (including sexual) recidivism (r=.32, AUC = .69).
Only small incremental improvements over the original two scales.
Reliance on static factors.
Prior sexual offences (same rules as in RRASOR)
Prior sentencing dates (number of distinct occasions on which the offender has been sentenced for criminal offences of any kind)
Any conviction for non-contact offences
Index non-sexual violence
Prior non-sexual violence
Any unrelated victims
Any stranger victims
Any male victims
Adjusting actuarial predictions either up or down depending on professional judgement
Structured Risk Assessment – 99 (SRA-99; Thornton, 1999)
Stepwise process including:
Initial classification of risk – Static-99
Consider offender’s functioning on dynamic risk factors to revise the original risk classification
Consider offender’s response to treatment
Consider offender’s typical offence pattern in association with situational factors
Reflects diversity of assessment domains.
Yet to be subject to systematic empirical evaluation.
VRAG, SORAG, RRASOR & Static-99 predicted general recidivism, serious (violent and sexual) recidivism, and sexual recidivism.
MnSOST-R predicted general recidivism but not serious or sexual recidivism,
PCL-R predicted general and serious recidivism but not sexual recidivism.
It is possible to predict sexually violent recidivism in sex offenders with moderate accuracy
Validity of structured professional judgements may equal that of actuarial instruments
Hanson, R.K. & Harris, A.J.R. (2001). A structured approach to evaluating change among sexual offenders. Sexual Abuse: Journal of Research and Treatment, 13(2): 105-122.
McCarthy, J. (2001). Risk assessment of sexual offenders. Psychiatry, Psychology & Law, 8(1): 56-64.
Hanson, R.K. & Thornton, D. (2000). Improving risk assessments for se offenders: A comparison of three actuarial scales. Law and Human Behavior, 24(1): 119-136.
Hanson, R.K. & Harris, A.J.R. (2000). Where should we intervene ? Dynamic predictors of sexual assault recidivism. Criminal Justice & Behavior, 27(1): 6-35.Hanson, R.K. & Bussiere, M.T. (1998). Predicting relapse: a meta-analysis of sexual offender recidivism studies. Journal of Consulting and Clinical Psychology, 66(2): 348.Barbaree, H.E., Seto, M.C., Langton, C.M. & Peacock, E.J. (2001). Evaluating the predictive accuracy of six risk assessment instruments for adult sex offenders. Criminal Justice & Behavior, 28(4): 490-521.
The Sex Offender Need Assessment Rating (SONAR): A Method for Measuring Change in Risk Levels2000-1By R. Karl Hanson & Andrew HarrisCorrections ResearchDepartment of the Solicitor General of Canadahttp://www.sgc.gc.ca/epub/corr/e200001a/e200001b/e200001b.htmThe Development of a Brief Actuarial Risk Scale for Sexual Offense Recidivism1997-04By R. Karl Hanson, Ph.D.Department of the Solicitor General of Canadahttp://www.sgc.gc.ca/epub/corr/e199704/e199704.htm
Static 99: Improving Actuarial Risk Assessments for Sex Offenders1999-02By R. Karl HansonDepartment of the Solicitor General of Canada, OttawaDavid ThorntonHer Majesty’s Prison Service, Londonhttp://www.sgc.gc.ca/epub/corr/e199902/e199902.htmDynamic Predictors Of Sexual Recidivism1998-1by R. Karl Hanson & Andrew HarrisCorrections ResearchDepartment of the Solicitor General Canadahttp://www.sgc.gc.ca/epub/corr/e199801b/e199801b.htm
Predictors of sexual offender recidivism: a meta-analysis Offenders1996-04By R. Karl Hanson & Monique T. BussièreCorrections ResearchDepartment of the Solicitor General Canadahttp://www.sgc.gc.ca/epub/corr/e199604/e199604.htm