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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

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Risk assessment of sexual offenders

Risk Assessment of Sexual Offenders

Mr Steven M Wright

University of South Australia

 2001


Why the current emphasis

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

Legal obligations / Ethical concerns

Sexual predator legislation (United States)

Duty to warn/protect


Risk assessment objectives hart 2001

Risk Assessment Objectives(Hart, 2001)

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.


Recidivism risk factors hanson 2000

Recidivism risk factors (Hanson, 2000)

Static – historical and unchangeable

age, criminal history, demographic characteristics

Dynamic predictors

Stable dynamic (sexual preferences, cognitive distortions)

Acute dynamic (intoxication, emotional states)


Sexual offense recidivism

Sexual offense recidivism

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.


Risk assessment of sexual offenders

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.


Risk assessment of sexual offenders

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).


Risk assessment of sexual offenders

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.


Statistical methods of describing and quantifying the accuracy of risk predictions

Statistical Methods of describing and quantifying the accuracy of risk predictions

Correlations

ROC – AUCs (receiver operating characteristic analysis)


Sex offender risk assessment measures campbell 2000

Sex Offender Risk Assessment Measures (Campbell, 2000) accuracy of risk predictions

Professional judgement

Unstructured or clinical

Structured

Actuarial decision making

Clinically Adjusted Actuarial Prediction

Multifactorial approaches and classification trees (to come)


Risk assessment of sexual offenders

Professional judgement accuracy of risk predictionsMost commonly used method for violence risk assessmentFlexible, requires limited training and resources

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)


Svr 20 boer hart kropp webster 1997

SVR-20 accuracy of risk predictions(Boer, Hart, Kropp & Webster, 1997)

20 standard risk factors

Three main areas Psychosocial adjustment

Sexual offending

Future plans

Rate as ‘present’, ‘possibly present’ or ‘not present’

Translate into ‘low’, ‘moderate’, or ‘high’ risk categories


Sample conclusion

Sample Conclusion accuracy of risk predictions

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.


Correlations roc aucs hart 2000

Correlations/ ROC – AUCs accuracy of risk predictionsHart (2000)

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*


The svr 20 1998 can be purchased from psychological assessment resources
The SVR-20 (1998) can be purchased accuracy of risk predictions from Psychological Assessment Resources :

  • www.parinc.com/


Actuarial devices

Actuarial devices accuracy of risk predictions

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)

Highly structured/systematic

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)


Rapid risk assessment of sexual recidivism rrasor hanson 1997

Rapid Risk Assessment of Sexual Recidivism accuracy of risk predictions(RRASOR; Hanson, 1997)

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)

Victim gender

Relationship to victim


Rrasor summary

RRASOR: Summary accuracy of risk predictions

No manual

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


The rrasor 1997 is available to download from
The RRASOR (1997) is available to download from: accuracy of risk predictions

  • http://www.sgc.gc.ca/epub/corr/e199704/e199704.htm


Sex offender risk appraisal guide sorag quinsey et al 1998

Sex Offender Risk Appraisal Guide accuracy of risk predictions(SORAG; Quinsey et al, 1998)

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)


Sorag 1998 items

SORAG (1998) Items accuracy of risk predictions

Living with biological parents until age 16

Elementary school maladjustment

History of alcohol problems

Marital status

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

PCL-R score


Risk assessment of sexual offenders

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)

No manual.

Lack of peer reviewed support.

ROC-AUCs

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


Risk assessment of sexual offenders

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


Minnesota sex offender screening tool revised mnsost r epperson kaul hesselton 1998

Minnesota Sex Offender Screening Tool - Revised accuracy of risk predictions(MnSOST-R; Epperson, Kaul & Hesselton, (1998)

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.


Risk assessment of sexual offenders

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


The mnsost r 1998 can be downloaded from
The MnSOST-R (1998) accuracy of risk predictionscan be downloaded from:

  • http://psych-server.iastate.edu/faculty/epperson/mnsost_download.htm


Static 99 hanson thornton 1999

Static-99 accuracy of risk predictions(Hanson & Thornton, 1999)

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.


Static 99 hanson thornton 1999 items

Static-99 (Hanson & Thornton, 1999) Items accuracy of risk predictions

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

Young

Single


The static 99 can be downloaded from
The STATIC-99 accuracy of risk predictionscan be downloaded from:

  • http://www.sgc.gc.ca/epub/corr/e199902/e199902.htm


Clinically adjusted actuarial prediction

Clinically Adjusted Actuarial Prediction accuracy of risk predictions

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.


Latest research predictive accuracy correlations roc aucs barbaree seto langton peacock 2001
Latest research accuracy of risk predictionsPredictive accuracy (Correlations/ROC - AUCs)Barbaree, Seto, Langton & Peacock (2001)

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.


Conclusions

Conclusions accuracy of risk predictions

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


References

References accuracy of risk predictions

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.


Risk assessment of sexual offenders

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.


Risk assessment of sexual offenders

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


Risk assessment of sexual offenders

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


Risk assessment of sexual offenders

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