Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-586b7cd67f-2brh9 Total loading time: 0 Render date: 2024-11-30T19:51:43.455Z Has data issue: false hasContentIssue false

3.8 - Risk and Dangerousness in Adults

from Part III - Assessment

Published online by Cambridge University Press:  02 December 2021

By
Martin Rettenberger ,
Grant T. Harris ,
Marnie E. Rice  and
Reinhard Eher
Edited by
Jennifer M. Brown  and
Miranda A. H. Horvath
Jennifer M. Brown
Affiliation:
London School of Economics and Political Science
Miranda A. H. Horvath
Affiliation:
University of Suffolk
Get access

Summary

In order to assess the recidivism risk of adults who have been convicted of violent and/or sexual offenses, there exist two kinds of formal assessments: an actuarial risk assessment approach and a nonactuarial approach which is usually called “structured professional judgment” (SPJ). The actuarial risk assessment approach could be further divided into risk assessment instruments which are using predominantly static (i.e., biographical, criminological, and unchangeable) or dynamic (i.e., changeable by, for example, treatment-related processes) risk factors. The SPJ approach is a research-based professional guideline approach to decision-making which provides bench marks for integrating information from a broad range of risk factors associated with recidivism. These instruments are based on considerations of the relevant scientific, professional, and legal literature. The present chapter provides an overview about the main characteristics of both risk assessment approaches as well as about the internationally most commonly used and best validated actuarial and SPJ instruments.

Keywords

RiskRisk AssessmentViolent OffensesSexual OffensesRecidivism
Type
Chapter
Information
The Cambridge Handbook of Forensic Psychology , pp. 474 - 490
Publisher: Cambridge University Press
Print publication year: 2021

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Ægisdóttir, S., White, M. J., Spengler, P. M., Maugherman, A. S., Anderson, L. A., Cook, R. S., Nichols, C. N., Lampropoulos, G. K., Walkers, B. S., Cohen, G., & Rush, J. 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.Google Scholar
Allan, A., Dawson, D., & Allan, M. M. (2006). Prediction of the risk of male sexual reoffending in Australia. Australian Psychologist, 41(1), 60–68.CrossRefGoogle Scholar
Andrews, D. A., & Bonta, J. (2010). The psychology of criminal conduct (5th ed.). Cincinnati, OH: Anderson.Google Scholar
Babchishin, K.M, Hanson, R.K., & Helmus, L. (2012). Even highly correlated measures can add incrementally to predicting recidivism among sex offenders. Assessment, 19(4), 442–461.Google Scholar
Baltieri, D. A., & de Andrade, A. G. (2008). Comparing serial and nonserial sexual offenders: Alcohol and street drug consumption, impulsiveness and history of sexual abuse. Revista Brasileira de Psiquiatria, 30(1), 25–31.CrossRefGoogle ScholarPubMed
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 and Behavior, 28(4), 490–521.CrossRefGoogle Scholar
Beggs, S. M., & Grace, R. C. (2010). Assessment of dynamic risk factors: An independent validation study of the Violence Risk Scale: Sexual Offender Version. Sexual Abuse: Journal of Research and Treatment, 22(2), 234–251.Google Scholar
Bengtson, S. (2008). Is new better? A cross-validation of the Static-2002 and the Risk Matrix 2000 in a Danish sample of sexual offenders. Psychology, Crime & Law, 14(2), 85–106.Google Scholar
Boer, D. P., & Hart, S. D. (2009). Sex Offender Risk Assessment: Research, Evaluation, ‘Best-practice’ Recommendations and Future Directions. In Ireland, J. L., Ireland, C. A. & Birch, P. (Eds.), Violent and sexual offenders: Assessment, treatment, and management (pp. 27–42). Cullompton: Willan Publishing.Google Scholar
Boer, D. P., Hart, S. D., Kropp, P. R., & Webster, C. D. (1997). Manual for the Sexual Violence Risk – 20: Professional guidelines for assessing risk of sexual violence. Vancouver, BC: Mental Health, Law, & Policy Institute, Simon Fraser University. Vancouver, British Columbia, Canada: Proactive Resolutions.Google Scholar
Boer, D. P., Hart, S. D., Kropp, P. R., & Webster, C. D. (2017). Manual for version 2 of the Sexual Violence Risk-20 (SVR-20 V2): Structured Professional Judgment guidelines for assessing and managing risk of sexual violence. Vancouver, BC: Mental Health, Law, & Policy Institute, Simon Fraser University.Google Scholar
Bonta, J., Law, M., & Hanson, K. (1998). The prediction of criminal and violent recidivism among mentally disordered offenders: A meta-analysis. Psychological Bulletin, 123(2), 123–142.CrossRefGoogle ScholarPubMed
Cohen, J. (1992). A power primer. Psychological Bulletin, 112(1), 155–159.Google Scholar
Cortoni, F., Hanson, R. K., & Choache, M.-E. (2010). The recidivism rates of female sexual offenders are low: A meta-analysis. Sexual Abuse: A Journal of Research and Treatment, 22(4), 387–401.CrossRefGoogle ScholarPubMed
Craig, L. A., & Beech, A. R. (2010). Towards a guide to best practice in conducting actuarial risk assessments with sex offenders. Aggression and Violent Behavior, 15(4), 278–293.CrossRefGoogle Scholar
Craig, L. A., Beech, A. R., & Browne, K. D. (2006). Cross-validation of the Risk Matrix 2000 Sexual and Violent scales. Journal of Interpersonal Violence, 21(5), 612–633.Google Scholar
Craig, L. A., & Rettenberger, M. (2016). The Wiley-Blackwell handbook on the theories, assessment, and treatment of sexual offending – volume II: Assessment. Chichester, UK: Wiley-Blackwell.Google Scholar
Dawes, R. M., Faust, D., & Meehl, P. E. (1989). Clinical versus actuarial judgement. Science, 243(4899), 1668–1674.Google Scholar
de Vogel, V., de Ruiter, C., van Beek, D., & Mead, G. (2004). Predictive validity of the SVR-20 and Static-99 in a Dutch sample of treated sex offenders. Law and Human Behavior, 28(3), 235–251.Google Scholar
Douglas, K. S., Hart, S. D., Webster, C. D., & Belfrge, H. (2013). HCR-20V3: Assessing risk for violence – user’s guide. Burnaby, Canada: Department of Psychology, Simon Fraser University.Google Scholar
Douglas, K. S., Ogloff, J. R. P., & Hart, S. D. (2003). Evaluation of a model of violence risk assessment among forensic psychiatric patients. Psychiatric Services, 54(10), 1372–1379.CrossRefGoogle Scholar
Ducro, C., & Pham, T. (2006). Evaluation of the SORAG and the Static-99 on Belgian sex offenders committed to a forensic facility. Sexual Abuse: A Journal of Research and Treatment, 18(1), 15–26.CrossRefGoogle ScholarPubMed
Eher, R., Matthes, A., Schilling, F. Haubner-MacLean, T., & Rettenberger, M. (2012). Dynamic risk assessment in sexual offenders using STABLE-2000 and the STABLE-2007: An investigation of predictive and incremental validity. Sexual Abuse: A Journal of Research and Treatment, 24(1), 5–28.Google Scholar
Eher, R., Olver, M. E., Heurix, I., Schilling, F., & Rettenberger, M. (2015). Predicting reoffense in pedophilic child molesters by clinical diagnoses and risk assessment. Law and Human Behavior, 39(6), 571–580.CrossRefGoogle ScholarPubMed
Eisenbarth, H., Osterheider, M., Nedopil, N., & Stadtland, C. (2012). Recidivism in female offenders: PCL-R lifestyle factor and VRAG show predictive validity in a German sample. Behavioral Sciences and the Law, 30(5), 575–584.Google Scholar
Etzler, S., Eher, R., & Rettenberger, M. (2018). Dynamic risk assessment of sexual offenders: Validity and dimensional structure of the Stable-2007. Assessment. Advance online publication. 10.1177/1073191118754705Google Scholar
Glover, A. J. J., Churcher, F. P., Gray, A. L., Mills, J. F., & Nicholson, D. E. (2017). A crossvalidation of the Violence Risk Appraisal Guide—Revised (VRAG-R) within a correctional sample. Law and Human Behavior, 41(6), 507–518.Google Scholar
Gray, N. S., Fitzgerald, S., Taylor, J., MacCulloch, M. J., & Snowden, R. J. (2007). Predicting future reconviction in offenders with intellectual disabilities: The predictive efficacy of VRAG, PCL-SV, and the HCR-20. Psychological Assessment, 19(4), 474–479.Google Scholar
Gregório Hertz, P., Eher, R., Etzler, S., & Rettenberger, M. (2019). Cross-validation of the revised version of the Violence Risk Appraisal Guide (VRAG-R) in a sample of individuals convicted of sexual offences. Sexual Abuse. Advance online publication. https://doi.org/10.1177/1079063219841901CrossRefGoogle Scholar
Grove, W. M., & Meehl, P. E. (1996). Comparative efficiency of informal (subjective, impressionistic) and formal (mechanical, algorithmic) prediction procedures: The clinical—statistical controversy. Psychology, Public Policy, and Law, 2(2), 293–323.Google Scholar
Grove, W. M., Zald, D. H., Lebow, B. S., Snitz, B. E., & Nelson, C. (2000). Clinical versus mechanical prediction: A meta-analysis. Psychological Assessment, 12(1), 19–30.Google Scholar
Hanson, R. K. (2009). The psychological assessment of risk for crime and violence. Canadian Psychology, 50(3), 172–182.Google Scholar
Hanson, R. K., & Harris, A. J. R. (2000). Where should we intervene? Dynamic predictors of sexual offence recidivism. Criminal Justice and Behavior, 27(1), 6–35.Google Scholar
Hanson, R. K., Harris, A. J. R., Helmus, L., & Thornton, D. (2014). High risk sex offenders may not be high risk forever. Journal of Interpersonal Violence, 29(15), 2792–2813.Google Scholar
Hanson, R. K., Harris, A. J. R, Scott, T. L., & Helmus, L. (2007). Assessing the risk of sexual offenders on community supervision: The Dynamic Supervision Project (Corrections research user report 2007-05). Ottawa, Ontario: Public Safety Canada. Retrieved from http://www.publicsafety.gc.ca/res/cor/rep/_fl/crp2007-05-en.pdfGoogle Scholar
Hanson, R. K., Helmus, M.-L., & Harris, A. J. R. (2015). Assessing the risk and needs of supervised sexual offenders: A prospective study using STABLE-2007, Static-99R, and Static-2002R. Criminal Justice and Behavior, 42(12), 1205–1224.CrossRefGoogle Scholar
Hanson, R. K., & Morton-Bourgon, K. (2007). The accuracy of recidivism risk assessment for sexual offenders: A meta-analysis (Corrections Research User Report No. 2007-01). Ottawa: Public Safety Canada.Google Scholar
Hanson, R. K., & Morton-Bourgon, K. (2009). The accuracy of recidivism risk assessments for sexual offenders: A meta-analysis of 118 prediction studies. Psychological Assessment, 21, 1–21.Google Scholar
Hanson, R. K., Sheahan, C. L., & van Zuylen, H. (2013). STATIC-99 and RRASOR predict recidivism among developmentally delayed sexual offenders: A cumulative meta-analysis. Sexual Offender Treatment, 8(1), 1–14. Retrieved from www.sexual-offender-treatment.org/index.php?id=119&type=123Google Scholar
Hanson, R. K., & Thornton, D. (2000). Improving risk assessment for sex offenders: A comparison of three actuarial scales. Law and Human Behavior, 24(1), 119–136. https://doi.org/10.1023/A:1005482921333CrossRefGoogle ScholarPubMed
Harris, G. T., Rice, M. E., & Quinsey, V. L. (1993). Violent recidivism of mentally disordered offenders: The development of a statistical prediction instrument. Criminal Justice and Behavior, 20(4), 315–335.Google Scholar
Harris, G. T., Rice, M. E., Quinsey, V. L., & Cormier, C. A. (2015). Violent offenders: Appraising and managing risk (3rd ed.). Washington, DC: American Psychological Association.Google Scholar
Harris, G. T., Rice, M. E., Quinsey, V. L., Lalumière, M. L., Boer, D., & Lang, C. (2003). A multisite comparison of actuarial risk instruments for sex offenders. Psychological Assessment, 15(3), 413–425.Google Scholar
Hart, S. D., & Boer, D. P. (2010). Structured Professional Judgement guidelines for sexual violence risk assessment: The Sexual Violence Risk-20 (SVR-20) and Risk for Sexual Violence Protocol (RSVP). In Otto, R. K. & Douglas, K. S. (Eds.). Handbook of violence risk assessment (pp. 269–294). Oxford: Routledge.Google Scholar
Helmus, L., Hanson, R. K., Thornton, D., Babchishin, K. M., & Harris, A. J. R. (2012). Absolute recidivism rates predicted by Static-99R and Static-2002R sex offender risk assessment tools vary across samples: A meta-analysis. Criminal Justice and Behavior, 33, 1148–1171.Google Scholar
Helmus, L., Thornton, D., Hanson, R. K., & Babchishin, K. M. (2012). Improving the predictive accuracy of Static-99 and Static-2002 with older sex offenders: Revised age weights. Sexual Abuse: A Journal of Research and Treatment, 24(1), 64–101.Google Scholar
Hilton, N. Z., Carter, A. M., Harris, G. T., & Sharpe, A. J. B. (2008a). Does using non-numerical terms to describe risk aid violence risk communication? Clinician agreement and decision-making. Journal of Interpersonal Violence, 23(2), 171–188.Google Scholar
Hilton, N. Z., Harris, G. T., Rice, M. E., Houghton, R. E., & Eke, A. W. (2008b). An indepth actuarial assessment for wife assault recidivism: The Domestic Violence Risk Appraisal Guide. Law and Human Behavior, 32(2), 150–163.Google Scholar
Hilton, N. Z., Harris, G. T., & Rice, M. E. (2006). Sixty-six years of research on the clinical versus actuarial prediction of violence. The Counseling Psychologist, 34(3), 400–409.Google Scholar
Hill, A., Rettenberger, M., Habermann, N., Berner, W., Eher, R., & Briken, P. (2012). The utility of risk assessment instruments for the prediction of recidivism in sexual homicide perpetrators. Journal of Interpersonal Violence, 27(18), 3553–3578.CrossRefGoogle ScholarPubMed
Klein, V., Rettenberger, M., Yoon, D., Köhler, N., & Briken, P. (2015). Protective factors and recidivism in accused juveniles who sexually offended. Sexual Abuse: A Journal of Research and Treatment, 27(1), 71–90.Google Scholar
Kropp, P. R., & Hart, S. D. (2015). SARA-V3: User manual for version 3 of the Spousal Assault Risk Assessment Guide. Vancouver, British Columbia, Canada: Proactive Resolutions.Google Scholar
Kropp, P. R., Hart, S. D., Webster, C. D., & Eaves, D. (1999). Spousal Assault Risk Assessment Guide (SARA). Toronto, Ontario, Canada: Multi-Health Systems.Google Scholar
Mann, R. E., Hanson, R. K., & Thornton, D. (2010). Assessing risk for sexual recidivism: Some proposals on the nature of psychologically meaningful risk factors. Sexual Abuse: A Journal of Research and Treatment, 22(2), 191–217.Google Scholar
Marshall, W. L. (2006). Clinical and research limitations in the use of phallometric testing with sexual offenders. Sexual Offender Treatment, 1(1), 1–19. Retrieved from http://sexual-offender-treatment.org/index.php?id=18&type=123Google Scholar
Meehl, P. E. (1954). Clinical versus statistical prediction: A theoretical analysis and a review of the evidence. Minneapolis: University of Minnesota Press.CrossRefGoogle Scholar
Murrie, D. C., Boccaccini, M. T., Guarnera, L. A., & Rufino, K. (2013). Are forensic experts biased by the side that retained them? Psychological Science, 24(10), 1889–1897.Google Scholar
Neal, T. M. S., & Grisso, T. (2014). The cognitive underpinnings of bias in forensic mental health evaluations. Psychology, Public Policy, and Law, 20(2), 200–211.CrossRefGoogle Scholar
Olver, M. E., & Sewall, L. (2018). Cross-validation of the discrimination and calibration properties of the VRAG-R in a treated sexual offender sample. Criminal Justice and Behavior, 45(6), 741–761.Google Scholar
Olver, M. E., Wong, S. C., Nicholaichuk, T., & Gordon, A. (2007). The validity and reliability of the Violence Risk Scale-Sexual Offender version: Assessing sex offender risk and evaluating therapeutic change. Psychological Assessment, 19(3), 318–329.CrossRefGoogle ScholarPubMed
Otto, R. K., & Douglas, K. S. (2010). Handbook of violence risk assessment. Oxford, UK: Routledge/Taylor & Francis.Google Scholar
Quinsey, V.L., Harris, G.T., Rice, M.E., & Cormier, C.A. (2006). Violent offenders: Appraising and managing risk (2nd ed.). Washington, DC: American Psychological Association.Google Scholar
Rettenberger, M., & Craig, L. A. (2016). Actuarial risk assessment of sexual offenders. In Craig, L. A. & Rettenberger, M. (Eds.), The Wiley-Blackwell handbook on the theories, assessment, and treatment of sexual offending – Volume II: Assessment (pp. 609–641). Chichester, UK: Wiley-Blackwell.Google Scholar
Rettenberger, M., & Eher, R. (2013). Actuarial risk assessment in sexually motivated intimate-partner violence. Law and Human Behavior, 37(2), 75–86.CrossRefGoogle ScholarPubMed
Rettenberger, M., Haubner-MacLean, T., & Eher, R. (2013). The contribution of age to the Static-99 risk assessment in a population-based prison sample of sexual offenders. Criminal Justice and Behavior, 40(12), 1413–1433.Google Scholar
Rettenberger, M. Matthes, A., Boer, D. P., & Eher, R. (2010). Actuarial recidivism risk assessment and sexual delinquency: A comparison of five risk assessment tools in different sexual offender subtypes. International Journal of Offender Therapy and Comparative Criminology, 54, 169–186.CrossRefGoogle Scholar
Rettenberger, M., Rice, M. E., Harris, G. T., & Eher, R. (2017). Actuarial risk assessment of sexual offenders: The psychometric properties of the Sex Offender Risk Appraisal Guide (SORAG). Psychological Assessment, 29(6), 624–638.Google Scholar
Rice, M. E., & Harris, G. T. (1995). Violent recidivism: Assessing predictive validity. Journal of Consulting and Clinical Psychology, 63(5), 737–748.Google Scholar
Rice, M. E., & Harris, G. T. (2005). Comparing effect sizes in follow-up studies: ROC, Cohen’s d and r. Law and Human Behavior, 29(5), 615–620.Google Scholar
Rice, M. E., Harris, G. T., & Hilton, N. Z. (2010). The Violence Risk Appraisal Guide and Sex Offender Risk Appraisal Guide for violence risk assessment and the Ontario Domestic Assault Risk Assessment and Domestic Violence Risk Appraisal Guide for wife assault risk assessment. In Otto, R. & Douglas, K. (Eds.), Handbook of violence risk assessment tools (pp. 99–119). Oxford, UK: Routledge/Taylor & Francis.Google Scholar
Rice, M. E., Harris, G. T., & Lang, C. (2013). Validation of and revision to the VRAG and SORAG: The Violence Risk Appraisal Guide-Revised (VRAG-R). Psychological Assessment, 25(3), 951–965.CrossRefGoogle Scholar
Schwalbe, C. S., Fraser, M. W., Day, S. H., & Cooley, V. (2006). Classifying juvenile offenders according to risk of recidivism: Predictive validity, race/ethnicity, and gender. Criminal Justice and Behavior, 33(3), 305–324.Google Scholar
Scurich, N., & John, R. S. (2011). The effect of framing actuarial risk probabilities on involuntary civil commitment decisions. Law and Human Behavior, 35(2), 83-91.CrossRefGoogle ScholarPubMed
Singer, J. C., Boer, D. P., & Rettenberger, M. (2013). A convergent approach to sex offender risk assessment. In Harrison, K. & Rainey, B. (Hrsg.), The Wiley-Blackwell handbook of legal and ethical aspects of sex offender treatment and management (pp. 341–355). New York: Wiley.Google Scholar
Singh, J. P., Bjørkly, S., & Fazel, S. (2016). International perspectives on violence risk assessment. New York, USA: Oxford University Press.Google Scholar
Sjöstedt, G., & Långstrom, N. (2001). Actuarial assessment of sex offender recidivism risk: A crossvalidation of the RRASOR and the Static-99 in Sweden. Law and Human Behavior, 25(6), 629–645.Google Scholar
Skelton, A., Riley, D., Wales, D., & Vess, J. (2006). Assessing risk for sexual offenders in New Zealand: Development and validation of a computer-scored risk measure. Journal of Sexual Aggression, 12(3), 277–286.Google Scholar
Webster, C. D., Eaves, D., Douglas, K. S., & Wintrup, A. (1995). The HCR-20 Scheme: The assessment of dangerousness and risk. Vancouver: Simon Fraser University and British Columbia Forensic Psychiatric Services Commission.Google Scholar
Wong, S. C., & Gordon, A. (2009). Manual for the Violence Risk Scale (VRS). Saskatoon: University of Saskatchewan.Google Scholar
Yang, M., Wong, S. C., & Coid, J. (2010). The efficacy of violence prediction: A meta-analytic comparison of nine risk assessment tools. Psychological Bulletin, 136(5), 740–767.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure [email protected] is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×