Fact Sheet: Forensic Risk Assessment

 
About the fact-sheet series: Fact sheets summarize current literature into a short (2 page) document intended for distribution. Fact-sheets are extremely useful for academics, professionals or laypeople who are in contact with offenders, victims, corrections or the legal system in any way. They provide a means to disseminate empirically based information in a way that is both quick and useful.

About the author: This article was written by Julia Shaw, EAPL-S co-president and Ph.D. student at the University of British Columbia (Canada).

View this document in it's full glory by downloading the pdf here.

Remember to also read our article on "Can we predict offender risk?".

What is Risk Assessment?

Forensic risk assessment is concerned with calculating how likely it is that antisocial behavior or criminal offending will occur[1]. This question is most commonly posed when an individual has recently been found guilty of a crime, as authorities need to know how to appropriately deal with the individual. Psychologists, social workers or legal professionals conduct these assessments, and they form an important part of decisions regarding what kind of prison is most appropriate for an offender (e.g., maximum security), whether to release an offender (e.g., to parole), and what factors need to be targeted by interventions.

This fact-sheet is intended to aid those who deal with offenders by reviewing recent literature in the field, including tools used to assess risk, and risk factors for offending.

Research on Assessment Tools

There are three types of risk assessments: Actuarial, unstructured clinical and structured clinical judgment. Actuarial tools are lists of factors that have been statistically established to be related to offending. For example, because offenders who are younger are more likely to re-offend, age is often considered a statistically based risk factor. These kinds of tools can typically be administered by individuals with only minimal training, as they are often easy to do. Unstructured clinical judgment, on the other hand, relies on an expert’s ability to determine the risk of an individual based on personal experience and knowledge. Finally, structured clinical judgment is a combination of the two, by providing a guide of empirically based items that are recommended for a clinician to examine in-depth. According to large literature reviews, actuarial tools outperform structured clinical judgment, which in turn outperforms unstructured clinical judgment[2]. Unstructured clinical judgment (based on “common sense”) is often considered an antiquated and potentially misleading method of assessing risk that is strongly recommended against.

The most commonly used actuarial instruments include: Violent Risk Appraisal Guide (VRAG), Sex Offender Risk Appraisal Guide (SORAG), Level of Service Inventory – Revised (LSI-R), STATIC-99/ STATIC-2002.

The most commonly used structured clinical instruments include: Psychopathy Checklist – Revised (PCL-R), HCR-20 (Historical, Clinical, Risk-20), Sexual Violence Risk -20 (SVR-20), Structured Assessment of Violence Risk in Youth (SAVRY).

Research on Potential Risk Factors

Research dedicated to this topic has identified several universal risk factors, and some risk factors that are crime specific. Good risk assessment tools will tap into some or all of these empirically validated risk factors, and also consider protective factors that reduce the risk of offending. Note that the more risk factors that apply to an individual the more likely he or she is to offend. Because we cannot predict the future, it is advised that individuals refrain from saying that an individual will re-offend. Risk factors are often divided into two categories; static and dynamic[3].

Static Factors

Offender characteristics that are predictive of re-offending but cannot be changed are considered static. These include:

  • Psychopathy. Psychopathy is a personality disorder characterized by behavioral problems such as cruelty to people and animals from a young age, and emotional deficits such as a lack of empathy. It is typically diagnosed by administering the PCL-R. It is highly researched, and arguably the single greatest predictor of criminal behavior [4],[5].
  • Adult criminal history, pre-adult history of antisocial behavior
  • Family criminality, poor family rearing practices and structure, low socio-economic status
  • Age, gender, low intellectual functioning

Dynamic Factors

Characteristics of an offender that can be changed are considered dynamic. These are factors that should be primarily addressed by interventions, and include:

  • Deviant companions, interpersonal conflict
  • Criminogenic needs (antisocial cognitions, values and behaviors), personal distress and anxiety
  • Low social achievement, substance abuse

Crime-specific Factors

In addition to their scores on risk assessment scales, adult, juvenile, sexual and mentally disordered offenders have uniquely important risk factors. The primary risk factors most highly correlated with re-offending are listed for each type of offender below[2]:

  • Adult offenders: identification and socialization with other offenders, antisocial personality (Psychopathy), criminogenic needs.[3]
  • Adult sexual offenders: General self-regulation problems, violation of conditional release[6].
  • Young offenders: Age at first offence[7], age at first contact with the law, non-severe pathology, psychopathy[8].
  • Young sexual offenders: Non-Caucasian, psychopathy, victim of sexual abuse[9], deviant sexuality, more than one victim, out-of-home placement [10].
  • Mentally disordered offenders: Adult criminal history, juvenile delinquency[11].

Conclusion

Risk assessment will always be a predictive judgment and as such there will be errors in judgment. However, as those who deal with forensic populations, it is our duty to use up-to-date empirically based methods to make predictions that are as accurate as possible.

Quick summary:

  • Risk assessment asks: how likely is it that an individual will commit a crime?
  • Use actuarial or structured clinical judgment
  • DO NOT use unstructured clinical judgment.
  • Static factors are things like age that cannot be changed
  • Dynamic factors can be treated
  • Crime-specific risk factors also need to be considered

Where can I get more information?

Information from the EAPL-S is available online, in PDF, or as paper brochures sent through the mail. If you would like to have EAPL-S publications, you can order hardcopies for a nominal fee through This email address is being protected from spambots. You need JavaScript enabled to view it. .

References

1.      Kemshall, H. (1996). A review of research on the assessment and management of risk and dangerousness: Implications for policy and practice in the probation service. Birmingham, England: Home Office Research and Statistics Directorate.

2.     Singh, J. P., & Fazel, S. (2010). Forensic risk assessment: A metareview. Criminal Justice and Behavior, 37(9), 965-988. doi:10.1177/0093854810374274

3.     Gendreau, P., Little, T., & Goggin, C. (1996). A meta-analysis of the predictors of adult offender recidivism: What works? Criminology, 34, 575-607.

4.     Leistico, A., Salekin, R., DeCoster, J., & Rogers, R. (2008). A large-scale meta-analysis relating the Hare measures of psychopathy to antisocial conduct. Law and Human Behavior, 32, 28-45.

5.     Edens, J., Campbell, J. S., & Weir, J. M. (2007). Youth psychopathy and criminal recidivism: A meta-analysis of the Psychopathy Checklist measures. Law and Human Behavior, 31, 53-75.

6.     Hanson, R. K., & Morton-Bourgon, K. (2004). Predictors of sexual recidivism: An updated meta-analysis. (Cat. No. PS3-1/2004-2E-PDF). Ottawa, Ontario, Canada: Public Works and Government Services Canada.

7.     Cottle, C. C., Lee, R. J., & Heilbrun, K. (2001). The prediction of criminal recidivism in juveniles: A meta-analysis. Criminal Justice and Behavior, 28, 367-394.

8.     Schwalbe, C. (2007). Risk assessment for juvenile justice: A meta-analysis. Law and Human Behavior, 31, 449-462.

9.     McCann, K. (2006). A meta-analysis of the predictors of sexual recidivism in juvenile sexual offenders (Master’s thesis). Retrieved from http://ir.lib.sfu.ca/handle/1892/3414

10.  Redlak, A. (2003). An exploratory meta-analysis of the predictor variables of juvenile sex offenders who sexually recidivate. California School of Professional Psychology (Doctoral dissertation). Available from Dissertations and Theses database.(UMI No. 3092415)

11.  Bonta, J., Law, M., & Hanson, K. (1998). The prediction of criminal and violent recidivism among mentally disordered offenders: A meta-analysis. Psychological Bulletin, 123, 123-142.

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Overview of Fact Sheet topics covered to date