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Same score, different message: perceptions of offender risk depend on Static-99R risk communication format
Jorge G Varela1, Marcus T Boccaccini1, Veronica A Cuervo1
1Department of Psychology and Philosophy.
The Static-99R risk assessment tool
Area of Science:
- Forensic Psychology
- Legal Decision-Making
- Risk Assessment
Background:
- The Static-99R is widely used to assess sexual offender recidivism risk.
- Communication of Static-99R scores can be presented in various formats: categorical, relative risk, or recidivism rates.
- The impact of these different communication formats on laypersons' understanding and conclusions is not well understood.
Purpose of the Study:
- To investigate whether judges and jurors interpret the same Static-99R score differently based on the communication format used.
- To examine how different risk communication formats influence risk perceptions of sexual offenders.
Main Methods:
- Community members (N=211) were presented with information about a sexual offender and his Static-99R score (1 or 6).
- The risk communication format was manipulated across three conditions: categorical, relative risk, or recidivism rate.
- Participants rated the offender's risk level and the importance/understandability of the Static-99R results.
Main Results:
- Participants rated the high-scoring offender as higher risk than the low-scoring offender only in the categorical communication condition.
- Risk ratings for the high-scoring offender were significantly higher in the categorical format compared to relative risk and recidivism rate formats.
- Participants found Static-99R results less important and harder to understand when presented in categorical or relative risk formats, particularly for low-risk scores.
Conclusions:
- The communication format significantly influences how laypersons perceive sexual offender risk scores.
- Categorical risk labels appear to be more impactful for high-risk offenders than statistical formats.
- Laypersons may be more receptive to high-risk assessments and interpretative labels over statistical data.
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