Communicating violence risk during testimony: Do different formats lead to different perceptions among jurors?

Abstract

The legal system often charges forensic clinicians with the task of assisting the court in making decisions about a defendant's risk for violence. The extent to which these evaluations are useful depends, in part, on how the results are communicated to and understood by the trier of fact. Using a sample of 155 participants who previously served as a criminal trial juror, this study examined the effects of various risk communication formats on participants' perceptions of a hypothetical defendant's risk level, including his likelihood of reoffense and risk category, as well as sentencing and release decisions. Results consistently showed that when risk data was not anchored by an absolute recidivism estimate, predictions of future violence were highest. That is, when risk was stated only as an ordinal category (medium risk) or only in terms of needed interventions, participants severely overestimated the defendant's likelihood of violence. In the context of numerical data, the use of elaborative strategies (i.e., base rate examples and visual aids) did not impact risk perceptions. However, no between-groups differences were found across participants' decisions regarding sentencing and community release. Overall, participants tended to adhere to the expert's opinion when judging risk. Implications for best practices and future research are discussed, including the need for experts to simplify information during testimony and for risk researchers to work toward a better understanding of which strategies impact layperson perceptions of risk testimony and under what conditions.

Situational Predictors of Negotiation and Violence in Hostage and Barricade Incidents

“…Available in Online Supplemental Materials is an Appendix containing the two actuarial tools along with the experience tables intended for field use. Their designs were informed by the recommendations of an expert consensus group (Trevena et al, 2013) and are supported by empirical findings across diverse contexts (Aakl et al, 2011;McDowell & Jacobs, 2017;Zipkin et al, 2014), such as communication of violence risk (Batastini et al, 2019), health-related information (Buchter et al, 2014;Fagerlin et al, 2011;West et al, 2013), and weather forecasts (Joslyn & LeClerc, 2012).…”

The Base Rate Study: Developing Base Rates for Risk Factors and Indicators for Engagement in Violent Extremism

“…From a policy and practice perspective, generating base rates for predictors of violent extremism in a general population sample will help develop more rigorous putative risk and protective factors , increase transparency in the provision of evidence , reduce potential bias in decision‐making (, however, see Ref. ), improve risk communication , and allow for risk assessments based on Bayesian principles . Knowledge of base rates could also inform different forms of risk and threat assessment differently, as well as guide risk management and intervention (see Discussion).…”

Testing a new non-arbitrary system for risk communication

“…Overall, risk management information and categorical representation of risk were associated with higher ratings of risk. Though previously risk management information was found to aid judges in their decisions (Dolores & Redding, 2009), this study found the inclusion led to more severe overestimations of risk (Batastini et al, 2019).…”

“…Research also suggests that risk management and categorical presentations of risk without actuarial data produce higher risk estimates, and that the inclusion of visual aids to contextualize base rates seems to be ineffective. Numerical presentations by experts in the courts may not be understood by laypersons and it may be beneficial to provide data driven examples to support a categorical risk estimate (Batastini et al, 2019). The research also suggests that in accordance with findings from cognitive psychology, laypeople tend to ignore base rates when making decisions.…”

“…Research has suggested that individuals select an outcome that is most representative of an input (Tversky & Kahneman, 1974). In forensic contexts, this heuristic could explain base rate neglect demonstrated in the previous studies (Batastini et al, 2018(Batastini et al, , 2019 as individuals may judge the outcome's likelihood without actually considering the probability that the event will occur (Tversky & Kahneman, 1974;Neal & Grisso, 2014). For example, when participants were given a neutral description of a person and told that 70% of the individuals are engineers and 30% are lawyers, most participants said there was a 50% chance the individual was either an engineer or lawyer (Tversky & Kahneman, 1974).…”