Simulations of child sexual abuse interviews using avatars paired with feedback improves interview quality

Abstract

We tested whether simulated child sexual abuse (CSA) interviews with computer-generated child avatars could improve interview quality. Feedback was provided not only on question types, as in previous research, but also on whether the conclusions drawn by the interviewers were correct. Twenty-one psychology students (average age M = 24.5) interviewed four different avatars which had a simulated story of either abuse or non-abuse. The participants were randomly divided into two groups: one received feedback on question types and conclusions after each simulated interview and the other one did not receive any feedback. Avatars revealed pre-defined ‘memories’ as a function of algorithms formulated based on previous empirical research on children's suggestibility. The feedback group used more open-ended and fewer closed questions. They also made more correct conclusions and found more correct details in the last two interviews compared to the no-feedback group. Feedback on both the question types and conclusions in simulated CSA interviews with avatars can improve the quality of investigative interviews in only one hour. The implications for training practice were discussed.