Prevention of maltreatment, physical and sexual abuse of children is a significant societal problem and a politically prioritized task. Every year, an estimated 18 million children in Europe are victims of abuse and maltreatment (WHO, 2013). Abuse and maltreatment increase the risk for severe psychological, psychosocial and somatic health problems. Protecting and assisting maltreated children is therefore of high priority for child protective services and law enforcement. These cases are demanding, and the quality of the investigative interviews conducted by the child protective services and the police must be high. However, national and international research show that although both intensive and less intensive training programs for investigative interviewers may impart knowledge about good practice, they have little effect on the interviewing skills.
The project proposes to develop a new digital interview-training program drawing on expertise in psychology, education and artificial intelligence. The program includes an interactive avatar (a virtual child) that responds like a real child during an interview situation. We will then determine if an interview-training program using realistic, interactive avatars can effectively improve to a consistently high level, the skills of child-welfare and law-enforcement professionals at interviewing maltreated and abused children. We will also investigate whether they maintain these skills over time. The project has the potential to contribute to more efficient and coordinated assistance to children who are victims of maltreatment, violence and sexual abuse. The interactive-learning program, if successfully, will thus significantly lower the interviewer-training costs. However, first and foremost, the project aims to improve the investigative interviewing skills of practitioners tasked with protecting vulnerable children, thereby contributing to the prevention of child abuse and physical violence.
Maltreatment and abuse of children is a significant societal problem and with serious damaging effects on children’s behavior, psychological development and adjustment. Both Child Protective Services (CPS) and law enforcement play important roles in protecting and assisting mistreated children. In their roles as investigators, they must elicit from children detailed, coherent and reliable accounts of their experiences. Researchers and professionals have developed best-practice guidelines for interviewing children to maximize narrative details. But despite huge investments in training programs, practitioners routinely fail to follow best-practices guidelines (Lamb, 2016). Recent studies show that interactive, computer-based learning activities can improve an investigator’s interviewer performance (Powell et al., 2016). This project seeks to create an empirically based interview-training system using realistic avatars and to determine if such a system can effectively train CPS and law enforcement professionals to conduct interviews of consistently high quality. To achieve this goal, an interdisciplinary team of psychologists and AI experts with expertise studying and working with at-risk children will use extant AI technologies and data from past investigative interviews with maltreated children to create a real-looking child avatar capable of expressing emotion and apparently spontaneous responses. This avatar will become part of an interview-training system that will be implemented with the cooperation of the CPS and police, and studied by the project team. The training system will then be evaluated, using pre-training and post-training and long-term post-training assessments, to determine effectiveness.