Scaffolding Empathy: Training Counselors with Simulated Patients and Utterance-level Performance Visualizations
This addresses the need for more efficient training of counselors in motivational interviewing, though it is incremental as it builds on existing simulation-based methods with new feedback mechanisms.
The paper tackled the problem of providing frequent, detailed feedback in counselor training by developing an LLM-powered system with simulated patients and turn-by-turn visualizations, demonstrating high usability and satisfaction in an evaluation with professional and student counselors.
Learning therapeutic counseling involves significant role-play experience with mock patients, with current manual training methods providing only intermittent granular feedback. We seek to accelerate and optimize counselor training by providing frequent, detailed feedback to trainees as they interact with a simulated patient. Our first application domain involves training motivational interviewing skills for counselors. Motivational interviewing is a collaborative counseling style in which patients are guided to talk about changing their behavior, with empathetic counseling an essential ingredient. We developed and evaluated an LLM-powered training system that features a simulated patient and visualizations of turn-by-turn performance feedback tailored to the needs of counselors learning motivational interviewing. We conducted an evaluation study with professional and student counselors, demonstrating high usability and satisfaction with the system. We present design implications for the development of automated systems that train users in counseling skills and their generalizability to other types of social skills training.