Multi-Level Feedback Generation with Large Language Models for Empowering Novice Peer Counselors

Understand

Realistic practice and tailored feedback are key processes for training peer counselors with clinical skills.

• However, existing mechanisms of providing feedback largely rely on human supervision.
• Peer counselors often lack mechanisms to receive detailed feedback from experienced mentors, making it difficult for them to support the large number of people with mental health issues who use peer counseling.
• Our work aims to leverage large language models to provide contextualized and multi-level feedback to empower peer counselors, especially novices, at scale.