A Multi-Agent Dual Dialogue System to Support Mental Health Care Providers
Abstract
We introduce a general-purpose, human-in-the-loop dual dialogue system to support mental health care professionals. The system, co-designed with care providers, is conceptualized to assist them in interacting with care seekers rather than functioning as a fully automated dialogue system solution. The AI assistant within the system reduces the cognitive load of mental health care providers by proposing responses, analyzing conversations to extract pertinent themes, summarizing dialogues, and recommending localized relevant content and internet-based cognitive behavioral therapy exercises. These functionalities are achieved through a multi-agent system design, where each specialized, supportive agent is characterized by a large language model. In evaluating the multi-agent system, we focused specifically on the proposal of responses to emotionally distressed care seekers. We found that the proposed responses matched a reasonable human quality in demonstrating empathy, showing its appropriateness for augmenting the work of mental health care providers.
Keywords
Cite
@article{arxiv.2411.18429,
title = {A Multi-Agent Dual Dialogue System to Support Mental Health Care Providers},
author = {Onno P. Kampman and Ye Sheng Phang and Stanley Han and Michael Xing and Xinyi Hong and Hazirah Hoosainsah and Caleb Tan and Genta Indra Winata and Skyler Wang and Creighton Heaukulani and Janice Huiqin Weng and Robert JT Morris},
journal= {arXiv preprint arXiv:2411.18429},
year = {2024}
}
Comments
Update: Render figures properly and update title