MentalGuide: Towards Multi-Turn, State-Aware and Strategy-Driven Conversations for Mental Health Support

Authors

  • Jinwei He State Key Laboratory of VR Technology and Systems, School of CSE, Beihang University
  • Feng Lu State Key Laboratory of VR Technology and Systems, School of CSE, Beihang University

DOI:

https://doi.org/10.1609/aaai.v40i37.40354

Abstract

The global shortage of psychiatrists has become a critical issue, and the advent of large language models (LLMs) presents new opportunities to address this challenge. However, existing approaches continue to underperform in multi-turn mental health counseling, particularly in the arrangement of counseling strategies. To overcome these limitations, we propose MentalGuide, a state-aware and strategy-driven conversation framework designed for multi-turn mental health support. Our method integrates expert-derived prior probabilities of counseling strategies tailored to the target client's state with the reasoning capabilities of LLMs. This enables effective strategy formulation and strategy-driven response generation, without the need for additional training. Experimental results show that MentalGuide surpasses baselines in automated and human expert evaluations, demonstrating the closest alignment with real-world multi-turn counseling dynamics.

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Published

2026-03-14

How to Cite

He, J., & Lu, F. (2026). MentalGuide: Towards Multi-Turn, State-Aware and Strategy-Driven Conversations for Mental Health Support. Proceedings of the AAAI Conference on Artificial Intelligence, 40(37), 30951–30959. https://doi.org/10.1609/aaai.v40i37.40354

Issue

Section

AAAI Technical Track on Natural Language Processing II