Psychological Counseling Cannot Be Achieved Overnight: Automated Psychological Counseling Through Multi-Session Conversations

TL;DR

This paper introduces MusPsy-Dataset and MusPsy-Model for multi-session automated psychological counseling, emphasizing the importance of sustained engagement over single-session approaches.

Contribution

It provides a new dataset capturing multi-session counseling dynamics and a model that tracks client progress across sessions, advancing automated psychological support.

Findings

MusPsy-Model outperforms baseline models in multi-session counseling tasks.

The dataset reflects realistic multi-session counseling progressions.

Our approach improves the quality of automated psychological counseling.

Abstract

In recent years, Large Language Models (LLMs) have made significant progress in automated psychological counseling. However, current research focuses on single-session counseling, which doesn't represent real-world scenarios. In practice, psychological counseling is a process, not a one-time event, requiring sustained, multi-session engagement to progressively address clients' issues. To overcome this limitation, we introduce a dataset for Multi-Session Psychological Counseling Conversation Dataset (MusPsy-Dataset). Our MusPsy-Dataset is constructed using real client profiles from publicly available psychological case reports. It captures the dynamic arc of counseling, encompassing multiple progressive counseling conversations from the same client across different sessions. Leveraging our dataset, we also developed our MusPsy-Model, which aims to track client progress and adapt its counseling direction over time. Experiments show that our model performs better than baseline models across multiple sessions.