CA+: Cognition Augmented Counselor Agent Framework for Long-term Dynamic Client Engagement

TL;DR

This paper introduces CA+, a cognition-augmented framework for AI counseling that improves long-term client engagement, empathy, and satisfaction through hierarchical planning, balanced communication, and dynamic information management.

Contribution

The paper presents a novel AI counseling framework integrating cognitive theories and systematic design considerations to enhance long-term engagement and therapeutic effectiveness.

Findings

CA+ significantly improves client engagement and perceived empathy.

The system achieves higher client satisfaction compared to baseline.

Licensed counselors confirm CA+'s professionalism and effectiveness.

Abstract

Current AI counseling systems struggle with maintaining effective long-term client engagement. Through formative research with counselors and a systematic literature review, we identified five key design considerations for AI counseling interactions. Based on these insights, we propose CA+, a Cognition Augmented counselor framework enhancing contextual understanding through three components: (1) Therapy Strategies Module: Implements hierarchical Goals-Session-Action planning with bidirectional adaptation based on client feedback; (2) Communication Form Module: Orchestrates parallel guidance and empathy pathways for balanced therapeutic progress and emotional resonance; (3) Information Management: Utilizes client profile and therapeutic knowledge databases for dynamic, context-aware interventions. A three-day longitudinal study with 24 clients demonstrates CA+'s significant improvements in client engagement, perceived empathy, and overall satisfaction compared to a baseline system. Besides, two licensed counselors confirm its high professionalism. Our research demonstrates the potential for enhancing LLM engagement in psychological counseling dialogues through cognitive theory, which may inspire further innovations in computational interaction in the future.