CA+: Cognition Augmented Counselor Agent Framework for Long-term Dynamic Client Engagement
Yuanrong Tang, Yu Kang, Yifan Wang, Tianhong Wang, Chen Zhong,, Jiangtao Gong

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…
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Taxonomy
TopicsDigital Mental Health Interventions
