We introduce a novel application of large language models (LLMs) in developing a virtual counselor capable of conducting motivational interviewing (MI) for alcohol use counseling. Access to effective counseling remains limited, particularly for substance abuse, and virtual agents offer a promising solution by leveraging LLM capabilities to simulate nuanced communication techniques inherent in MI. Our approach combines prompt engineering and integration into a user-friendly virtual platform to facilitate realistic, empathetic interactions. We evaluate the effectiveness of our virtual agent through a series of studies focusing on replicating MI techniques and human counselor dialog. Initial findings suggest that our LLM-powered virtual agent matches human counselors' empathetic and adaptive conversational skills, presenting a significant step forward in virtual health counseling and providing insights into the design and implementation of LLM-based therapeutic interactions.
Philips Research（飞利浦研究院）；University of Cagliari（卡利亚里大学）
Empathetic response from the therapist is key to the success of clinical psychotherapy, especially motivational interviewing. Previous work on computational modelling of empathy in motivational interviewing has focused on offline, session-level assessment of therapist empathy, where empathy captures all efforts that the therapist makes to understand the client's perspective and convey that understanding to the client. In this position paper, we propose a novel task of turn-level detection of client need for empathy. Concretely, we propose to leverage pre-trained language models and empathy-rel…
CAMI: A Counselor Agent Supporting Motivational Interviewing through State Inference and Topic Exploration
Beijing Institute of Technology（北京理工大学）；Singapore Management University（新加坡管理大学）；Australian National University（澳大利亚国立大学）；National Institute of Education（教育学院）；Singapore University of Social Sciences（新加坡社科大学）；National University of Singapore（新加坡国立大学）
Benchmarking Motivational Interviewing Competence of Large Language Models
National Institute of Mental Health and Neuro Sciences (NIMHANS)（国家精神卫生与神经科学研究所（NIMHANS））；Indian Institute of Technology (IIT) Kharagpur（印度理工学院卡拉格普尔分校（IIT Kharagpur））
Distinct Profiles of Run-to-Run Score Reliability and Expert-Panel Alignment Across Four LLM Evaluators of Simulated Japanese-Language AI-to-AI Counseling
Japan National Institute of Occupational Safety and Health（日本国立职业安全卫生研究所）；Kaze To Taiyo（凯泽・太阳）；Saga Occupational Health Association（Saga职业健康协会）；Department of Pharmacy, Zikei Hospital/Zikei Institute of Psychiatry（药剂科，Zikei医院/Zikei精神医学研究所）；Department of Medical Welfare, Suzuka University of Medical Science（医疗福祉科， Suzuka医科大学）；Graduate School of Human Sciences, Ritsumeikan University（人类科学研究生院，立命馆大学）；Faculty of Nursing, National Defense Medical College（护理学部，国家防卫医疗大学）；Support Center for Students with Disabilities, Aoyama Gakuin University（残疾学生支持中心，上智大学）
Georgia Institute of Technology（佐治亚理工学院）；Carnegie Mellon University（卡内基梅隆大学）；Stanford University（斯坦福大学）
Millions of people participate in online peer-to-peer support sessions, yet there has been little prior research on systematic psychology-based evaluations of fine-grained peer-counselor behavior in relation to client satisfaction. This paper seeks to bridge this gap by mapping peer-counselor chat-messages to motivational interviewing (MI) techniques. We annotate 14,797 utterances from 734 chat conversations using 17 MI techniques and introduce four new interviewing codes such as chit-chat and inappropriate to account for the unique conversational patterns observed on online platforms. We auto…
GenAI for Social Work Field Education: Client Simulation with Real-Time Feedback
School of Computing（计算学院）；Data Science The University of Hong Kong Hong Kong, China（数据科学香港大学香港）；Dept. of Mathematics The University of Hong Kong Hong Kong, China（数学系香港大学香港）；Faculty of Engineering The University of Hong Kong Hong Kong, China（工程学院香港大学香港）；Social Administration The University of Hong Kong Hong Kong, China（社会行政香港大学香港）
Large Language Model-Powered Conversational Agent Delivering Problem-Solving Therapy (PST) for Family Caregivers: Enhancing Empathy and Therapeutic Alliance Using In-Context Learning
Florida State University（佛罗里达州立大学）；University of Washington（华盛顿大学）；University of Texas at Austin（德克萨斯大学奥斯汀分校）
Know You Before You Speak: User-State Modeling for LLM Personalization in Multi-Turn Conversation
School of Computing, National University of Singapore（新加坡国立大学计算机学院）；School of Artificial Intelligence, Beihang University（北航人工智能学院）；Institute of Computing Technology, Chinese Academy of Sciences（中国科学院计算技术研究所）；German Institute of Human Nutrition Potsdam-Rehbruecke（德国人类营养研究所波茨坦-雷赫布鲁克）
Can AI Relate: Testing Large Language Model Response for Mental Health Support
New York University（纽约大学）；Grossman School of Medicine（格罗斯曼医学院）；Massachusetts Institute of Technology（麻省理工学院）；University of California, Los Angeles（加州大学洛杉矶分校）
