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Virtual Agents for Alcohol Use Counseling: Exploring LLM-Powered Motivational Interviewing

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arxiv 2407.08095 v1 pith:WM5NRFZM submitted 2024-07-10 cs.HC cs.CL

classification cs.HCcs.CL
keywords virtualcounselingagentagentsalcoholcounselorempathetichuman
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. CAMI: A Counselor Agent Supporting Motivational Interviewing through State Inference and Topic Exploration

    cs.CL 2025-02 conditional novelty 6.0 of 10

    CAMI's combination of client-state inference and topic-tree exploration improves motivational-interviewing counseling performance over four LLM-based baselines in simulated sessions.

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