Daily Arxiv

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A Fully Generative Motivational Interviewing Counselor Chatbot for Moving Smokers Towards the Decision to Quit

Created by
  • Haebom

Author

Zafarullah Mahmood, Soliman Ali, Jiading Zhu, Mohamed Abdelwahab, Michelle Yu Collins, Sihan Chen, Yi Cheng Zhao, Jodi Wolff, Osnat Melamed, Nadia Minian, Marta Maslej, Carolynne Cooper, Matt Ratto, Peter Selby, Jonathan Rose

Outline

This paper presents the results of a study that developed a chatbot for smoking cessation counseling using the latest large-scale language model (LLM) and verified its effectiveness with 106 participants. The chatbot, which applied the motivational interviewing (MI) technique, improved the participants' confidence in smoking cessation success by an average of 1.7 points, and the automatic evaluation result showed that the MI compliance rate was 98%, which was higher than that of human counselors. The participants positively evaluated the chatbot's empathy ability, and the analysis of the participants' language showed that they were highly motivated to change, which is the main goal of MI. These results suggest the possibility of LLM-based automated counseling.

Takeaways, Limitations

Takeaways:
Demonstrating the effectiveness of an LLM-based automated consulting system.
Presenting the potential application of the LLM in the field of smoking cessation counseling.
Development and validation of an automated counseling assessment system.
We demonstrate that LLM-based chatbots can outperform human counselors in terms of MI compliance rates.
Limitations:
Chatbots' empathy skills are rated lower than those of human counselors.
The number of participants (106) was relatively small.
Because this model is specialized in smoking cessation counseling, its generalizability to other counseling fields is limited.
Further research is needed on long-term effects and maintenance.
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