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Conversational Chatbot for Cigarette Smoking Cessation: Results From the 11-Step User-Centered Design Development
Jonathan B Bricker1,2, Brianna Sullivan1, Kristin Mull1
1Division of Public Health Sciences, Fred Hutch Cancer Center, Seattle, WA, United States.
QuitBot, a novel conversational chatbot, demonstrated higher smoking cessation rates compared to a text messaging program in a pilot study. This development marks the first large language model-based quit smoking intervention delivered via chatbot.
Area of Science:
- Digital health interventions
- Behavioral science
- Artificial intelligence in healthcare
Background:
- Conversational chatbots represent an emerging digital intervention for smoking cessation.
- No prior studies have detailed the complete development process of a smoking cessation chatbot.
Purpose of the Study:
- To report the user-centered design development process and randomized controlled trial (RCT) outcomes for QuitBot, a novel conversational chatbot for smoking cessation.
- To evaluate the efficacy and user engagement of QuitBot compared to existing digital interventions.
Main Methods:
- A 4-year user-centered design process involving needs assessment, persona development, and iterative prototyping.
- Development of a 42-day conversational program with content analysis of existing interventions.
- A pilot randomized controlled trial (RCT) to assess QuitBot's effectiveness, followed by iterative improvements including the addition of a large language model (LLM)-powered question-and-answer function.
Main Results:
- QuitBot demonstrated high user engagement and significantly higher 3-month abstinence rates (63%) compared to SmokefreeTXT (38.5%) in a pilot RCT.
- The chatbot's conversational feature, powered by LLMs and a 11,000-pair QnA library, effectively addressed user-posed questions.
- Transition from Facebook Messenger to a stand-alone app improved the delivery channel due to intermittent blocking issues.
Conclusions:
- The development resulted in the first LLM-based quit smoking program delivered as a conversational chatbot.
- Iterative testing and user feedback led to significant enhancements, including an improved delivery channel and a core LLM-supported conversational feature.
- The study highlights the potential of AI-driven conversational agents in smoking cessation interventions.
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