Women’s Preferences and Willingness to Pay for AI Chatbots in Women’s Health: Discrete Choice Experiment Study - Jing Wang; Hewei Min; Tao Li; Jiaheng Li; Yang Jiang; Jingbo Zhang; Yibo Wu; Xinying Sun (Journal of Medical Internet Research)
Abstract BackgroundOver 96% of adult women face health issues, with 70% experiencing conditions like infections. Mobile health education is increasingly popular but faces challenges in personalization and readability. Artificial intelligence (AI) chatbots provide tailored support, and a discrete choice experiment can help in understanding user preferences to improve chatbot design. ObjectiveThis study aims at exploring the preferences of women toward AI chatbots to improve health education communication and user experience. MethodsA discrete choice experiment was conducted, identifying 6 main attributes of AI chatbots: response accuracy, legibility, service cost, background information collection, information utility, and content provision. A total of 957 female participants from a hospital in Hebei Province participated, choosing between 2 hypothetical chatbots or opting for neither (a no-choice option). The conditional logit model was used to estimate user preferences. ResultsA total of 957 participants were included in the analysis. The results showed that participants preferred a chatbot with 100% response accuracy (β=0.940, PPPPP ConclusionsAI chatbots designed for female users should focus on high response accuracy, clear content, free access, privacy protection, practical information, and disease knowledge to attract users and enhance health education.