Women's Preferences and Willingness to Pay for Artificial Intelligence Chatbots in Women's Health: A Discrete Choice Experiment Study (Preprint) DOI Creative Commons
Jing Wang, Hewei Min, Tao Li

и другие.

Journal of Medical Internet Research, Год журнала: 2024, Номер unknown

Опубликована: Окт. 8, 2024

Over 96% of adult women face health issues, with 70% experiencing conditions like infections. Mobile education is increasingly popular but faces challenges in personalization and readability. Artificial intelligence (AI) chatbots provide tailored support, a discrete choice experiment can help understanding user preferences to improve chatbot design. This study aims at exploring the toward AI communication experience. A was conducted, identifying 6 main attributes chatbots: response accuracy, legibility, service cost, background information collection, utility, content provision. total 957 female participants from hospital Hebei Province participated, choosing between 2 hypothetical or opting for neither (a no-choice option). The conditional logit model used estimate preferences. were included analysis. results showed that preferred 100% accuracy (β=0.940, P<.001; 95% CI 0.624 1.255), very easy understand (β=0.907, 0.634 1.180), fee CN ¥0/month (β=-0.095, -0.108 -0.082; currency exchange rate US $1=CN ¥7.09 applicable), practical utility (β=1.085, 0.832 1.338), provision disease-related knowledge (β=0.752, 0.485 1.018). Whether not allow collection (only question answer information) has no significant impact on women's Additionally, willing pay an additional ¥9.916 (95% 6.843 12.292) ¥9.567 "very understand" information, ¥11.451 8.704 14.198) practical" utility. they ¥7.931 4.975 10.886) "knowledge diseases" compared "gender knowledge" (CN ¥2.602, -0.551 5.756). relative importance indicated (1.085/3.858, 28.12%) (0.940/3.858, 24.37%) most influential factors participants' designed users should focus high clear content, free access, privacy protection, disease attract enhance education.

Язык: Английский

Educable learning-oriented multilevel shared autonomy for inclusive mobility and healthcare DOI Creative Commons
Frédéric Vanderhaegen, Corentin Ascone

ITM Web of Conferences, Год журнала: 2024, Номер 69, С. 03004 - 03004

Опубликована: Янв. 1, 2024

This paper proposes a new paradigm based on educable learning for multilevel shared autonomy between humans and machines future inclusive mobility or healthcare. Multilevel is presented from the perspective of three groups process: group interactive supports, roles machine in course sources targets Two literature reviews present advances first two groups. Educable oriented then proposed to recover limits current approaches update online offline education supports. A case study illustrates feasibility such process.

Язык: Английский

Процитировано

0
Women's Preferences and Willingness to Pay for Artificial Intelligence Chatbots in Women's Health: A Discrete Choice Experiment Study (Preprint) DOI Creative Commons
Jing Wang, Hewei Min, Tao Li

и другие.

Journal of Medical Internet Research, Год журнала: 2024, Номер unknown

Опубликована: Окт. 8, 2024

Over 96% of adult women face health issues, with 70% experiencing conditions like infections. Mobile education is increasingly popular but faces challenges in personalization and readability. Artificial intelligence (AI) chatbots provide tailored support, a discrete choice experiment can help understanding user preferences to improve chatbot design. This study aims at exploring the toward AI communication experience. A was conducted, identifying 6 main attributes chatbots: response accuracy, legibility, service cost, background information collection, utility, content provision. total 957 female participants from hospital Hebei Province participated, choosing between 2 hypothetical or opting for neither (a no-choice option). The conditional logit model used estimate preferences. were included analysis. results showed that preferred 100% accuracy (β=0.940, P<.001; 95% CI 0.624 1.255), very easy understand (β=0.907, 0.634 1.180), fee CN ¥0/month (β=-0.095, -0.108 -0.082; currency exchange rate US $1=CN ¥7.09 applicable), practical utility (β=1.085, 0.832 1.338), provision disease-related knowledge (β=0.752, 0.485 1.018). Whether not allow collection (only question answer information) has no significant impact on women's Additionally, willing pay an additional ¥9.916 (95% 6.843 12.292) ¥9.567 "very understand" information, ¥11.451 8.704 14.198) practical" utility. they ¥7.931 4.975 10.886) "knowledge diseases" compared "gender knowledge" (CN ¥2.602, -0.551 5.756). relative importance indicated (1.085/3.858, 28.12%) (0.940/3.858, 24.37%) most influential factors participants' designed users should focus high clear content, free access, privacy protection, disease attract enhance education.

Язык: Английский

Процитировано

0