Paper Number
1729
Paper Type
Complete Research Paper
Abstract
Weight management is a lifetime challenge involving the co-responsibility of individuals/patients and medical practitioners. Technological interventions, particularly AI chatbots, should support this co-responsibility. However, there's a lack of understanding regarding the design of AI chatbots for co-responsibility in weight management. This paper conducts a scoping review to address this gap and suggest future research directions. Utilizing Bandara et al.’s (2015) framework, we searched PubMed, Web of Science, ACM Digital Library, AIS eLibrary, and IEEE Xplore using predefined criteria focusing on empirical studies of AI chatbot-based interventions and system design showcasing interaction. Following PRISMA, we screened studies and performed a thematic analysis. Findings indicate that AI chatbot research in weight management is nascent, with most not designed for co-responsibility. We propose research directions to guide future work, emphasizing interaction design to enhance stakeholder collaboration in chatbot-mediated interventions, considering delivery mode, and ethical/privacy concerns.
Recommended Citation
Uzoechina, Chibuike E.; Cranefield, Jocelyn; and Doyle, Cathal, "Collaborating with AI Chatbots for Weight Management: A Literature Review and Research Agenda" (2024). ECIS 2024 Proceedings. 13.
https://aisel.aisnet.org/ecis2024/track06_humanaicollab/track06_humanaicollab/13
Collaborating with AI Chatbots for Weight Management: A Literature Review and Research Agenda
Weight management is a lifetime challenge involving the co-responsibility of individuals/patients and medical practitioners. Technological interventions, particularly AI chatbots, should support this co-responsibility. However, there's a lack of understanding regarding the design of AI chatbots for co-responsibility in weight management. This paper conducts a scoping review to address this gap and suggest future research directions. Utilizing Bandara et al.’s (2015) framework, we searched PubMed, Web of Science, ACM Digital Library, AIS eLibrary, and IEEE Xplore using predefined criteria focusing on empirical studies of AI chatbot-based interventions and system design showcasing interaction. Following PRISMA, we screened studies and performed a thematic analysis. Findings indicate that AI chatbot research in weight management is nascent, with most not designed for co-responsibility. We propose research directions to guide future work, emphasizing interaction design to enhance stakeholder collaboration in chatbot-mediated interventions, considering delivery mode, and ethical/privacy concerns.
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