Understanding How Chatbot Phrasing Styles and Care Demonstration Influence Overweight Users' Adherence Intention Towards Chatbots Supporting Weight Management

Chatbots hold promise as a technology to aid in sustained weight management. However, determining the optimal way for chatbots to deliver advice to effectively change user behaviors remains a significant hurdle. This research investigates the effects of different chatbot communication styles and expressions of care on user satisfaction, misinterpretation, and intent to adhere to the advice in weight-related conversations. A mixed method study with 97 participants classified as overweight was conducted, dividing them into four groups based on explicit/implicit communication styles and the presence or absence of caring language. Surprisingly, the study found that most participants in the explicit communication groups viewed the chatbot as non-offensive. These participants also reported higher levels of enjoyment and a greater intention to follow the chatbot's recommendations. Utilizing caring language may diminish users' perception of the chatbot as a marketing tool, thereby increasing their willingness to interact. The article discusses the implications for the design of healthcare chatbots.

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Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2025-10-16
DOI
https://doi.org/10.1145/3757517
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
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article

Understanding How Chatbot Phrasing Styles and Care Demonstration Influence Overweight Users' Adherence Intention Towards Chatbots Supporting Weight Management

Jack Jamieson, Wen‐Chieh Lin, Wen-Hsuan Cheng, Wei-Han Wang et al.
Proceedings of the ACM on Human-Computer Interaction
AI in Service Interactions
article

Understanding How Chatbot Phrasing Styles and Care Demonstration Influence Overweight Users' Adherence Intention Towards Chatbots Supporting Weight Management

Jack Jamieson, Wen‐Chieh Lin, Wen-Hsuan Cheng, Wei-Han Wang, Yi‐Chieh Lee
article en

Abstract

Chatbots hold promise as a technology to aid in sustained weight management. However, determining the optimal way for chatbots to deliver advice to effectively change user behaviors remains a significant hurdle. This research investigates the effects of different chatbot communication styles and expressions of care on user satisfaction, misinterpretation, and intent to adhere to the advice in weight-related conversations. A mixed method study with 97 participants classified as overweight was conducted, dividing them into four groups based on explicit/implicit communication styles and the presence or absence of caring language. Surprisingly, the study found that most participants in the explicit communication groups viewed the chatbot as non-offensive. These participants also reported higher levels of enjoyment and a greater intention to follow the chatbot's recommendations. Utilizing caring language may diminish users' perception of the chatbot as a marketing tool, thereby increasing their willingness to interact. The article discusses the implications for the design of healthcare chatbots.

Proceedings of the ACM on Human-Computer InteractionVol. 9(7)
National Yang Ming Chiao Tung University (TW), National University of Singapore (SG), Naval Hospital Yokosuka Japan (JP)
Openalex Percentile: Top 85%
AI in Service Interactions
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Understanding How Chatbot Phrasing Styles and Care Demonstration Influence Overweight Users' Adherence Intention Towards Chatbots Supporting Weight Management — Jack Jamieson, Wen‐Chieh Lin, et al. · Proceedings of the ACM on Human-Computer Interaction (2025) | TGRS Research Map | TGRS