Cognitive vs. emotional empathy: exploring their impact on user outcomes in health-assistant chatbots

Tingting Jiang, Chuxuan Huang, Yanrun Xu and Han Zheng

Behaviour and Information Technology, 2025, vol. 44, issue 18, 4387-4402

Abstract: Chatbots are increasingly employed to provide basic medical advice and medication guidance among other health information services. Despite their utility, many users feel a disconnect due to perceived lack of empathy in these systems, leading to resistance toward using chatbot services. Prior research in human–computer interaction has highlighted the significant role of empathy in enhancing user experience, yet it remains uncertain whether cognitive empathy and emotional empathy differ in their impact. Informed by the Computers as Social Actors (CASA) theory, this study conducted a between-subjects experiment to investigate how different empathy types in health-assistant chatbots influence user satisfaction and usage intention. Additionally, it examined the mediating role of social presence and the moderating role of gender. The findings revealed that emotional empathy significantly improved user satisfaction and intention to use compared to cognitive empathy, with no notable gender differences. Social presence partially mediated the relationship between the chatbot’s empathy type and user outcomes. These results not only enhance our understanding of empathy’s mechanisms and effects in human–computer interactions but also offer crucial insights for developing effective communication strategies in health-assistant chatbots.

Date: 2025
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DOI: 10.1080/0144929X.2025.2474087

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