Document Type

Article

Publication Date

9-11-2023

Publication Title

ACM Transactions on Computer-Human Interaction

Volume

30

Issue

4

First Page

1

Last Page

44

DOI

https://doi.org/10.1145/3589959

Abstract

Chatbot-based symptom checker (CSC) apps have become increasingly popular in healthcare. These apps engage users in human-like conversations and offer possible medical diagnoses. The conversational design of these apps can significantly impact user perceptions and experiences, and may influence medical decisions users make and the medical care they receive. However, the effects of the conversational design of CSCs remain understudied, and there is a need to investigate and enhance users’ interactions with CSCs. In this article, we conducted a two-stage exploratory study using a human-centered design methodology. We first conducted a qualitative interview study to identify key user needs in engaging with CSCs. We then performed an experimental study to investigate potential CSC conversational design solutions based on the results from the interview study. We identified that emotional support, explanations of medical information, and efficiency were important factors for users in their interactions with CSCs. We also demonstrated that emotional support and explanations could affect user perceptions and experiences, and they are context-dependent. Based on these findings, we offer design implications for CSC conversations to improve the user experience and health-related decision-making.

Comments

© {Authors | ACM} {2023}. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in {ACM Transactions on Computer-Human Interactionn},https://doi.org/10.1145/3589959

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