User Experience of Symptom Checkers: A Systematic Review
Yue You, Renkai Ma, Xinning Gui

TL;DR
This systematic review analyzes existing literature on symptom checkers, highlighting user demographics, explored experience aspects, and suggesting improvements in accuracy, safety, and usability for future designs.
Contribution
It provides a comprehensive overview of user experience research on symptom checkers and offers design recommendations based on identified gaps.
Findings
Most users are relatively young
Eight aspects of user experience have been studied
Future improvements should focus on accuracy, safety, and usability
Abstract
This review reports the user experience of symptom checkers, aiming to characterize users studied in the existing literature, identify the aspects of user experience of symptom checkers that have been studied, and offer design suggestions. Our literature search resulted in 31 publications. We found that (1) most symptom checker users are relatively young; (2) eight relevant aspects of user experience have been explored, including motivation, trust, acceptability, satisfaction, accuracy, usability, safety or security, and functionality; (3) future symptom checkers should improve their accuracy, safety, and usability.
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Taxonomy
TopicsDigital Mental Health Interventions · Mobile Health and mHealth Applications · Artificial Intelligence in Healthcare and Education
