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Individual differences in views toward healthcare conversational agents: A cross-sectional survey study

2025·2 Zitationen·Digital HealthOpen Access
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2

Zitationen

3

Autoren

2025

Jahr

Abstract

Background and Objective: To date, there has been limited research on people's attitudes and design preferences with respect to conversational agents (CAs) that are used for healthcare. Individual differences in attitudes and design preferences have received particularly little attention. The purpose of this study was to gain greater insight into this topic. Methods: We recruited American and Canadian residents through the online research platform Prolific. Participants completed a cross-sectional survey assessing demographic, personality, and health factors, as well as attitudes and design preferences with respect to healthcare CAs. Hierarchical regressions were used to determine demographic, personality, and health predictors of attitudes and design preferences. Results: = 12.94) were included in the analysis. Participants tended to report slightly positive attitudes toward healthcare CAs, with more positive attitudes among American residents and people with lower income, lower education levels, and higher levels of the personality factor conscientiousness. In general, participants preferred CAs that use text communication, have unrestricted language input, are disembodied, and simulate health professionals in their presentation. CAs that use text communication were preferred to a greater degree among people with higher levels of digital health literacy, and disembodied CAs were preferred to a greater degree among people with lower levels of conscientiousness. Conclusion: The results of this study provide insight into people's attitudes and design preferences with respect to healthcare CAs. This information will help guide developers on how to better design and market CAs for the health sector, which may increase people's adoption and use of these programs.

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Digital Mental Health InterventionsAI in Service InteractionsArtificial Intelligence in Healthcare and Education
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