Using design science and artificial intelligence to improve health communication: ChronologyMD case example
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Linda Neuhauser1, Gary L Kreps, Kathleen Morrison
1School of Public Health, University of California, Berkeley, USA. lindan@berkeley.edu
Objective:
This paper describes how design science theory and methods and use of artificial intelligence (AI) components can improve the effectiveness of health communication.
Methods:
We identified key weaknesses of traditional health communication and features of more successful eHealth/AI communication. We examined characteristics of the design science paradigm and the value of its user-centered methods to develop eHealth/AI communication. We analyzed a case example of the participatory design of AI components in the ChronologyMD project intended to improve management of Crohn's disease.
Results:
eHealth/AI communication created with user-centered design shows improved relevance to users' needs for personalized, timely and interactive communication and is associated with better health outcomes than traditional approaches. Participatory design was essential to develop ChronologyMD system architecture and software applications that benefitted patients.
Conclusion:
AI components can greatly improve eHealth/AI communication, if designed with the intended audiences. Design science theory and its iterative, participatory methods linked with traditional health communication theory and methods can create effective AI health communication.
Practice Implications:
eHealth/AI communication researchers, developers and practitioners can benefit from a holistic approach that draws from theory and methods in both design sciences and also human and social sciences to create successful AI health communication.
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