Improving the design of patient-generated health data visualizations: design considerations from a Fitbit sleep study.

Autor:	Tsai CT; Department of Biomedical Informatics, College of Medicine, University of Cincinnati, Cincinnati, Ohio, USA.; School of Design, College of Design, Architecture, Art, and Planning, University of Cincinnati, Cincinnati, Ohio, USA., Rajput G; Department of Biomedical Informatics, College of Medicine, University of Cincinnati, Cincinnati, Ohio, USA.; Medical Science Baccalaureate Program, College of Medicine, University of Cincinnati, Cincinnati, Ohio, USA., Gao A; Department of Biomedical Informatics, College of Medicine, University of Cincinnati, Cincinnati, Ohio, USA.; Medical Science Baccalaureate Program, College of Medicine, University of Cincinnati, Cincinnati, Ohio, USA., Wu Y; Department of Biomedical Informatics, College of Medicine, University of Cincinnati, Cincinnati, Ohio, USA.; School of Design, College of Design, Architecture, Art, and Planning, University of Cincinnati, Cincinnati, Ohio, USA., Wu DTY; Department of Biomedical Informatics, College of Medicine, University of Cincinnati, Cincinnati, Ohio, USA.; School of Design, College of Design, Architecture, Art, and Planning, University of Cincinnati, Cincinnati, Ohio, USA.; Medical Science Baccalaureate Program, College of Medicine, University of Cincinnati, Cincinnati, Ohio, USA.
Jazyk:	angličtina
Zdroj:	Journal of the American Medical Informatics Association : JAMIA [J Am Med Inform Assoc] 2024 Jan 18; Vol. 31 (2), pp. 465-471.
DOI:	10.1093/jamia/ocad117
Abstrakt:	Interactive data visualization can be a viable way to discover patterns in patient-generated health data and enable health behavior changes. However, very few studies have investigated the design and usability of such data visualization. The present study aimed to (1) explore user experiences with sleep data visualizations in the Fitbit app, and (2) focus on end users' perspectives to identify areas of improvement and potential solutions. The study recruited eighteen pre-medicine college students, who wore Fitbit watches for a two-week sleep data collection period and participated in an exit semi-structured interview to share their experience. A focus group was conducted subsequently to ideate potential solutions. The qualitative analysis identified six pain points (PPs) from the interview data using affinity mapping. Four design solutions were proposed by the focus group to address these PPs and illustrated by a set of mock-ups. The study findings informed four design considerations: (1) usability, (2) transparency and explainability, (3) understandability and actionability, and (4) individualized benchmarking. Further research is needed to examine the design guidelines and best practices of sleep data visualization, to create well-designed visualizations for the general population that enables health behavior changes. (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)
Databáze:	MEDLINE
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