App Designs and Interactive Features to Increase mHealth Adoption: User Expectation Survey and Experiment

Despite the ubiquity of smartphones, there is little guidance for how to design mobile health apps to increase use. Specifically, knowing what features users expect, grab their attention, encourage use (via predicted use or through positive app evaluations), and signal beneficial action possibilitie...

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Bibliographic Details
Published in:JMIR mHealth and uHealth 2021-11, Vol.9 (11), p.e29815-e29815
Main Authors: Lazard, Allison J, Babwah Brennen, J Scott, Belina, Stephanie P
Format: Article
Language:English
Subjects:
Chronic illnesses
Design
Health care
Humans
Influence
Intervention
Mobile Applications
Motivation
Original Paper
Perceptions
Physical fitness
Prevention
Smartphone
Smartphones
Surveys and Questionnaires
Technology Acceptance Model
Technology adoption
Telemedicine
Usability
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Summary:Despite the ubiquity of smartphones, there is little guidance for how to design mobile health apps to increase use. Specifically, knowing what features users expect, grab their attention, encourage use (via predicted use or through positive app evaluations), and signal beneficial action possibilities can guide and focus app development efforts. We investigated what features users expect and how the design (prototypicality) impacts app adoption. In a web-based survey, we elicited expectations, including presence and placement, for 12 app features. Thereafter, participants (n=462) viewed 2 health apps (high prototypicality similar to top downloaded apps vs low prototypicality similar to research interventions) and reported willingness to download, attention, and predicted use of app features. Participants rated both apps (high and low) for aesthetics, ease of use, usefulness, perceived affordances, and intentions to use. Most participants (425/462, 92%) expected features for navigation or personal settings (eg, menu) in specific regions (eg, top corners). Features with summary graphs or statics were also expected by many (395-396 of 462, 86%), with a center placement expectation. A feature to "share with friends" was least expected among participants (203/462, 44%). Features fell into 4 unique categories based on attention and predicted use, including essential features with high (>50% or >231 of 462) predicted use and attention (eg, calorie trackers), flashy features with high attention but lower predicted use (eg, links to specific diets), functional features with modest attention and low use (eg, settings), and mundane features with low attention and use (eg, discover tabs). When given a choice, 347 of 462 (75%) participants would download the high-prototypicality app. High prototypicality apps (vs low) led to greater aesthetics, ease of use, usefulness, and intentions, (for all, P
ISSN:2291-5222
2291-5222
DOI:10.2196/29815