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Abstract
BackgroundCardiac rehabilitation (CR) improves outcomes for patients with ischemic heart disease or heart failure but is underused. New strategies to improve access to and engagement in CR are needed. There is considerable interest in technology-facilitated home CR. However, little is known about patient acceptance and use of mobile technology for CR.ObjectiveThe aim of this study was to develop a mobile app for technology-facilitated home CR and seek to determine its usability.MethodsWe recruited patients eligible for CR who had access to a mobile phone, tablet, or computer with Internet access. The mobile app includes physical activity goal setting, logs for tracking physical activity and health metrics (eg, weight, blood pressure, and mood), health education, reminders, and feedback. Study staff demonstrated the mobile app to participants in person and then observed participants completing prespecified tasks with the mobile app. Participants completed the System Usability Scale (SUS, 0-100), rated likelihood to use the mobile app (0-100), questionnaires on mobile app use, and participated in a semistructured interview. The Unified Theory of Acceptance and Use of Technology and the Theory of Planned Behavior informed the analysis. On the basis of participant feedback, we made iterative revisions to the mobile app between users.ResultsWe conducted usability testing in 13 participants. The first version of the mobile app was used by the first 5 participants, and revised versions were used by the final 8 participants. From the first version to revised versions, task completion success rate improved from 44% (11/25 tasks) to 78% (31/40 tasks; P=.05), SUS improved from 54 to 76 (P=.04; scale 0-100, with 100 being the best usability), and self-reported likelihood of use remained high at 76 and 87 (P=.30; scale 0-100, with 100 being the highest likelihood). In interviews, patients expressed interest in tracking health measures (“I think it’ll be good to track my exercise and to see what I’m doing”), a desire for introductory training (“Initially, training with a technical person, instead of me relying on myself”), and an expectation for sharing data with providers (“It would also be helpful to share with my doctor, it just being a matter of clicking a button and sharing it with my doctor”).ConclusionsWith participant feedback and iterative revisions, we significantly improved the usability of a mobile app for CR. Patient expectations for using a mobile app for CR include tracking health metrics, introductory training, and sharing data with providers. Iterative mixed-method evaluation may be useful for improving the usability of health technology.
Highlights
Cardiac rehabilitation (CR) is an evidence-based program of exercise training, risk factor management, education, and counseling that improves outcomes for patients with heart disease [1,2,3,4]
Patients expressed interest in tracking health measures (“I think it’ll be good to track my exercise and to see what I’m doing”), a desire for introductory training (“Initially, training with a technical person, instead of me relying on myself”), and an expectation for sharing data with providers (“It would be helpful to share with my doctor, it just being a matter of clicking a button and sharing it with my doctor”)
With participant feedback and iterative revisions, we significantly improved the usability of a mobile app for CR
Summary
Cardiac rehabilitation (CR) is an evidence-based program of exercise training, risk factor management, education, and counseling that improves outcomes for patients with heart disease [1,2,3,4]. An extension of the TPB has been developed to explain behavior specific to technology use, called the Unified Theory of Acceptance and Use of Technology (UTAUT) [27] and its extension for consumer use of technology (UTAUT2) [28]. This theory contends that constructs of performance expectancy, effort expectancy, social influence, facilitating conditions, hedonic motivation, price value, and habit influence behavioral intention, which is the strongest predictor of technology use. Little is known about patient acceptance and use of mobile technology for CR
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