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Assessing the Impact of Usability Design Features of an mHealth App on Clinical Protocol Compliance Using a Mixed Methods Approach

abstract: In the last decade, the number of people who own a mobile phone or portable electronic communication device has grown exponentially. Recent advances in smartphone technology have enabled mobile devices to provide applications (“mHealth apps”) to support delivering interventions, tracking health treatments, or involving a healthcare team into the treatment process and symptom monitoring. Although the popularity of mHealth apps is increasing, few lessons have been shared regarding user experience design and evaluation for such innovations as they relate to clinical outcomes. Studies assessing usability for mobile apps primarily rely on survey instruments. Though surveys are effective in determining user perception of usability and positive attitudes towards an app, they do not directly assess app feature usage, and whether feature usage and related aspects of app design are indicative of whether intended tasks are completed by users. This is significant in the area of mHealth apps, as proper utilization of the app determines compliance to a clinical study protocol. Therefore it is important to understand how design directly impacts compliance, specifically what design factors are prevalent in non-compliant users. This research studies the impact of usability features on clinical protocol compliance by applying a mixed methods approach to usability assessment, combining traditional surveys, log analysis, and clickstream analysis to determine the connection of design to outcomes. This research is novel in its construction of the mixed methods approach and in its attempt to tie usability results to impacts on clinical protocol compliance. The validation is a case study approach, applying the methods to an mHealth app developed for early prevention of anxiety in middle school students. The results of three empirical studies are shared that support the construction of the mixed methods approach. / Dissertation/Thesis / Masters Thesis Computer Science 2016

Identiferoai:union.ndltd.org:asu.edu/item:39441
Date January 2016
ContributorsPatwardhan, Mandar (Author), Gary, Kevin A (Advisor), Pina, Armando (Committee member), Amresh, Ashish (Committee member), Arizona State University (Publisher)
Source SetsArizona State University
LanguageEnglish
Detected LanguageEnglish
TypeMasters Thesis
Format134 pages
Rightshttp://rightsstatements.org/vocab/InC/1.0/, All Rights Reserved

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