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      Mobile App Rating Scale: A New Tool for Assessing the Quality of Health Mobile Apps

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          Abstract

          Background

          The use of mobile apps for health and well being promotion has grown exponentially in recent years. Yet, there is currently no app-quality assessment tool beyond “star”-ratings.

          Objective

          The objective of this study was to develop a reliable, multidimensional measure for trialling, classifying, and rating the quality of mobile health apps.

          Methods

          A literature search was conducted to identify articles containing explicit Web or app quality rating criteria published between January 2000 and January 2013. Existing criteria for the assessment of app quality were categorized by an expert panel to develop the new Mobile App Rating Scale (MARS) subscales, items, descriptors, and anchors. There were sixty well being apps that were randomly selected using an iTunes search for MARS rating. There were ten that were used to pilot the rating procedure, and the remaining 50 provided data on interrater reliability.

          Results

          There were 372 explicit criteria for assessing Web or app quality that were extracted from 25 published papers, conference proceedings, and Internet resources. There were five broad categories of criteria that were identified including four objective quality scales: engagement, functionality, aesthetics, and information quality; and one subjective quality scale; which were refined into the 23-item MARS. The MARS demonstrated excellent internal consistency (alpha = .90) and interrater reliability intraclass correlation coefficient (ICC = .79).

          Conclusions

          The MARS is a simple, objective, and reliable tool for classifying and assessing the quality of mobile health apps. It can also be used to provide a checklist for the design and development of new high quality health apps.

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          Most cited references 29

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          Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement.

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            Intraclass correlations: uses in assessing rater reliability.

            Reliability coefficients often take the form of intraclass correlation coefficients. In this article, guidelines are given for choosing among six different forms of the intraclass correlation for reliability studies in which n target are rated by k judges. Relevant to the choice of the coefficient are the appropriate statistical model for the reliability and the application to be made of the reliability results. Confidence intervals for each of the forms are reviewed.
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              Health behavior models in the age of mobile interventions: are our theories up to the task?

              Mobile technologies are being used to deliver health behavior interventions. The study aims to determine how health behavior theories are applied to mobile interventions. This is a review of the theoretical basis and interactivity of mobile health behavior interventions. Many of the mobile health behavior interventions reviewed were predominately one way (i.e., mostly data input or informational output), but some have leveraged mobile technologies to provide just-in-time, interactive, and adaptive interventions. Most smoking and weight loss studies reported a theoretical basis for the mobile intervention, but most of the adherence and disease management studies did not. Mobile health behavior intervention development could benefit from greater application of health behavior theories. Current theories, however, appear inadequate to inform mobile intervention development as these interventions become more interactive and adaptive. Dynamic feedback system theories of health behavior can be developed utilizing longitudinal data from mobile devices and control systems engineering models.
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                Author and article information

                Contributors
                Journal
                JMIR Mhealth Uhealth
                JMIR Mhealth Uhealth
                JMU
                JMIR mHealth and uHealth
                JMIR Publications Inc. (Toronto, Canada )
                2291-5222
                Jan-Mar 2015
                11 March 2015
                : 3
                : 1
                Affiliations
                1Institute of Health & Biomedical Innovation School of Psychology and Counselling Queensland University of Technology (QUT) Brisbane, QLDAustralia
                2The Young and Well Cooperative Research Centre (Young and Well CRC) Abbotsford, VICAustralia
                3School of Design Creative Industries Faculty Queensland University of Technology (QUT) Brisbane, QLDAustralia
                4Information Systems Science and Engineering Faculty Queensland University of Technology (QUT) Brisbane, QLDAustralia
                Author notes
                Corresponding Author: Leanne Hides leanne.hides@ 123456qut.edu.au
                Article
                v3i1e27
                10.2196/mhealth.3422
                4376132
                25760773
                ©Stoyan R Stoyanov, Leanne Hides, David J Kavanagh, Oksana Zelenko, Dian Tjondronegoro, Madhavan Mani. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 11.03.2015.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR mhealth and uhealth, is properly cited. The complete bibliographic information, a link to the original publication on http://mhealth.jmir.org/, as well as this copyright and license information must be included.

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