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      App Chronic Disease Checklist: Protocol to Evaluate Mobile Apps for Chronic Disease Self-Management

      research-article
      , BComm, GradDipEd 1 , , BPharm, PhD 1 , , BPharm, PhD 1 ,
      (Reviewer), (Reviewer), (Reviewer)
      JMIR Research Protocols
      JMIR Publications
      health, mobile applications, app, smartphones, self-management, protocol, usability checklist, self-care, chronic disease

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          Abstract

          Background

          The availability of mobile health apps for self-care continues to increase. While little evidence of their clinical impact has been published, there is general agreement among health authorities and authors that consumers’ use of health apps assist in self-management and potentially clinical decision making. A consumer’s sustained engagement with a health app is dependent on the usability and functionality of the app. While numerous studies have attempted to evaluate health apps, there is a paucity of published methods that adequately recognize client experiences in the academic evaluation of apps for chronic conditions.

          Objective

          This paper reports (1) a protocol to shortlist health apps for academic evaluation, (2) synthesis of a checklist to screen health apps for quality and reliability, and (3) a proposed method to theoretically evaluate usability of health apps, with a view towards identifying one or more apps suitable for clinical assessment.

          Methods

          A Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) flow diagram was developed to guide the selection of the apps to be assessed. The screening checklist was thematically synthesized with reference to recurring constructs in published checklists and related materials for the assessment of health apps. The checklist was evaluated by the authors for face and construct validity. The proposed method for evaluation of health apps required the design of procedures for raters of apps, dummy data entry to test the apps, and analysis of raters’ scores.

          Results

          The PRISMA flow diagram comprises 5 steps: filtering of duplicate apps; eliminating non-English apps; removing apps requiring purchase, filtering apps not updated within the past year; and separation of apps into their core functionality. The screening checklist to evaluate the selected apps was named the App Chronic Disease Checklist, and comprises 4 sections with 6 questions in each section. The validity check verified classification of, and ambiguity in, wording of questions within constructs. The proposed method to evaluate shortlisted and downloaded apps comprises instructions to attempt set-up of a dummy user profile, and dummy data entry to represent in-range and out-of-range clinical measures simulating a range of user behaviors. A minimum score of 80% by consensus (using the Intraclass Correlation Coefficient) between raters is proposed to identify apps suitable for clinical trials.

          Conclusions

          The flow diagram allows researchers to shortlist health apps that are potentially suitable for formal evaluation. The evaluation checklist enables quantitative comparison of shortlisted apps based on constructs reported in the literature. The use of multiple raters, and comparison of their scores, is proposed to manage inherent subjectivity in assessing user experiences. Initial trial of the combined protocol is planned for apps pertaining to the self-monitoring of asthma; these results will be reported elsewhere.

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          Most cited references42

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          Interrater agreement and interrater reliability: key concepts, approaches, and applications.

          Evaluations of interrater agreement and interrater reliability can be applied to a number of different contexts and are frequently encountered in social and administrative pharmacy research. The objectives of this study were to highlight key differences between interrater agreement and interrater reliability; describe the key concepts and approaches to evaluating interrater agreement and interrater reliability; and provide examples of their applications to research in the field of social and administrative pharmacy. This is a descriptive review of interrater agreement and interrater reliability indices. It outlines the practical applications and interpretation of these indices in social and administrative pharmacy research. Interrater agreement indices assess the extent to which the responses of 2 or more independent raters are concordant. Interrater reliability indices assess the extent to which raters consistently distinguish between different responses. A number of indices exist, and some common examples include Kappa, the Kendall coefficient of concordance, Bland-Altman plots, and the intraclass correlation coefficient. Guidance on the selection of an appropriate index is provided. In conclusion, selection of an appropriate index to evaluate interrater agreement or interrater reliability is dependent on a number of factors including the context in which the study is being undertaken, the type of variable under consideration, and the number of raters making assessments. Copyright © 2013 Elsevier Inc. All rights reserved.
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            Understanding randomised controlled trials.

            A Akobeng (2005)
            The hierarchy of evidence in assessing the effectiveness of interventions or treatments is explained, and the gold standard for evaluating the effectiveness of interventions, the randomised controlled trial, is discussed. Issues that need to be considered during the critical appraisal of randomised controlled trials, such as assessing the validity of trial methodology and the magnitude and precision of the treatment effect, and deciding on the applicability of research results, are discussed. Important terminologies such as randomisation, allocation concealment, blinding, intention to treat, p values, and confidence intervals are explained.
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              Just a Fad? Gamification in Health and Fitness Apps

              Background Gamification has been a predominant focus of the health app industry in recent years. However, to our knowledge, there has yet to be a review of gamification elements in relation to health behavior constructs, or insight into the true proliferation of gamification in health apps. Objective The objective of this study was to identify the extent to which gamification is used in health apps, and analyze gamification of health and fitness apps as a potential component of influence on a consumer’s health behavior. Methods An analysis of health and fitness apps related to physical activity and diet was conducted among apps in the Apple App Store in the winter of 2014. This analysis reviewed a sample of 132 apps for the 10 effective game elements, the 6 core components of health gamification, and 13 core health behavior constructs. A regression analysis was conducted in order to measure the correlation between health behavior constructs, gamification components, and effective game elements. Results This review of the most popular apps showed widespread use of gamification principles, but low adherence to any professional guidelines or industry standard. Regression analysis showed that game elements were associated with gamification (P<.001). Behavioral theory was associated with gamification (P<.05), but not game elements, and upon further analysis gamification was only associated with composite motivational behavior scores (P<.001), and not capacity or opportunity/trigger. Conclusions This research, to our knowledge, represents the first comprehensive review of gamification use in health and fitness apps, and the potential to impact health behavior. The results show that use of gamification in health and fitness apps has become immensely popular, as evidenced by the number of apps found in the Apple App Store containing at least some components of gamification. This shows a lack of integrating important elements of behavioral theory from the app industry, which can potentially impact the efficacy of gamification apps to change behavior. Apps represent a very promising, burgeoning market and landscape in which to disseminate health behavior change interventions. Initial results show an abundant use of gamification in health and fitness apps, which necessitates the in-depth study and evaluation of the potential of gamification to change health behaviors.
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                Author and article information

                Contributors
                Journal
                JMIR Res Protoc
                JMIR Res Protoc
                ResProt
                JMIR Research Protocols
                JMIR Publications (Toronto, Canada )
                1929-0748
                Oct-Dec 2016
                04 November 2016
                : 5
                : 4
                : e204
                Affiliations
                [1] 1School of Pharmacy Curtin University PerthAustralia
                Author notes
                Corresponding Author: Lynne Emmerton lynne.emmerton@ 123456curtin.edu.au
                Author information
                http://orcid.org/0000-0001-7324-491X
                http://orcid.org/0000-0001-5089-1268
                http://orcid.org/0000-0002-0806-6691
                Article
                v5i4e204
                10.2196/resprot.6194
                5116100
                27815233
                ffc5b3cc-342d-4c71-be79-b99c99f38c3e
                ©Kevin Anderson, Oksana Burford, Lynne Emmerton. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 04.11.2016.

                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 Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on http://www.researchprotocols.org, as well as this copyright and license information must be included.

                History
                : 13 June 2016
                : 11 July 2016
                : 17 September 2016
                : 18 September 2016
                Categories
                Protocol
                Protocol

                health,mobile applications,app,smartphones,self-management,protocol,usability checklist,self-care,chronic disease

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