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      The Definitions of Health Apps and Medical Apps From the Perspective of Public Health and Law: Qualitative Analysis of an Interdisciplinary Literature Overview

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          Abstract

          Background

          The terms health app and medical app are often used interchangeably but do not necessarily mean the same thing. To better understand these terms and better regulate such technologies, we need distinct definitions of health and medical apps.

          Objective

          This study aimed to provide an overview of the definitions of health and medical apps from an interdisciplinary perspective. We summarized the core elements of the identified definitions for their holistic understanding in the context of digital public health.

          Methods

          The legal frameworks for medical device regulation in the United States, the European Union, and Germany formed the basis of this study. We then searched 6 databases for articles defining health or medical apps from an interdisciplinary perspective. The narrative literature review was supported by a forward and backward snowball search for more original definitions of health and medical apps. A qualitative analysis was conducted on the identified relevant aspects and core elements of each definition. On the basis of these findings, we developed a holistic definition of health and medical apps and created a decision flowchart to highlight the differences between the 2 types.

          Results

          The legal framework showed that medical apps could be regulated as mobile medical devices, whereas there is no legal term for health apps. Our narrative literature review identified 204 peer-reviewed publications that offered a definition of health and medical apps. After screening for original definitions and applying the snowball method, 11.8% (24/204) of the publications were included in the qualitative analysis. Of these 24 publications, 22 (88%) provided an original definition of health apps and 11 (44%) described medical apps. The literature suggests that medical apps are a part of health apps. To describe health or medical apps, most definitions used the user group, a description of health, the device, the legal regulation, collected data, or technological functions. However, the regulation should not be a distinction criterion as it requires legal knowledge, which is neither suitable nor practical. An app’s intended medical or health use enables a clear differentiation between health and medical apps. Ultimately, the health aim of an app and its main target group are the only distinction criteria.

          Conclusions

          Health apps are software programs on mobile devices that process health-related data on or for their users. They can be used by every health-conscious person to maintain, improve, or manage the health of an individual or the community. As an umbrella term, health apps include medical apps. Medical apps share the same technological functions and devices. Health professionals, patients, and family caregivers are the main user groups. Medical apps are intended for clinical and medical purposes and can be legally regulated as mobile medical devices.

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          Most cited references80

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          Three approaches to qualitative content analysis.

          Content analysis is a widely used qualitative research technique. Rather than being a single method, current applications of content analysis show three distinct approaches: conventional, directed, or summative. All three approaches are used to interpret meaning from the content of text data and, hence, adhere to the naturalistic paradigm. The major differences among the approaches are coding schemes, origins of codes, and threats to trustworthiness. In conventional content analysis, coding categories are derived directly from the text data. With a directed approach, analysis starts with a theory or relevant research findings as guidance for initial codes. A summative content analysis involves counting and comparisons, usually of keywords or content, followed by the interpretation of the underlying context. The authors delineate analytic procedures specific to each approach and techniques addressing trustworthiness with hypothetical examples drawn from the area of end-of-life care.
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            Content analysis and thematic analysis: Implications for conducting a qualitative descriptive study.

            Qualitative content analysis and thematic analysis are two commonly used approaches in data analysis of nursing research, but boundaries between the two have not been clearly specified. In other words, they are being used interchangeably and it seems difficult for the researcher to choose between them. In this respect, this paper describes and discusses the boundaries between qualitative content analysis and thematic analysis and presents implications to improve the consistency between the purpose of related studies and the method of data analyses. This is a discussion paper, comprising an analytical overview and discussion of the definitions, aims, philosophical background, data gathering, and analysis of content analysis and thematic analysis, and addressing their methodological subtleties. It is concluded that in spite of many similarities between the approaches, including cutting across data and searching for patterns and themes, their main difference lies in the opportunity for quantification of data. It means that measuring the frequency of different categories and themes is possible in content analysis with caution as a proxy for significance. © 2013 Wiley Publishing Asia Pty Ltd.
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              Guidelines for snowballing in systematic literature studies and a replication in software engineering

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                Author and article information

                Contributors
                Journal
                JMIR Mhealth Uhealth
                JMIR Mhealth Uhealth
                JMU
                JMIR mHealth and uHealth
                JMIR Publications (Toronto, Canada )
                2291-5222
                October 2022
                31 October 2022
                : 10
                : 10
                : e37980
                Affiliations
                [1 ] Department of Health, Long-Term Care and Pensions Research Center on Inequality and Social Policy University of Bremen Bremen Germany
                [2 ] Leibniz ScienceCampus Digital Public Health Bremen Germany
                [3 ] Institute for Information, Health and Medical Law University of Bremen Bremen Germany
                [4 ] Unit of Lifestyle-Related Disorders Department of Epidemiological Methods and Etiological Research Leibniz Institute for Prevention and Epidemiology Bremen Germany
                [5 ] Department of Prevention and Health Promotion Institute for Public Health and Care Research University of Bremen Bremen Germany
                [6 ] Institute for Philosophy University of Bremen Bremen Germany
                [7 ] Human Computer Interaction Research Group Institute of Computer Science University of St. Gallen St. Gallen Switzerland
                [8 ] Department of Health Services Research Institute for Public Health and Care Research University of Bremen Bremen Germany
                Author notes
                Corresponding Author: Laura Maaß laura.maass@ 123456uni-bremen.de
                Author information
                https://orcid.org/0000-0001-7354-8120
                https://orcid.org/0000-0001-9895-9997
                https://orcid.org/0000-0002-2710-3259
                https://orcid.org/0000-0003-3586-0695
                https://orcid.org/0000-0003-3529-0653
                https://orcid.org/0000-0002-8367-4574
                Article
                v10i10e37980
                10.2196/37980
                9664324
                36315221
                10d79488-512f-412e-98cd-7e9d69a74dca
                ©Laura Maaß, Merle Freye, Chen-Chia Pan, Hans-Henrik Dassow, Jasmin Niess, Tina Jahnel. Originally published in JMIR mHealth and uHealth (https://mhealth.jmir.org), 31.10.2022.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), 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 https://mhealth.jmir.org/, as well as this copyright and license information must be included.

                History
                : 14 March 2022
                : 5 May 2022
                : 30 May 2022
                : 30 June 2022
                Categories
                Review
                Review

                mobile health,health app,medical app,digital health,regulation,mobile medical device,digital health applications,diga,digital care applications,dipa,snowball search,mobile phone

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