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      Finding a Depression App: A Review and Content Analysis of the Depression App Marketplace

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          Abstract

          Background

          Depression is highly prevalent and causes considerable suffering and disease burden despite the existence of wide-ranging treatment options. Mobile phone apps offer the potential to help close this treatment gap by confronting key barriers to accessing support for depression.

          Objectives

          Our goal was to identify and characterize the different types of mobile phone depression apps available in the marketplace.

          Methods

          A search for depression apps was conducted on the app stores of the five major mobile phone platforms: Android, iPhone, BlackBerry, Nokia, and Windows. Apps were included if they focused on depression and were available to people who self-identify as having depression. Data were extracted from the app descriptions found in the app stores.

          Results

          Of the 1054 apps identified by the search strategy, nearly one-quarter (23.0%, 243/1054) unique depression apps met the inclusion criteria. Over one-quarter (27.7%, 210/758) of the excluded apps failed to mention depression in the title or description. Two-thirds of the apps had as their main purpose providing therapeutic treatment (33.7%, 82/243) or psychoeducation (32.1%, 78/243). The other main purpose categories were medical assessment (16.9%, 41/243), symptom management (8.2%, 20/243), and supportive resources (1.6%, 4/243). A majority of the apps failed to sufficiently describe their organizational affiliation (65.0%, 158/243) and content source (61.7%, 150/243). There was a significant relationship ( χ 2 5=50.5, P<.001) between the main purpose of the app and the reporting of content source, with most medical assessment apps reporting their content source (80.5%, 33/41). A fifth of the apps featured an e-book (20.6%, 50/243), audio therapy (16.9%, 41/243), or screening (16.9%, 41/243) function. Most apps had a dynamic user interface (72.4%, 176/243) and used text as the main type of media (51.9%, 126/243), and over a third (14.4%, 35/243) incorporated more than one form of media.

          Conclusion

          Without guidance, finding an appropriate depression app may be challenging, as the search results yielded non-depression–specific apps to depression apps at a 3:1 ratio. Inadequate reporting of organization affiliation and content source increases the difficulty of assessing the credibility and reliability of the app. While certification and vetting initiatives are underway, this study demonstrates the need for standardized reporting in app stores to help consumers select appropriate tools, particularly among those classified as medical devices.

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          Most cited references 68

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          The measurement of observer agreement for categorical data

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            The measurement of observer agreement for categorical data

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              Detection of postnatal depression. Development of the 10-item Edinburgh Postnatal Depression Scale.

              The development of a 10-item self-report scale (EPDS) to screen for Postnatal Depression in the community is described. After extensive pilot interviews a validation study was carried out on 84 mothers using the Research Diagnostic Criteria for depressive illness obtained from Goldberg's Standardised Psychiatric Interview. The EPDS was found to have satisfactory sensitivity and specificity, and was also sensitive to change in the severity of depression over time. The scale can be completed in about 5 minutes and has a simple method of scoring. The use of the EPDS in the secondary prevention of Postnatal Depression is discussed.
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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
                16 February 2015
                : 3
                : 1
                Affiliations
                1Centre for Addictions and Mental Health (CAMH) CAMH Education Toronto, ONCanada
                2Institute of Health Policy, Management and Evaluation University of Toronto Toronto, ONCanada
                3Centre for Global eHealth Innovation Toronto General Hospital Toronto, ONCanada
                4ELLICSR Health, Wellness and Cancer Survivorship Centre Toronto General Hospital Toronto, ONCanada
                5Faculty of Medicine Department of Psychiatry University of Toronto Toronto, ONCanada
                Author notes
                Corresponding Author: David Wiljer david.wiljer@ 123456camh.ca
                Article
                v3i1e16
                10.2196/mhealth.3713
                4376135
                25689790
                ©Nelson Shen, Michael-Jane Levitan, Andrew Johnson, Jacqueline Lorene Bender, Michelle Hamilton-Page, Alejandro (Alex) R Jadad, David Wiljer. Originally published in JMIR Mhealth and Uhealth (http://mhealth.jmir.org), 16.02.2015.

                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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