Finding a Depression App: A Review and Content Analysis of the Depression App Marketplace
BackgroundDepression 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. O...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
JMIR Publications
2015-02-01
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| Series: | JMIR mHealth and uHealth |
| Online Access: | http://mhealth.jmir.org/2015/1/e16/ |
| _version_ | 1819278949720522752 |
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| author | Shen, Nelson Levitan, Michael-Jane Johnson, Andrew Bender, Jacqueline Lorene Hamilton-Page, Michelle Jadad, Alejandro (Alex) R Wiljer, David |
| author_facet | Shen, Nelson Levitan, Michael-Jane Johnson, Andrew Bender, Jacqueline Lorene Hamilton-Page, Michelle Jadad, Alejandro (Alex) R Wiljer, David |
| author_sort | Shen, Nelson |
| collection | DOAJ |
| description | BackgroundDepression 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.
ObjectivesOur goal was to identify and characterize the different types of mobile phone depression apps available in the marketplace.
MethodsA 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.
ResultsOf 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 (χ25=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.
ConclusionWithout 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. |
| first_indexed | 2024-12-24T00:20:08Z |
| format | Article |
| id | doaj.art-9a3d5d5cb14542bd81aa1dca36ff391b |
| institution | Directory Open Access Journal |
| issn | 2291-5222 |
| language | English |
| last_indexed | 2024-12-24T00:20:08Z |
| publishDate | 2015-02-01 |
| publisher | JMIR Publications |
| record_format | Article |
| series | JMIR mHealth and uHealth |
| spelling | doaj.art-9a3d5d5cb14542bd81aa1dca36ff391b2022-12-21T17:24:37ZengJMIR PublicationsJMIR mHealth and uHealth2291-52222015-02-0131e1610.2196/mhealth.3713Finding a Depression App: A Review and Content Analysis of the Depression App MarketplaceShen, NelsonLevitan, Michael-JaneJohnson, AndrewBender, Jacqueline LoreneHamilton-Page, MichelleJadad, Alejandro (Alex) RWiljer, DavidBackgroundDepression 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. ObjectivesOur goal was to identify and characterize the different types of mobile phone depression apps available in the marketplace. MethodsA 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. ResultsOf 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 (χ25=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. ConclusionWithout 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.http://mhealth.jmir.org/2015/1/e16/ |
| spellingShingle | Shen, Nelson Levitan, Michael-Jane Johnson, Andrew Bender, Jacqueline Lorene Hamilton-Page, Michelle Jadad, Alejandro (Alex) R Wiljer, David Finding a Depression App: A Review and Content Analysis of the Depression App Marketplace JMIR mHealth and uHealth |
| title | Finding a Depression App: A Review and Content Analysis of the Depression App Marketplace |
| title_full | Finding a Depression App: A Review and Content Analysis of the Depression App Marketplace |
| title_fullStr | Finding a Depression App: A Review and Content Analysis of the Depression App Marketplace |
| title_full_unstemmed | Finding a Depression App: A Review and Content Analysis of the Depression App Marketplace |
| title_short | Finding a Depression App: A Review and Content Analysis of the Depression App Marketplace |
| title_sort | finding a depression app a review and content analysis of the depression app marketplace |
| url | http://mhealth.jmir.org/2015/1/e16/ |
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