Evidence map›Paper›PMID 25689790›Full record

ReviewJMIR mHealth and uHealth2015

Finding a depression app: a review and content analysis of the depression app marketplace.

Nelson Shen, Michael-Jane Levitan, Andrew Johnson, Jacqueline Lorene Bender, Michelle Hamilton-Page, Alejandro Alex R Jadad, David Wiljer

Open access · goldAbstract readReview
In one paragraph

Review in JMIR mHealth and uHealth, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 123 papers, 11 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
123citing papers in PubMed, 11 pooled it
32.2field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

123 citing papers in PubMed, 11 syntheses or guidelines pooled it, 305 citations in OpenAlex.

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  5. Evaluating Commercially Available Mobile Apps for Depression Self-Management.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2020
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  13. Evaluation of the Effectiveness of Mobile App-Based Stress-Management Program: A Randomized Controlled Trial.International journal of environmental research and public health · 2019
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63 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Nelson ShenCentre for Addictions and Mental Health (CAMH), CAMH Education, Toronto, ON, Canada.ORCID http://orcid.org/0000-0003-1788-8176
Centre for Addiction and Mental Health · CAUniversity of Toronto · CAToronto General Hospital · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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 (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.

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.

Indexed as

consumerdepressionhealth informationmental healthmobile apps

Identifiers

PMID25689790
PMCPMC4376135
OpenAlexW1973546009

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.