Evidence map›Paper›PMID 35119370›Full record

SynthesisJournal of medical Internet research2022

Characteristics of Mobile Health Platforms for Depression and Anxiety: Content Analysis Through a Systematic Review of the Literature and Systematic Search of Two App Stores.

Qiao Ying Leong, Shreya Sridhar, Agata Blasiak, Xavier Tadeo, GeckHong Yeo, Alexandria Remus, Dean Ho

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of medical Internet research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

20 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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.

Qiao Ying LeongN.1 Institute for Health, National University of Singapore, Singapore, Singapore.ORCID 0000-0003-2369-4933
Shreya SridharN.1 Institute for Health, National University of Singapore, Singapore, Singapore.ORCID 0000-0003-1265-8937
Agata BlasiakN.1 Institute for Health, National University of Singapore, Singapore, Singapore.ORCID 0000-0003-0727-7611
Xavier TadeoN.1 Institute for Health, National University of Singapore, Singapore, Singapore.ORCID 0000-0003-0356-826X
GeckHong YeoN.1 Institute for Health, National University of Singapore, Singapore, Singapore.ORCID 0000-0002-5817-990X
Alexandria Remus *N.1 Institute for Health, National University of Singapore, Singapore, Singapore.ORCID 0000-0001-9002-7933
Dean Ho *N.1 Institute for Health, National University of Singapore, Singapore, Singapore.ORCID 0000-0002-7337-296X

Funding

Wellcome Trust
6 · The paper itself

Abstract

backgroundMobile health (mHealth) platforms show promise in the management of mental health conditions such as anxiety and depression. This has resulted in an abundance of mHealth platforms available for research or commercial use.

objectiveThe objective of this review is to characterize the current state of mHealth platforms designed for anxiety or depression that are available for research, commercial use, or both.

methodsA systematic review was conducted using a two-pronged approach: searching relevant literature with prespecified search terms to identify platforms in published research and simultaneously searching 2 major app stores-Google Play Store and Apple App Store-to identify commercially available platforms. Key characteristics of the mHealth platforms were synthesized, such as platform name, targeted condition, targeted group, purpose, technology type, intervention type, commercial availability, and regulatory information.

resultsThe literature and app store searches yielded 169 and 179 mHealth platforms, respectively. Most platforms developed for research purposes were designed for depression (116/169, 68.6%), whereas the app store search reported a higher number of platforms developed for anxiety (Android: 58/179, 32.4%; iOS: 27/179, 15.1%). The most common purpose of platforms in both searches was treatment (literature search: 122/169, 72.2%; app store search: 129/179, 72.1%). With regard to the types of intervention, cognitive behavioral therapy and referral to care or counseling emerged as the most popular options offered by the platforms identified in the literature and app store searches, respectively. Most platforms from both searches did not have a specific target age group. In addition, most platforms found in app stores lacked clinical and real-world evidence, and a small number of platforms found in the published research were available commercially.

conclusionsA considerable number of mHealth platforms designed for anxiety or depression are available for research, commercial use, or both. The characteristics of these mHealth platforms greatly vary. Future efforts should focus on assessing the quality-utility, safety, and effectiveness-of the existing platforms and providing developers, from both commercial and research sectors, a reporting guideline for their platform description and a regulatory framework to facilitate the development, validation, and deployment of effective mHealth platforms.

Indexed as

Mobile ApplicationsTelemedicineAnxietyDelivery of Health CareDepressionHumansanxietydepressiondigital medicinemental health conditionsmHealthmobile phonesystematic review

Identifiers

PMID35119370
PMCPMC8857696

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.