Please use this identifier to cite or link to this item: https://doi.org/10.2196/27388
Title: 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
Authors: Leong, Qiao Ying 
Sridhar, Shreya
Blasiak, Agata 
Tadeo, Xavier 
Yeo, GeckHong 
Remus, Alexandria 
Ho, Dean 
Keywords: Science & Technology
Life Sciences & Biomedicine
Health Care Sciences & Services
Medical Informatics
mHealth
digital medicine
anxiety
depression
systematic review
mental health conditions
mobile phone
RANDOMIZED CONTROLLED-TRIAL
SELF-HELP INTERVENTION
MENTAL-HEALTH
PRIMARY-CARE
COMMITMENT THERAPY
SMARTPHONE
SUPPORT
SYMPTOMS
FEASIBILITY
PREVENTION
Issue Date: 4-Feb-2022
Publisher: JMIR PUBLICATIONS, INC
Citation: Leong, Qiao Ying, Sridhar, Shreya, Blasiak, Agata, Tadeo, Xavier, Yeo, GeckHong, Remus, Alexandria, Ho, Dean (2022-02-04). 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. JOURNAL OF MEDICAL INTERNET RESEARCH 24 (2). ScholarBank@NUS Repository. https://doi.org/10.2196/27388
Abstract: Background: Mobile 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. Objective: The 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. Methods: A 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. Results: The 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. Conclusions: A 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.
Source Title: JOURNAL OF MEDICAL INTERNET RESEARCH
URI: https://scholarbank.nus.edu.sg/handle/10635/239363
ISSN: 1438-8871
DOI: 10.2196/27388
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