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Objective User Engagement With Mental Health Apps: Systematic Search and Panel-Based Usage Analysis

BACKGROUND: Understanding patterns of real-world usage of mental health apps is key to maximizing their potential to increase public self-management of care. Although developer-led studies have published results on the use of mental health apps in real-world settings, no study yet has systematically...

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Autores principales: Baumel, Amit, Muench, Frederick, Edan, Stav, Kane, John M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6785720/
https://www.ncbi.nlm.nih.gov/pubmed/31573916
http://dx.doi.org/10.2196/14567
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author Baumel, Amit
Muench, Frederick
Edan, Stav
Kane, John M
author_facet Baumel, Amit
Muench, Frederick
Edan, Stav
Kane, John M
author_sort Baumel, Amit
collection PubMed
description BACKGROUND: Understanding patterns of real-world usage of mental health apps is key to maximizing their potential to increase public self-management of care. Although developer-led studies have published results on the use of mental health apps in real-world settings, no study yet has systematically examined usage patterns of a large sample of mental health apps relying on independently collected data. OBJECTIVE: Our aim is to present real-world objective data on user engagement with popular mental health apps. METHODS: A systematic engine search was conducted using Google Play to identify Android apps with 10,000 installs or more targeting anxiety, depression, or emotional well-being. Coding of apps included primary incorporated techniques and mental health focus. Behavioral data on real-world usage were obtained from a panel that provides aggregated nonpersonal information on user engagement with mobile apps. RESULTS: In total, 93 apps met the inclusion criteria (installs: median 100,000, IQR 90,000). The median percentage of daily active users (open rate) was 4.0% (IQR 4.7%) with a difference between trackers (median 6.3%, IQR 10.2%) and peer-support apps (median 17.0%) versus breathing exercise apps (median 1.6%, IQR 1.6%; all z≥3.42, all P<.001). Among active users, daily minutes of use were significantly higher for mindfulness/meditation (median 21.47, IQR 15.00) and peer support (median 35.08, n=2) apps than for apps incorporating other techniques (tracker, breathing exercise, psychoeducation: medians range 3.53-8.32; all z≥2.11, all P<.05). The medians of app 15-day and 30-day retention rates were 3.9% (IQR 10.3%) and 3.3% (IQR 6.2%), respectively. On day 30, peer support (median 8.9%, n=2), mindfulness/meditation (median 4.7%, IQR 6.2%), and tracker apps (median 6.1%, IQR 20.4%) had significantly higher retention rates than breathing exercise apps (median 0.0%, IQR 0.0%; all z≥2.18, all P≤.04). The pattern of daily use presented a descriptive peak toward the evening for apps incorporating most techniques (tracker, psychoeducation, and peer support) except mindfulness/meditation, which exhibited two peaks (morning and night). CONCLUSIONS: Although the number of app installs and daily active minutes of use may seem high, only a small portion of users actually used the apps for a long period of time. More studies using different datasets are needed to understand this phenomenon and the ways in which users self-manage their condition in real-world settings.
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spelling pubmed-67857202019-10-31 Objective User Engagement With Mental Health Apps: Systematic Search and Panel-Based Usage Analysis Baumel, Amit Muench, Frederick Edan, Stav Kane, John M J Med Internet Res Original Paper BACKGROUND: Understanding patterns of real-world usage of mental health apps is key to maximizing their potential to increase public self-management of care. Although developer-led studies have published results on the use of mental health apps in real-world settings, no study yet has systematically examined usage patterns of a large sample of mental health apps relying on independently collected data. OBJECTIVE: Our aim is to present real-world objective data on user engagement with popular mental health apps. METHODS: A systematic engine search was conducted using Google Play to identify Android apps with 10,000 installs or more targeting anxiety, depression, or emotional well-being. Coding of apps included primary incorporated techniques and mental health focus. Behavioral data on real-world usage were obtained from a panel that provides aggregated nonpersonal information on user engagement with mobile apps. RESULTS: In total, 93 apps met the inclusion criteria (installs: median 100,000, IQR 90,000). The median percentage of daily active users (open rate) was 4.0% (IQR 4.7%) with a difference between trackers (median 6.3%, IQR 10.2%) and peer-support apps (median 17.0%) versus breathing exercise apps (median 1.6%, IQR 1.6%; all z≥3.42, all P<.001). Among active users, daily minutes of use were significantly higher for mindfulness/meditation (median 21.47, IQR 15.00) and peer support (median 35.08, n=2) apps than for apps incorporating other techniques (tracker, breathing exercise, psychoeducation: medians range 3.53-8.32; all z≥2.11, all P<.05). The medians of app 15-day and 30-day retention rates were 3.9% (IQR 10.3%) and 3.3% (IQR 6.2%), respectively. On day 30, peer support (median 8.9%, n=2), mindfulness/meditation (median 4.7%, IQR 6.2%), and tracker apps (median 6.1%, IQR 20.4%) had significantly higher retention rates than breathing exercise apps (median 0.0%, IQR 0.0%; all z≥2.18, all P≤.04). The pattern of daily use presented a descriptive peak toward the evening for apps incorporating most techniques (tracker, psychoeducation, and peer support) except mindfulness/meditation, which exhibited two peaks (morning and night). CONCLUSIONS: Although the number of app installs and daily active minutes of use may seem high, only a small portion of users actually used the apps for a long period of time. More studies using different datasets are needed to understand this phenomenon and the ways in which users self-manage their condition in real-world settings. JMIR Publications 2019-09-25 /pmc/articles/PMC6785720/ /pubmed/31573916 http://dx.doi.org/10.2196/14567 Text en ©Amit Baumel, Frederick Muench, Stav Edan, John M Kane. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 25.09.2019. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
spellingShingle Original Paper
Baumel, Amit
Muench, Frederick
Edan, Stav
Kane, John M
Objective User Engagement With Mental Health Apps: Systematic Search and Panel-Based Usage Analysis
title Objective User Engagement With Mental Health Apps: Systematic Search and Panel-Based Usage Analysis
title_full Objective User Engagement With Mental Health Apps: Systematic Search and Panel-Based Usage Analysis
title_fullStr Objective User Engagement With Mental Health Apps: Systematic Search and Panel-Based Usage Analysis
title_full_unstemmed Objective User Engagement With Mental Health Apps: Systematic Search and Panel-Based Usage Analysis
title_short Objective User Engagement With Mental Health Apps: Systematic Search and Panel-Based Usage Analysis
title_sort objective user engagement with mental health apps: systematic search and panel-based usage analysis
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6785720/
https://www.ncbi.nlm.nih.gov/pubmed/31573916
http://dx.doi.org/10.2196/14567
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