Mobile Apps for Mental Health Issues: Meta-Review of Meta-Analyses.
anxiety
apps
depression
mental health
meta
review
Journal
JMIR mHealth and uHealth
ISSN: 2291-5222
Titre abrégé: JMIR Mhealth Uhealth
Pays: Canada
ID NLM: 101624439
Informations de publication
Date de publication:
29 05 2020
29 05 2020
Historique:
received:
13
12
2019
accepted:
26
02
2020
revised:
11
02
2020
pubmed:
30
4
2020
medline:
28
4
2021
entrez:
30
4
2020
Statut:
epublish
Résumé
Mental health apps have great potential to help people needing support to cope with distress or specific symptoms. In fact, there is an exponential increase in the number of mental health apps available on the internet, with less than 5% being actually studied. This study aimed to assess the quality of the available evidence regarding the use of mental health apps and to summarize the results obtained so far. Systematic reviews and meta-analyses were searched, specifically for mobile apps on mental health issues or symptoms, and rated using the Grading of Recommendations Assessment, Development and Evaluation system. A total of 7 meta-analyses were carefully reviewed and rated. Although some meta-analyses looked at any mental health issue and analyzed the data together, these studies were of poorer quality and did not offer strong empirical support for the apps. Studies focusing specifically on anxiety symptoms or depressive symptoms were of moderate to high quality and generally had small to medium effect sizes. Similarly, the effects of apps on stress and quality of life tended to offer small to medium effects and were of moderate to high quality. Studies looking at stand-alone apps had smaller effect sizes but better empirical quality than studies looking at apps with guidance. The studies that included follow-ups mostly found a sustained impact of the app at an 11-week follow-up. This meta-review revealed that apps for anxiety and depression hold great promise with clear clinical advantages, either as stand-alone self-management or as adjunctive treatments. More meta-analyses and more quality studies are needed to recommend apps for other mental health issues or for specific populations.
Sections du résumé
BACKGROUND
Mental health apps have great potential to help people needing support to cope with distress or specific symptoms. In fact, there is an exponential increase in the number of mental health apps available on the internet, with less than 5% being actually studied.
OBJECTIVE
This study aimed to assess the quality of the available evidence regarding the use of mental health apps and to summarize the results obtained so far.
METHODS
Systematic reviews and meta-analyses were searched, specifically for mobile apps on mental health issues or symptoms, and rated using the Grading of Recommendations Assessment, Development and Evaluation system.
RESULTS
A total of 7 meta-analyses were carefully reviewed and rated. Although some meta-analyses looked at any mental health issue and analyzed the data together, these studies were of poorer quality and did not offer strong empirical support for the apps. Studies focusing specifically on anxiety symptoms or depressive symptoms were of moderate to high quality and generally had small to medium effect sizes. Similarly, the effects of apps on stress and quality of life tended to offer small to medium effects and were of moderate to high quality. Studies looking at stand-alone apps had smaller effect sizes but better empirical quality than studies looking at apps with guidance. The studies that included follow-ups mostly found a sustained impact of the app at an 11-week follow-up.
CONCLUSIONS
This meta-review revealed that apps for anxiety and depression hold great promise with clear clinical advantages, either as stand-alone self-management or as adjunctive treatments. More meta-analyses and more quality studies are needed to recommend apps for other mental health issues or for specific populations.
Identifiants
pubmed: 32348289
pii: v8i5e17458
doi: 10.2196/17458
pmc: PMC7293054
doi:
Types de publication
Journal Article
Meta-Analysis
Langues
eng
Sous-ensembles de citation
IM
Pagination
e17458Informations de copyright
©Tania Lecomte, Stéphane Potvin, Marc Corbière, Stéphane Guay, Crystal Samson, Briana Cloutier, Audrey Francoeur, Antoine Pennou, Yasser Khazaal. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 29.05.2020.
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