Reassessing evidence-based content in popular smartphone apps for depression and anxiety: Developing and applying user-adjusted analyses.


Journal

Journal of consulting and clinical psychology
ISSN: 1939-2117
Titre abrégé: J Consult Clin Psychol
Pays: United States
ID NLM: 0136553

Informations de publication

Date de publication:
Nov 2020
Historique:
pubmed: 4 9 2020
medline: 2 3 2021
entrez: 4 9 2020
Statut: ppublish

Résumé

To assess the dissemination of evidence-based content within smartphone apps for depression and anxiety by developing and applying We searched the Apple App Store and Google Play Store and identified 27 apps within the top search hits, which real-world users are most likely to encounter. We developed a codebook of evidence-based treatment elements by reviewing past research on empirically supported treatments. We coded the apps to develop an initial tally of the frequency of treatment elements within the mental health (MH) apps. We then developed and applied user-adjusted analysis to refine the tallies based on each app's number of monthly active users. The 2 most popular apps were responsible for 90% of monthly active users, and user-adjusted analysis markedly altered conclusions of prior reports based on tallies alone. For example, mindfulness was present in 37% of apps but reached 96% of monthly active users, cognitive restructuring was present in 22% but reached only 2%, and exposure was present in 7% but reached only 0.0004%. The potential impact of MH apps on mental health may be best evaluated via assessment that combines tallies of evidence-based content with data on the content users are actually accessing. Given wide variation in the popularity of MH apps, findings weighted by usage data may differ markedly from findings based on raw tallies alone. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Identifiants

pubmed: 32881542
pii: 2020-65097-001
doi: 10.1037/ccp0000604
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

983-993

Auteurs

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Classifications MeSH