Reassessing Evidence-Based Content in Popular Smartphone Apps for Depression and Anxiety: Developing and Applying User-Adjusted Analyses

Objective: To assess the dissemination of evidence-based content within smartphone apps for depression and anxiety by developing and applying user-adjusted analysis-a method for weighting app content based on each app's number of active users. Method: We searched the Apple App Store and Google...

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Veröffentlicht in:Journal of consulting and clinical psychology 2020-11, Vol.88 (11), p.983-993
Hauptverfasser: Wasil, Akash R, Gillespie, Sarah, Patel, Raveena, Petre, Annemarie, Venturo-Conerly, Katherine E, Shingleton, Rebecca M, Weisz, John R, DeRubeis, Robert J
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Sprache:eng
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Zusammenfassung:Objective: To assess the dissemination of evidence-based content within smartphone apps for depression and anxiety by developing and applying user-adjusted analysis-a method for weighting app content based on each app's number of active users. Method: 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. Results: 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%. Conclusions: 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. What is the public health significance of this article? Traditionally, analyses of mobile health and mental health applications have not accounted for the fact that apps differ markedly in their dissemination. In this study, we developed and applied a new method-user adjusted analysis-to better understand the content that users are receiving from mobile apps for depression and anxiety. From a public health perspective, this study (a) enhances our understanding of mobile apps for depression and anxiety and (b) presents a new way of estimating the impact of mobile apps.
ISSN:0022-006X
1939-2117
DOI:10.1037/ccp0000604