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

Abstract

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 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 two 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.

Assessing mental health apps marketplaces with objective metrics from 29,190 data points from 278 apps

“…31 As other authors have emphasized, however, simply offering evidence-based components and features does not necessarily mean that an app itself is efficacious. 32 Our results confirm reports of overall lack of evidence in the mental health app space. Less than 25% of apps were supported by a feasibility or efficacy study according to our results, which does not take into account the quality (and biases) of studies.…”

“…This finding corresponds to prior work highlighting the lack of comprehensive apps that would facilitate multiple diverse uses, as opposed to a single function or more limited set of uses 31 . As other authors have emphasized, however, simply offering evidence‐based components and features does not necessarily mean that an app itself is efficacious 32 …”

Commonly Reported Problems and Coping Strategies During the COVID-19 Crisis: A Survey of Graduate and Professional Students

“…Because these sources focused on common EBPs in youth psychotherapies, we also surveyed empirically supported treatment manuals for adults with depression and anxiety. This full search, distillation, and matching procedure is described elsewhere (for full details see Wasil et al, 2019Wasil et al, , 2020a. In brief, we reviewed metaanalyses (e.g., Chambless and Hollon, 1998;Cuijpers et al, 2013) and relevant chapters of A Guide to Treatments that Work (Nathan and Gorman, 2015) to identify empirically supported interventions for adults.…”

Is there an app for that? A review of popular mental health and wellness apps

“…Third, we described the applications qualitatively without applying a formal codebook. This approach allowed us to characterize the apps in greater detail and nuance; however, this approach can be supplemented DESCRIBING POPULAR MENTAL HEALTH APPS by formal content analyses that code for the presence or absence of specific content (see Bry et al, 2018;Shen et al, 2015;Wasil et al, 2019;Wasil, Gillespie, Patel, et al, 2020). Relatedly, we did not conduct a thorough technological evaluation that includes their ease of usage or the presence of technical errors (e.g., glitches, application crashes).…”