OBJECTIVE: To examine the frequency of evidence-based treatment elements in popular smartphone apps for eating disorders (EDs), and to characterize the extent to which real-world users encounter different elements. METHOD: We searched the Apple App Store and Google Play Store for apps offering treatment or support to individuals with EDs. Then, we created a codebook of 47 elements found in evidence-based treatments for EDs. We examined the presence or absence of each element within each ED app. We also acquired estimates of the monthly active users (MAU) of each app. RESULTS: The ED apps (n = 28) included a median of nine elements of empirically supported treatments (mean = 9.46, SD = 6.28). Four apps accounted for 96% of all MAU. MAU-adjusted analyses revealed that several elements are reaching more users than raw frequency tallies would suggest. For example, assessments were included in 32% of apps, but 84% of users used an app with assessments. Similar trends were found for cognitive restructuring (21% of apps, 56% of MAU), activity scheduling (39%, 57%), and self-monitoring (14%, 46%). Problem solving, exposure, and relapse prevention strategies, elements that are prominent in face-to-face empirically supported treatments, were rarely included in the apps. DISCUSSION: Evidence-based content is commonly included in ED apps, with certain elements reaching more users than others. Additionally, the top four apps are responsible for nearly all active users. We recommend that ED clinicians and researchers familiarize themselves with these apps-those that patients are most likely to encounter.
OBJECTIVE: To examine the frequency of evidence-based treatment elements in popular smartphone apps for eating disorders (EDs), and to characterize the extent to which real-world users encounter different elements. METHOD: We searched the Apple App Store and Google Play Store for apps offering treatment or support to individuals with EDs. Then, we created a codebook of 47 elements found in evidence-based treatments for EDs. We examined the presence or absence of each element within each ED app. We also acquired estimates of the monthly active users (MAU) of each app. RESULTS: The ED apps (n = 28) included a median of nine elements of empirically supported treatments (mean = 9.46, SD = 6.28). Four apps accounted for 96% of all MAU. MAU-adjusted analyses revealed that several elements are reaching more users than raw frequency tallies would suggest. For example, assessments were included in 32% of apps, but 84% of users used an app with assessments. Similar trends were found for cognitive restructuring (21% of apps, 56% of MAU), activity scheduling (39%, 57%), and self-monitoring (14%, 46%). Problem solving, exposure, and relapse prevention strategies, elements that are prominent in face-to-face empirically supported treatments, were rarely included in the apps. DISCUSSION: Evidence-based content is commonly included in ED apps, with certain elements reaching more users than others. Additionally, the top four apps are responsible for nearly all active users. We recommend that ED clinicians and researchers familiarize themselves with these apps-those that patients are most likely to encounter.
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