Specifying the Efficacy of Digital Therapeutic Tools for Depression and Anxiety: Retrospective, 2-Cohort, Real-World Analysis

BackgroundDepression and anxiety are the main sources of work and social disabilities as well as health-related problems around the world. Digital therapeutic solutions using cognitive behavioral therapy have demonstrated efficacy in depression and anxiety. A common goal of digital health apps is to increase user digital engagement to improve outcomes. However, there is a limited understanding of the association between digital platform components and clinical outcomes. ObjectiveThe aim of the study is to investigate the contribution of specific digital engagement tools to mental health conditions. We hypothesized that participation in coaching sessions and breathing exercises would be associated with a reduction in depression and anxiety. MethodsDepression and general anxiety symptoms were evaluated in real-world data cohorts using the digital health platform for digital intervention and monitoring change. This retrospective real-world analysis of users on a mobile platform–based treatment followed two cohorts of people: (1) users who started with moderate levels of depression and completed at least 2 depression assessments (n=519) and (2) users who started with moderate levels of anxiety and completed at least 2 anxiety assessments (n=474). Levels of depression (Patient Health Questionnaire-9) and anxiety (Generalized Anxiety Disorder-7) were tracked throughout the first 16 weeks. A piecewise mixed-effects model was applied to model the trajectories of the Patient Health Questionnaire-9 and the Generalized Anxiety Disorder-7 mean scores in 2 segments (1-6 weeks and 7-16 weeks). Finally, simple slope analysis was used for the interpretation of the interactions probing the moderators: coaching sessions and breathing exercises in both depression and anxiety cohorts. ResultsAnalysis revealed a significant decrease in depression symptoms (β=–.37, 95% CI –0.46 to 0.28; P≤.001) during the period of weeks 1-6 of app use, which was maintained during the period of 7-16 weeks. Coach interaction significantly moderated the reduction in depression symptoms during the period of weeks 1-6 (β=–.03, 95% CI –0.05 to –0.001; P=.02). A significant decrease in anxiety symptoms (β=–.41, 95% CI –0.50 to –0.33; P≤.001) was revealed during the period of 1-6 weeks, which was maintained during the period of 7-16 weeks. Breathing exercises significantly moderated the reduction in anxiety symptoms during the period of 1-6 weeks (β=–.07, 95% CI –0.14 to –0.01; P=.04). ConclusionsThis study demonstrated general improvement followed by a period of stability of depression and anxiety symptoms associated with cognitive behavioral therapy–based digital intervention. Interestingly, engagement with a coaching session but not a breathing exercise was associated with a reduction in depression symptoms. Moreover, breathing exercise but not engagement with a coaching session was associated with a reduction of anxiety symptoms. These findings emphasize the importance of using a personalized approach to behavioral health during digital health interventions

Glycemic Management by a Digital Therapeutic Platform across Racial/Ethnic Groups: A Retrospective Cohort Study

Significant racial/ethnic disparities in healthcare and diabetes technology use have been observed in Type 2 diabetes mellitus (T2DM), which are associated with nonengagement in diabetes self-management and out-of-range glycemia. This study aimed to assess whether there were differences in the blood glucose levels achieved by several racial/ethnic groups using the same digital tool. Study objectives were to determine whether engagement with the digital tool and blood glucose levels differ among ethnic groups, and to determine whether any differences in the in-target-glycemia are related to engagement levels. The retrospective real-world analysis followed a group of 1000 people with Type 2 diabetes who used the DarioTM digital therapeutic platform over 12 months. Participants included in the study had a blood glucose average > 180 mg/dL (hyperglycemia, high-risk) in their first month. The differences between/within the groups’ average blood glucose level (Avg.bg) and glycemic variability were evaluated. Furthermore, three general linear models were constructed to predict the Avg.bg by the number of blood glucose measurements (Bgm) in Model 1 (with the moderator White persons (WP)/people from racial and ethnic minority groups (REM)) and by the frequency of measurements by months (F.m) within REM and WP in Model 2 and Model 3, respectively. The Avg.bg was significantly reduced in each group over a year with no differences between REM/WP users. Blood glucose measurements in Model 1 and frequency of measurements by months in Model 2 and Model 3 predicted the Avg.bg (β1 = −0.20, p = 0.045; β2 = −4.38, p = 0.009; β3= −3.77, p < 0.001, respectively). Findings indicate a positive association between digital engagement and glycemia, with no differences between REM and WP participants