This week we will be reviewing and discussing an article published last month in the Journal of Medical Internet Research written by Zhang, Nocholas, Knapp, Graham, Gray, Kwasny, Reddy, and Mohr. In the article, Clinically Meaningful Use of Mental Health Apps and its Effects on Depression: Mixed Methods Study, the authors examine a variety of mental health app use behaviors and discuss the variability in outcomes related to each specific behavior.

What did they do?

The authors of this study conducted a secondary data analysis of mental health app use data examining 13 different mental health apps. They identified distinct clusters of behaviors and analyzed the resulting outcomes on mental health status relative to those behaviors.

Why did they do it?

As we have highlighted here on our blog before, mobile phone apps have become an important supplemental component in mental health treatment. The authors of this article specifically highlight that there is very little research targeting effective use of mental health apps. Research examining engagement metrics has typically been based on quantitative analysis, rather than examining user interactions with specific components of mental health apps. The authors of this study recognized the accessibility and diversity that mobile mental health apps can provide to the mental health world, and thus sought to extend the literature by examining ways in which mental health apps can be made more effective based on user engagement behaviors.

How did they do it?

In a secondary data analysis, the authors examined data from 301 participants (M age = 37 years) utilizing 12 clinical mental health apps covering a range of behavioral and psychological treatment strategies targeted at the improvement of depressive and anxiety symptoms. There were four conditions in this study design; the coaching condition received 8 weeks of coaching via text message aimed at improving and supporting app engagement, the self-guided condition had no continuous contact with coaches, the recommendation condition received specific app recommendations on a weekly basis, and the non-recommendation condition allowed participants to freely explore the apps by themselves.

The authors categorized two types of app use: clinically meaningful use, and generic use. 67 behaviors were examined and deemed clinically meaningful, these behaviors were then grouped into 6 distinct types:

  1. Viewing/listening (e.g. viewing a coping card, listening to relaxing audio)
  2. Creating/inputting (e.g. creating a self-affirming statement)
  3. Setting goals (e.g. creating a checklist and selecting a weekly goal)
  4. Scheduling (e.g. adding/changing a reminder time)
  5. Tracking (e.g. creating a sleep log)
  6. Reviewing (e.g. going over past activities and lessons)

To assess depression and anxiety outcomes, the Patient Health Questionnaire-9 (PHQ-9) and the Generalized Anxiety Disorder-7 (GAD-7) were used, where higher scores reflect greater problems with depression or anxiety.

What did they find?

The first goal of this study was to identify mobile mental health use behaviors that are most effective in decreasing depression and anxiety symptoms. The authors conducted a principal component analysis on the 6 previously identified groups of clinically meaningful behaviors to determine which behaviors could be grouped together. Their analysis revealed 3 distinct groups: Learning, which includes viewing and creating; Goal setting, which includes setting goals and scheduling; and Self-tracking, which includes reviewing and tracking. Overall, the median frequency of clinically meaningful app use was 400 sessions. For generic app use, the median number of app use sessions was 184.

The second goal of this study was to determine how app use behaviors influence depression and anxiety outcomes. The results showed that different types of clinically meaningful activities (i.e. learning, goal setting, and self-tracking) had varied effects on outcomes. Self-tracking at all levels of intensity was related to improvement in depression symptoms, and moderate intensity of learning and goal setting predicted improvement in depression symptoms as assessed via the PHQ-9. Anxiety (measured by the GAD-7), at the end of the 8-week treatment was not significantly associated with any of the 3 clusters of meaningful activities or overall clinically meaningful app use.

What does it all mean (our take)?

It’s not just about the availability of technology that will ultimately make the difference, it’s about how patients actually use it. Not surprisingly, engagement is critical. Continuing to reimagine the ways that patients interact with virtual environments will ultimately lead to maximization of use - and at that time, we believe that the true positive effect of integrating technology with healthcare will be realized. We’re certainly moving in the right direction, and we are really looking forward to seeing what is to come!

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