There is a non-evidence-based app for that: A systematic review and mixed methods analysis of depression- and anxiety-related apps that incorporate unrecognized techniques

Abstract

Background: Recent studies have utilized available online data to examine the impact of depression- and anxiety-related apps that incorporate evidence-based techniques; however, the impact of apps incorporating non-evidence-based techniques is unknown. Understanding this impact is important in order to assess the potential benefits or harm from their use.

Methods: We systematically reviewed apps incorporating relevant techniques aimed at depression- and anxiety-related conditions, found through Google Play search. We conducted quantitative and qualitative analyses of user reviews, and analyzed app usage utilizing an independent user panel.

Results: Compared to apps incorporating evidence-based techniques (n = 14), user ratings of apps classified as non-evidence-based (n = 27) were lower (4.0 versus 4.5, p=.001, η²=0.24) and a smaller percentage of users found these apps to be beneficial for mental health (76.2% versus 100%, p=.003, η²=0.23). Users found apps incorporating non-evidence-based techniques to be mostly helpful in providing in-the-moment relief; however, some users described these apps as containing content that could be harmful for a person in such a mental state.

Limitations: The data do not enable the differentiation of user experiences based on user groups (e.g. according to the severity of symptoms), which should be examined in future studies.

Conclusions: This study indicates that depression and anxiety apps incorporating non-evidence-based techniques are viewed less favorably and have more potential to cause harm. However, many users found them helpful mostly in providing in-the-moment relief. Examining user experiences with these apps is an important way to learn about unmet user needs and potential benefits or harm.

Keywords: Anxiety; Depression; Digital; Intervention; eHealth; mHealth.