JMIR Publications

ABSTRACT

Background:

While there are thousands of behavioral health focused mHealth applications (apps) available to consumers, users often quickly discontinue their use, which limits their therapeutic value. By varying the types and number of ways that users can interact with behavioral health apps, developers may be able to support greater therapeutic engagement and increase app stickiness and adherence.

Objective:

The main objective for this analysis was to systematically study and characterize the types of user interactivity features that are available in behavioral health mHealth apps, and then to examine if interactivity was associated with user satisfaction and app visibility.

Methods:

Using a modified PRISMA methodology, we searched several different app clearinghouse websites and identified 76 behavioral health apps that included some type of interactivity. We then filtered the results to ensure we were examining behavioral health apps and further refined our search to include apps that identified one or more of the following terms: peer or therapist forum, discussion, feedback, professional, licensed, buddy, friend, AI, chatbot, counselor, therapist, provider, mentor, bot, coach, message, comment, chat room, community, games, care team, connect, share, and support in the app descriptions. In the final group of 34 apps, we examined the presence of six types of human-machine interactivities: human-to-human with peers, human-to-human with providers, humans-to-artificial intelligence (AI), human-to-algorithms, human-to-data, and novel interactive smartphone modalities. We also downloaded information on app user ratings and visibility, as well as reviewed other key app features.

Results:

We found that on average, the 34 apps reviewed included 2.53 (sd 1.05) (range 1 to 5) features of interactivity. Most common types of interactivities were human-to-data (100%), followed by human-to-algorithm (42.9%). The least common type of interactivity was human-AI (20.0%). There were no significant associations between the total number of app interactivity features and user ratings or app visibility. We found that a full range of therapeutic interactivity features were not utilized in behavioral health apps.

Conclusions:

Ideally, app developers would do well to include more interactivity features in behavioral health apps to fully utilize the capability of smartphone technologies and increase app stickiness. Theoretically, increased user engagement would occur by using multiple types of user interactivity, thereby maximizing the benefits that a person would receive when using a behavioral health mHealth app. Clinical Trial: N/A