User engagement and utilisation of an app for anxiety management: analysis and evaluation of usage patterns (Preprint)
BACKGROUND SAM is a mobile app providing self-help for anxiety management. Launched in 2013, the app has achieved over a 1 million downloads and favourable ratings on the platform app stores. Key features of the app are anxiety monitoring, self-help techniques and social support via an online forum (“the social cloud”). This paper presents unique insights into e-mental health app usage patterns and explores user behaviour and usage of self-help techniques. OBJECTIVE To investigate behavioural engagement and to establish discernible usage patterns of the app linked to the features of: anxiety monitoring, rating of self-help techniques and social participation. METHODS We use data mining techniques on aggregate data from registered users of the app’s cloud services RESULTS Engagement in general conforms to common online participation patterns, with an inverted pyramid or “funnel” of engagement of increasing intensity. We further identify four distinct groups of behavioural engagement, differentiated by levels of activity in anxiety monitoring and social feature usage. Anxiety levels among all monitoring users show a marked reduction in the first few days of usage, with some “bounce back” effect thereafter. A small group of users with demonstrable long-term anxiety reduction (using a robust measure) typically monitored for 12-110 days with 10-30 discrete updates and showed low levels of social participation. CONCLUSIONS The data supports our expectation of different usage patterns given flexible user journeys and varying commitment in an unstructured mobile usage setting. We nevertheless show an aggregate trend of reduction in self-reported anxiety across all minimally engaged users. We find several commonalities between these patterns and traditional therapy engagement.