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Interaction and Engagement with an Anxiety Management App: Analysis Using Large-Scale Behavioral Data.
Paul Matthews1, Phil Topham2, Praminda Caleb-Solly2
1Data Science Group, Computer Science Research Centre, Department of Computer Science and Creative Technologies, University of the West of England, Bristol, United Kingdom.
JMIR Mental Health
|October 6, 2018
Summary
Self-help for Anxiety Management (SAM) app usage shows varied engagement patterns, with most users experiencing initial anxiety reduction. Long-term benefits were observed in a dedicated user group, highlighting potential in digital mental health tools.
Area of Science:
- Digital mental health
- eMental health app usage patterns
- Mobile health interventions
Background:
- Self-help for Anxiety Management (SAM) is a mobile app launched in 2013 for anxiety management.
- Features include anxiety monitoring, self-help techniques, and social support via "the Social Cloud" forum.
- The app has over one million downloads on iOS and Android platforms.
Purpose of the Study:
- Investigate behavioral engagement with the SAM app.
- Identify distinct usage patterns related to anxiety monitoring, self-help technique ratings, and social participation.
Main Methods:
- Utilized data mining techniques on aggregate data.
- Analyzed data from 105,380 registered users of the app's cloud services.
Main Results:
- User engagement followed a typical mobile usage funnel.
- Identified 4 distinct behavioral engagement groups based on monitoring and social feature use.
- Anxiety levels reduced initially for most users, with a subset showing sustained reduction over 12-110 days.
Conclusions:
- User journeys and commitment levels varied, leading to diverse usage patterns.
- Aggregate data showed a trend of reduced self-reported anxiety across minimally-engaged users.
- App-based behavioral patterns share commonalities with traditional therapy engagement.
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