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Assessing Digital Phenotyping for App Recommendations and Sustained Engagement: Cohort Study.
Bridget Dwyer1, Matthew Flathers1, James Burns1
1Division of Digital Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States.
JMIR Formative Research
|November 19, 2024
Summary
Digital phenotyping can match individuals to mental health apps, potentially boosting engagement. This approach, using smartphone data, showed higher engagement in a pilot study, suggesting feasibility for real-world application.
Area of Science:
- Digital health
- Mental health technology
- Behavioral science
Background:
- Low engagement with mental health apps limits their effectiveness.
- Personalized app matching may enhance user engagement.
- Novel approaches are needed to connect individuals with suitable digital mental health tools.
Purpose of the Study:
- To pilot digital phenotyping for matching individuals to mental health apps.
- To assess if data-driven recommendations increase app engagement.
- To evaluate the feasibility of using smartphone sensor data for app selection.
Main Methods:
- Collected digital phenotyping data using the mindLAMP app.
- Randomly assigned participants to a digital phenotyping arm (with recommendations) or a control arm.
- Measured engagement using objective screen time, self-report, and the Digital Working Alliance Inventory.
Main Results:
- Higher engagement (screen time, alliance scores) observed in the digital phenotyping arm.
- Most participants used apps for depression or anxiety.
- No correlation found between self-reported and objective engagement metrics.
Conclusions:
- Digital phenotyping for mental health app recommendation is feasible and may improve engagement.
- The approach is generalizable and practical for real-world implementation.
- Future advancements in digital phenotyping promise more personalized recommendations.
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