Introducing FRED: Software for Generating Feedback Reports for Ecological Momentary Assessment Data

Area of Science:

• Digital Health
• Behavioral Science
• Data Science

Background:

• Ecological Momentary Assessment (EMA) collects real-time data but can burden participants, leading to compliance issues.
• Existing feedback frameworks for EMA data are not scalable for large participant groups.
• Citizen science models suggest participant data access can boost motivation.

Purpose of the Study:

• To introduce FRED (Feedback Reports on EMA Data), an interactive tool for generating personalized reports for numerous EMA participants.
• To address scalability challenges in providing feedback for large-scale EMA studies.
• To enhance participant motivation and compliance in EMA research.

Main Methods:

• Developed FRED, an interactive online tool using the R programming language and Shiny app framework.
• Integrated FRED with data from the WARN-D study (867 participants, 85 days).
• FRED offers descriptive statistics, time-series visualizations, and network analyses of EMA variables.

Main Results:

• FRED successfully generated personalized data reports for a large cohort (867 participants).
• The tool provides accessible, interactive data exploration for participants.
• The FRED infrastructure is adaptable for various research and clinical settings.

Conclusions:

• FRED offers a scalable solution for providing personalized data feedback in EMA studies.
• The tool has the potential to improve participant engagement and data quality in digital health research.
• FRED's open-source nature promotes its adoption and adaptation for diverse applications.