A smartphone application for semi-controlled collection of objective eating behavior data from multiple subjects

Area of Science:

• Behavioral Science
• Human-Computer Interaction
• Digital Health

Background:

• Eating behavior is linked to health issues like obesity and eating disorders.
• Smartphones show potential for monitoring and modifying eating behaviors.
• Existing smartphone apps lack support for semi-controlled eating behavior data collection in research.

Purpose of the Study:

• Introduce ASApp, a smartphone application for integrated collection of eating behavior data.
• Address the gap in tools for collecting heterogeneous objective and subjective eating behavior data.
• Facilitate large-scale, naturalistic human subject research (HSR) on eating behaviors.

Main Methods:

• ASApp integrates objective (sensor-acquired) and subjective (self-reported) data collection.
• Data includes dietary self-assessment, food weight timeseries, meal photographs, and quantitative eating behavior indicators.
• A robust, quick, and straightforward data collection protocol is employed for semi-controlled HSR.

Main Results:

• ASApp functionalities and user interfaces for researchers and participants are detailed.
• The app was successfully deployed in an in-house study and the real-life SPLENDID study.
• Evaluation showed ASApp to be attractive, usable, and technically sound.

Conclusions:

• ASApp is a novel smartphone application for integrated eating behavior data collection.
• It supports researchers in gathering heterogeneous data for semi-controlled HSR.
• The app provides a concise yet rich dataset for studying eating behaviors.