Background:

Binge eating is a subjective loss of control while eating, leading to the consumption of large amounts of food. It can cause significant emotional distress and is often accompanied by purging behaviors (eg, meal skipping, over-exercising or vomiting).

Objective:

The aim of this study was to explore the potential for mobile sensing to detect indicators for binge eating episodes, with a view toward informing the design of future context-aware mobile interventions.

Methods:

Our study was conducted in two stages. The first involved the development of the DeMMI app. As part of this, we conducted a consultation session to explore whether the types of sensor data we were proposing to capture were seen to be useful and appropriate, as well as gathering feedback on some specific app features relating to self-report. The second stage involved carrying out a 6-week period of data collection with 10 participants experiencing binge eating (logging both their mood and episodes of binge eating) and 10 control participants (logging only mood). An optional interview was conducted post-study discussing their experience with using the app, 8 participants (3 binge eating and 5 controls) consented.

Results:

Findings showed unique differences in the types of sensor data that were triangulated with individuals’ episodes (with nearby Bluetooth devices, screen and app usage features, mobility features, and mood scores showing relevance). Participants had a largely positive opinion about the app, its unobtrusive role, and its ease of use. Interacting with the app increased their awareness of and reflection around mood and their phone usage patterns. Moreover, they expressed no privacy concerns as the study information sheet alleviated these.

Conclusions:

In this study, we contribute a series of recommendations for future studies wishing to scale our approach, and for the design of bespoke mobile interventions to support this population.