Monitoring and Modeling Family Eating Dynamics

M2FED proposes an integrated system of in-home beacons, wireless and wearable sensors, and smartphones that provide ongoing, synchronized real-time data on in-home eating behaviors and theory-based process variables.

This rich data will be aggregated to generate real-time contextual FED models using systems networks models. Key activities that precede target behaviors will be identified in order to develop and optimize future just-in-time, adaptive interventions.

Overview

Recent data suggest that 31% of children in the United States are overweight or obese, which translates to 4-5 million children in the United States. Children who are obese are at an increased risk for many negative health consequences in childhood and in adulthood, including orthopedic and endocrine conditions, cardiovascular disease, cancer and all-cause mortality.

This project attempts a dramatically different mobile health (mHealth) approach to childhood obesity by not focusing directly on diet and activity, but rather on family eating dynamics (FED). Recent discoveries in behavioral science have revealed that in-home FED – who is eating, when, where, with whom, and under what interpersonal stress and mood – has high potential to impact child as well as parent dietary intake and obesity rates.

The M2FED project is developing and deploying new methods for in-home sensing that monitor and model FED, allowing us to generate family-specific real-time FED system models.

Two key health-related scientific challenges are currently being investigated: (1) understanding obesity-related behaviors in real-time and in context, and (2) developing dynamic models of FED behavior that can serve as the foundations for future interventions to change family eating dynamics with just-in-time model-driven feedback.

This will be the first study that will model family dynamics in real-time to identify potential opportunities for innovative interventions in the future. The resulting data will enable the development of an unprecedented, in-depth understanding of every-day family interactions around food.

Apple Watch

Training Opportunities

Undergraduate Research Assistantships

USC undergraduate students in the Health Promotion and Disease Prevention & Global Health B.S. programs qualify to apply for undergraduate research assistantships.

Undergraduate students in other degree programs will also be considered. Assistantships are available as part of the HP 290 or HP 490 Direct Research course. Please contact Luz Antunez Castillo (antunez@usc.edu) if you are interested in applying for an assistantship.

Volunteer Opportunities

If you are not a USC undergraduate student but you are interested in working on the M2FED project, then please contact Luz Antunez Castillo (antunez@usc.edu) for more information.

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Get Involved

Join M2FED Community

We would like to invite Los Angeles families to participate in our new, cutting-edge project that uses technology to understand family eating patterns.

We are testing state-of-the-art technology that is designed to detect mood and eating. Our goal is to detect if mood affects your family’s eating patterns.

Help us understand how family eating habits can be harnessed to help families, and particularly children, eat healthy diets.

Partner with us

If your family is interested in participating in our study, then please contact Luz Antunez Castillo at (213) 821-1768 or antunez@usc.edu.

Alternatively, please provide your name, phone number, and email address and we will contact you with more information.

Best time to contact:

Our Team

Our multidisciplinary team consists of behavioral scientists, system scientists, obesity experts, computer scientists, and electrical engineers to address the challenges of capturing real-time behavior data for obesity prevention and treatment.

Donna Spruijt-Metz, PhD USC mHealth Collaboratory
M2FED Principal Investigator

John Stankovic, PhD University of Virginia
M2FED Principal Investigator

Kayla de la Haye, PhD Keck School of Medicine of USC
M2FED Co-Principal Investigator

John Lach, PhD University of Virginia
M2FED Co-Principal Investigator


Luz Antunez Castillo, MBA USC mHealth Collaboratory

Yadira Garcia, MAG USC mHealth Collaboratory

Sarah Preum University of Virginia

Meiyi Ma University of Virginia


Bas Weerman, MBA USC mHealth Collaboratory

Brooke Bell | PhD Candidate | USC mHealth Collaboratory

Ifat Emi University of Virginia

Ridwan Alam University of Virginia


Jessica Rayo USC mHealth Collaboratory

Megri Kartounian USC mHealth Collaboratory

Zeya Chen University of Virginia

Rahim Adamu | MBA | MPH | Keck School of Medicine
USC mHealth Collaboratory


Asif Salekin University of Virginia

Nutta Homdee University of Virginia

Mohsin Ahmad University of Virginia

Abdeltawab Hendawi University of Virginia

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How can you support M2FED?

Please contact us at antunez@usc.edu and let's start a discussion.