  Developing and enforcing study protocols is a foundational component of
medical research. As study complexity for participant interactions increases,
translating study protocols to supporting application code becomes challenging.
A collaboration exists between the University of Kentucky and Arizona State
University to determine the efficacy of time-restricted eating in improving
metabolic risk among postmenopausal women. This study utilizes a graph-based
approach to monitor and support adherence to a designated schedule, enabling
the validation and step-wise audit of participants' statuses to derive
dependable conclusions. A texting service, driven by a participant graph,
automatically manages interactions and collects data. Participant data is then
accessible to the research study team via a website, which enables viewing,
management, and exportation. This paper presents a system for automatically
managing participants in a time-restricted eating study that eliminates
time-consuming interactions with participants.
