State-Based Automation for Time-Restricted Eating Adherence
Abstract
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.
- Publication:
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arXiv e-prints
- Pub Date:
- June 2024
- DOI:
- 10.48550/arXiv.2406.18718
- arXiv:
- arXiv:2406.18718
- Bibcode:
- 2024arXiv240618718A
- Keywords:
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- Computer Science - Human-Computer Interaction;
- Electrical Engineering and Systems Science - Systems and Control
- E-Print:
- 8 pages, 4 figures, submitted to AMIA 2024 Annual Symposium