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.

翻译：制定并执行研究方案是医学研究的基础组成部分。随着参与者交互的研究复杂性增加，将研究方案转化为支持性应用程序代码变得具有挑战性。肯塔基大学与亚利桑那州立大学合作开展了一项研究，旨在确定时间限制饮食对改善绝经后女性代谢风险的有效性。本研究采用基于图的方法来监测和支持对指定时间表的依从性，通过对参与者状态进行验证和逐步审核，从而得出可靠结论。一个由参与者图谱驱动的短信服务自动管理交互并收集数据。随后，研究团队可通过网站访问参与者数据，实现查看、管理和导出功能。本文提出了一种用于时间限制饮食研究的参与者自动管理系统，该系统消除了与参与者之间耗时的交互环节。