Technological advancements have made it possible to deliver mobile health interventions to individuals. A novel framework that has emerged from such advancements is the just-in-time adaptive intervention (JITAI), which aims to suggest the right support to the individuals when their needs arise. The micro-randomized trial (MRT) design has been proposed recently to test the proximal effects of these JITAIs. However, the extant MRT framework only considers components with a fixed number of categories added at the beginning of the study. We propose a flexible MRT (FlexiMRT) design which allows addition of more categories to the components during the study. The proposed design is motivated by collaboration on the DIAMANTE study, which learns to deliver text messages to encourage physical activity among the patients with diabetes and depression. We developed a new test statistic and the corresponding sample size calculator for the FlexiMRT using an approach similar to the generalized estimating equation for longitudinal data. Simulation studies were conducted to evaluate the sample size calculators and an R shiny application for the calculators was developed.

翻译：技术进步使得向个体提供移动健康干预成为可能。由此衍生出的一个新颖框架是即时自适应干预（JITAI），旨在当个体需求产生时提供恰当支持。微随机试验（MRT）设计近期被提出用于检验这些JITAI的即时效应。然而，现有MRT框架仅考虑在研究起始时添加固定类别数量的组件。我们提出一种灵活的MRT（FlexiMRT）设计，允许在研究过程中向组件添加更多类别。该设计受参与DIAMANTE研究的合作启发，该研究致力于通过发送短信鼓励糖尿病合并抑郁症患者增加体力活动。我们采用类似纵向数据广义估计方程的方法，为FlexiMRT开发了新的检验统计量及相应的样本量计算器。通过模拟研究评估了样本量计算器的性能，并开发了基于R shiny的计算器应用。