A Flexible Micro-Randomized Trial Design and Sample Size Considerations

TL;DR

This paper introduces FlexiMRT, a flexible micro-randomized trial design that allows adding categories during the study, with new statistical tools and a practical R implementation, improving adaptive intervention testing.

Contribution

It proposes a novel flexible MRT framework that accommodates evolving component categories and provides new sample size calculation methods and software tools.

Findings

Simulation studies validate the sample size calculator.

The R shiny application facilitates practical implementation.

FlexiMRT enhances adaptive intervention evaluation.

Abstract

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.