TY - JOUR
T1 - A flexible micro-randomized trial design and sample size considerations
AU - Xu, Jing
AU - Yan, Xiaoxi
AU - Figueroa, Caroline
AU - Williams, Joseph Jay
AU - Chakraborty, Bibhas
PY - 2023
Y1 - 2023
N2 - 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, which aims to suggest the right support to the individuals when their needs arise. The micro-randomized trial design has been proposed recently to test the proximal effects of the components of these just-in-time adaptive interventions. However, the extant micro-randomized trial framework only considers components with a fixed number of categories added at the beginning of the study. We propose a more flexible micro-randomized trial design which allows addition of more categories to the components during the study. Note that the number and timing of the categories added during the study need to be fixed initially. The proposed design is motivated by collaboration on the Diabetes and Mental Health Adaptive Notification Tracking and Evaluation study, which learns to deliver effective text messages to encourage physical activity among patients with diabetes and depression. We developed a new test statistic and the corresponding sample size calculator for the flexible micro-randomized trial 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.
AB - 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, which aims to suggest the right support to the individuals when their needs arise. The micro-randomized trial design has been proposed recently to test the proximal effects of the components of these just-in-time adaptive interventions. However, the extant micro-randomized trial framework only considers components with a fixed number of categories added at the beginning of the study. We propose a more flexible micro-randomized trial design which allows addition of more categories to the components during the study. Note that the number and timing of the categories added during the study need to be fixed initially. The proposed design is motivated by collaboration on the Diabetes and Mental Health Adaptive Notification Tracking and Evaluation study, which learns to deliver effective text messages to encourage physical activity among patients with diabetes and depression. We developed a new test statistic and the corresponding sample size calculator for the flexible micro-randomized trial 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.
KW - generalized estimating equation
KW - just-in-time adaptive intervention
KW - longitudinaldata
KW - mHealth
KW - micro-randomized trial
UR - http://www.scopus.com/inward/record.url?scp=85165910690&partnerID=8YFLogxK
U2 - 10.1177/09622802231188513
DO - 10.1177/09622802231188513
M3 - Article
C2 - 37491804
AN - SCOPUS:85165910690
SN - 0962-2802
VL - 32
SP - 1766
EP - 1783
JO - Statistical Methods in Medical Research
JF - Statistical Methods in Medical Research
IS - 9
ER -