Abstract
Technological advancements in the field of mobile devices and wearable sensors have helped overcome obstacles in the delivery of care, making it possible to deliver behavioral treatments anytime and anywhere. Here, we discuss our work on the design of a mobile health smoking cessation intervention study with the goal of assessing whether reminders, delivered at times of stress, result in a reduction/prevention of stress in the near-term, and whether this effect changes with time in study. Multiple statistical challenges arose in this effort, leading to the development of the stratified micro-randomized trial design. In these designs, each individual is randomized to treatment repeatedly at times determined by predictions of risk. These risk times may be impacted by prior treatment. We describe the statistical challenges and detail how they can be met.
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