Dempsey Walter, Liao Peng, Kumar Santosh, Murphy Susan A
University of Michigan.
University of Memphis.
Ann Appl Stat. 2020 Jun;14(2):661-684. doi: 10.1214/19-aoas1293. Epub 2020 Jun 29.
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 design. In these designs, each individual is randomized to treatment repeatedly at times determined by predictions of risk. These may be impacted by prior treatment. We describe the statistical challenges and detail how they can be met.
移动设备和可穿戴传感器领域的技术进步有助于克服医疗服务提供过程中的障碍,从而能够在任何时间、任何地点提供行为治疗。在此,我们讨论我们在一项移动健康戒烟干预研究设计方面的工作,其目的是评估在压力时刻发送的提醒是否会在短期内减轻/预防压力,以及这种效果在研究过程中是否会随时间变化。在这项工作中出现了多个统计方面的挑战,从而促成了该设计的形成。在这些设计中,每个个体在由风险预测所确定的时间被反复随机分配到治疗组。这些可能会受到先前治疗的影响。我们描述了统计方面的挑战,并详细说明了如何应对这些挑战。