Department of Statistics, University of Michigan, Ann Arbor, MI, USA.
School of Information, University of Michigan, Ann Arbor, MI, USA.
Prev Sci. 2019 Jan;20(1):100-109. doi: 10.1007/s11121-017-0862-5.
Mobile Health (mHealth) interventions are behavioral interventions that are accessible to individuals in their daily lives via a mobile device. Most mHealth interventions consist of multiple intervention components. Some of the components are "pull" components, which require individuals to access the component on their mobile device at moments when they decide they need help. Other intervention components are "push" components, which are initiated by the intervention, not the individual, and are delivered via notifications or text messages. Micro-randomized trials (MRTs) have been developed to provide data to assess the effects of push intervention components on subsequent emotions and behavior. In this paper, we review the micro-randomized trial design and provide an approach to computing a standardized effect size for these intervention components. This effect size can be used to compare different push intervention components that may be included in an mHealth intervention. In addition, a standardized effect size can be used to inform sample size calculations for future MRTs. Here, the standardized effect size is a function of time because the push notifications can occur repeatedly over time. We illustrate this methodology using data from an MRT involving HeartSteps, an mHealth intervention for physical activity as part of the secondary prevention of heart disease.
移动健康 (mHealth) 干预措施是通过移动设备在个人日常生活中提供的行为干预措施。大多数 mHealth 干预措施由多个干预组件组成。其中一些组件是“拉”组件，需要个人在需要帮助时自行决定何时在移动设备上访问该组件。其他干预组件是“推”组件，由干预措施而不是个人发起，并通过通知或短信发送。微随机试验 (MRT) 已经开发出来，以提供数据来评估推送干预组件对后续情绪和行为的影响。在本文中，我们回顾了微随机试验设计，并提供了一种计算这些干预组件标准化效应大小的方法。该效应大小可用于比较可能包含在 mHealth 干预措施中的不同推送干预组件。此外，标准化效应大小可用于为未来的 MRT 提供样本量计算的信息。在这里，标准化效应大小是时间的函数，因为推送通知可以随着时间的推移重复发生。我们使用涉及 HeartSteps 的 MRT 的数据来说明这种方法，HeartSteps 是一项用于身体活动的 mHealth 干预措施，是心脏病二级预防的一部分。
