Mobile health (m-Health) resources are emerging as a significant tool to overcome mental health support access barriers due to their ability to rapidly reach and provide support to individuals in need of mental health support. m-Health provides an approach to adapt and initiate mental health support at precise moments, when they are most likely to be effective for the individual. However, poor adoption of mental health apps in the real world suggests that new approaches to optimising the quality of m-Health interventions are critically needed in order to realise the potential translational benefits for mental health support. The micro-randomised trial is an experimental approach for optimising and adapting m-Health resources. This trial design provides data to construct and optimise m-Health interventions. The data can be used to inform when and what type of m-Health interventions should be initiated, and thus serve to integrate interventions into daily routines with precision. Here, we illustrate this approach in a case study, review implementation issues that need to be considered while conducting an MRT, and provide a checklist for mental health m-Health intervention developers.

流动医疗（m-Health）资源正在迅速成为克服精神卫生支持障碍的重要工具，因为它们能够迅速到达需要精神卫生支持的个人并为其提供支持。m-Health提供了一种在最可能对个人有效的精确时刻调整和发起心理健康支持的方法。但是，现实世界中对心理健康应用程序的采用率不高，表明迫切需要优化m-Health干预质量的新方法，以实现对心理健康支持的潜在转化效益。微观随机试验是一种用于优化和调整m-Health资源的实验方法。该试验设计为构建和优化m-Health干预措施提供了数据。该数据可用于告知何时应启动何种类型的m-Health干预措施，从而将干预措施精确地整合到日常工作中。在这里，我们在案例研究中说明了这种方法，回顾了进行MRT时需要考虑的实施问题，并为心理健康m-Health干预开发商提供了清单。