被动智能手机措施具有巨大的潜力,并越来越多地用于心理和生物医学研究,以捕捉个人的行为。这些措施涉及从智能手机中近乎连续且不引人注意的数据收集,而无需参与者的主动输入。例如,GPS传感器用于确定一个人的(社会)背景,和加速度计来测量运动。然而,利用被动智能手机措施在数据收集和分析过程中提出了方法上的挑战。研究人员在使用这些措施时必须做出多个决定,这可能会导致不同的结论。不幸的是,这些决策过程往往缺乏透明度。开放科学实践的实施才刚刚开始出现在数字表型研究中,并且在研究中差异很大。由于必须做出的各种选择,善意的研究人员可能无法报告某些决定。为了解决这个问题,提高数字表型研究的可重复性,我们建议采用预先注册作为前进的方向。尽管已经有一些尝试预先注册数字表型研究,目前缺少注册此类研究的模板。由于需要结构良好的模板的高度复杂性,这可能是有问题的。因此,我们的目标是开发一种易于使用且易于研究人员理解的预注册模板.此外,我们解释这个模板,并提供资源来帮助研究人员做出有关数据收集的明智决定,清洁,和分析。总的来说,我们的目标是让研究人员的选择明确,提高透明度,并提高使用被动智能手机措施的研究标准。
Passive smartphone measures hold significant potential and are increasingly employed in psychological and biomedical research to capture an individual\'s behavior. These measures involve the near-continuous and unobtrusive collection of data from smartphones without requiring active input from participants. For example, GPS sensors are used to determine the (social) context of a person, and accelerometers to measure movement. However, utilizing passive smartphone measures presents methodological challenges during data collection and analysis. Researchers must make multiple decisions when working with such measures, which can result in different conclusions. Unfortunately, the transparency of these decision-making processes is often lacking. The implementation of open science practices is only beginning to emerge in digital phenotyping studies and varies widely across studies. Well-intentioned researchers may fail to report on some decisions due to the variety of choices that must be made. To address this issue and enhance reproducibility in digital phenotyping studies, we propose the adoption of preregistration as a way forward. Although there have been some attempts to preregister digital phenotyping studies, a template for registering such studies is currently missing. This could be problematic due to the high level of complexity that requires a well-structured template. Therefore, our objective was to develop a preregistration template that is easy to use and understandable for researchers. Additionally, we explain this template and provide resources to assist researchers in making informed decisions regarding data collection, cleaning, and analysis. Overall, we aim to make researchers\' choices explicit, enhance transparency, and elevate the standards for studies utilizing passive smartphone measures.