Physical and mental well-being during the COVID-19 pandemic is typically assessed via surveys, which might make it difficult to conduct longitudinal studies and might lead to data suffering from recall bias. Ecological momentary assessment (EMA) driven smartphone apps can help alleviate such issues, allowing for in situ recordings. Implementing such an app is not trivial, necessitates strict regulatory and legal requirements, and requires short development cycles to appropriately react to abrupt changes in the pandemic. Based on an existing app framework, we developed Corona Health, an app that serves as a platform for deploying questionnaire-based studies in combination with recordings of mobile sensors. In this paper, we present the technical details of Corona Health and provide first insights into the collected data. Through collaborative efforts from experts from public health, medicine, psychology, and computer science, we released Corona Health publicly on Google Play and the Apple App Store (in July, 2020) in 8 languages and attracted 7,290 installations so far. Currently, five studies related to physical and mental well-being are deployed and 17,241 questionnaires have been filled out. Corona Health proves to be a viable tool for conducting research related to the COVID-19 pandemic and can serve as a blueprint for future EMA-based studies. The data we collected will substantially improve our knowledge on mental and physical health states, traits and trajectories as well as its risk and protective factors over the course of the COVID-19 pandemic and its diverse prevention measures.
翻译:在COVID-19大流行期间,通常通过调查来评估身心健康情况,这可能使得难以进行纵向研究,并可能导致出现召回偏见的数据;生态瞬间评估(EMA)驱动的智能手机应用程序有助于缓解这些问题,允许现场记录;实施这种应用程序并非微不足道,需要严格的监管和法律要求,要求短期发展周期对这一大流行病的突变作出适当反应;根据现有的应用框架,我们开发了Corona-19健康软件,作为结合移动传感器录音进行基于问卷的研究的平台;在本文件中,我们介绍了Corona健康的技术细节,并对收集的数据提供了初步见解;通过公共卫生、医学、心理学和计算机科学专家的合作努力,我们以8种语言公开发布Corona健康软件和苹果应用商店(2020年7月),吸引了7 290个设施。我们开发了5项与身心健康有关的研究,并填写了17 241份调查表,证明Corona健康软件是进行与COVI-19大流行流行病有关研究的可行工具,作为我们所收集的蓝图和心理健康知识的基础,可以作为我们所收集的蓝图和历史数据的基础。