Winter Michael, Probst Thomas, John Dennis, Pryss Rüdiger
Institute of Medical Data Science, University Hospital Würzburg, Würzburg, Germany.
Institute of Clinical Epidemiology and Biometry, University of Würzburg, Würzburg, Germany.
Data Brief. 2025 Aug 12;62:111967. doi: 10.1016/j.dib.2025.111967. eCollection 2025 Oct.
The dataset presented in this work is derived from the Stress Recognition Study in the Corona Health app, a digital health platform designed with the German Robert Koch Institute (RKI) to monitor stress levels and associated factors in adults during and after the COVID-19 pandemic. Data were collected using a mobile-based survey completed by 627 adults (18 years and older) at baseline, with 385 of these participants also contributing 4,331 follow-up assessments over time. The study utilized baseline and follow-up questionnaires to capture changes in participants' stress levels throughout the pandemic period and beyond (December 2020 to May 2025). The questionnaires cover key stress indicators such as perceived stress levels, demographic factors, and smartphone sensor data. By capturing real-time, longitudinal stress data from adults during a public health crisis, this dataset enables researchers to examine how stress levels fluctuated in response to pandemic restrictions and recovery phases. The integration of ecological momentary assessments with mobile sensing data (e.g., app usage statistics, coarse-grained location information) provides opportunities to analyze adult stress trajectories, identify stress resilience factors, and evaluate the effectiveness of mobile health approaches for stress monitoring during crisis situations. The data, including questionnaire responses and mobile sensing data, are publicly available under a Creative Commons license at https://zenodo.org/records/15780255.
本研究中呈现的数据集源自“新冠健康”应用程序中的压力识别研究,该应用程序是一个数字健康平台,由德国罗伯特·科赫研究所(RKI)设计,用于监测成年人在新冠疫情期间及之后的压力水平和相关因素。数据通过一项基于手机的调查收集,627名成年人(18岁及以上)在基线时完成了该调查,其中385名参与者还随时间提供了4331次随访评估。该研究利用基线问卷和随访问卷来记录参与者在整个疫情期间及之后(2020年12月至2025年5月)压力水平的变化。问卷涵盖了关键压力指标,如感知压力水平、人口统计学因素和智能手机传感器数据。通过在公共卫生危机期间收集成年人的实时纵向压力数据,该数据集使研究人员能够研究压力水平如何因疫情限制和恢复阶段而波动。生态瞬时评估与移动传感数据(如应用程序使用统计、粗粒度位置信息)的整合为分析成年人压力轨迹、识别压力恢复力因素以及评估危机情况下移动健康方法用于压力监测的有效性提供了机会。这些数据,包括问卷回复和移动传感数据,根据知识共享许可在https://zenodo.org/records/15780255上公开提供。