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多模态面板数据集,用于了解疫情对心理的影响。

A multi-modal panel dataset to understand the psychological impact of the pandemic.

机构信息

Utrecht University, Department of Sociology, Utrecht University, 3584 CH, Utrecht, The Netherlands.

Tilburg University, Department of Methodology and Statistics, 5037 AB, Tilburg, The Netherlands.

出版信息

Sci Data. 2023 Aug 11;10(1):537. doi: 10.1038/s41597-023-02438-y.

Abstract

Besides far-reaching public health consequences, the COVID-19 pandemic had a significant psychological impact on people around the world. To gain further insight into this matter, we introduce the Real World Worry Waves Dataset (RW3D). The dataset combines rich open-ended free-text responses with survey data on emotions, significant life events, and psychological stressors in a repeated-measures design in the UK over three years (2020: n = 2441, 2021: n = 1716 and 2022: n = 1152). This paper provides background information on the data collection procedure, the recorded variables, participants' demographics, and higher-order psychological and text-derived variables that emerged from the data. The RW3D is a unique primary data resource that could inspire new research questions on the psychological impact of the pandemic, especially those that connect modalities (here: text data, psychological survey variables and demographics) over time.

摘要

除了对公共卫生产生深远影响外,新冠疫情对全球民众的心理健康也造成了巨大影响。为了进一步深入研究这一问题,我们引入了真实世界担忧波数据集(RW3D)。该数据集结合了丰富的开放式自由文本回复,以及英国三年来(2020 年:n=2441,2021 年:n=1716,2022 年:n=1152)在情绪、重大生活事件和心理压力源方面的调查数据,采用重复测量设计。本文提供了数据收集程序、记录变量、参与者人口统计学信息以及从数据中提取的高阶心理和文本变量的背景信息。RW3D 是一个独特的原始数据资源,它可以激发关于大流行对心理健康影响的新研究问题,特别是那些能够将不同模式(这里:文本数据、心理调查变量和人口统计学)联系起来的研究问题。

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