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**新冠疫情下的医护人员心态研究:基于 Twitter 话语的文本分析**

The State of Mind of Health Care Professionals in Light of the COVID-19 Pandemic: Text Analysis Study of Twitter Discourses.

机构信息

Software and Information Systems Engineering, Ben-Gurion University of the Negev, Beer Sheva, Israel.

Cyber@BGU, Ben-Gurion University of the Negev, Beer Sheva, Israel.

出版信息

J Med Internet Res. 2021 Oct 22;23(10):e30217. doi: 10.2196/30217.

Abstract

BACKGROUND

The COVID-19 pandemic has affected populations worldwide, with extreme health, economic, social, and political implications. Health care professionals (HCPs) are at the core of pandemic response and are among the most crucial factors in maintaining coping capacities. Yet, they are also vulnerable to mental health effects caused by managing a long-lasting emergency with a lack of resources and under complicated personal concerns. However, there are a lack of longitudinal studies that investigate the HCP population.

OBJECTIVE

The aim of this study was to analyze the state of mind of HCPs as expressed in online discussions published on Twitter in light of the COVID-19 pandemic, from the onset of the pandemic until the end of 2020.

METHODS

The population for this study was selected from followers of a few hundred Twitter accounts of health care organizations and common HCP points of interest. We used active learning, a process that iteratively uses machine learning and manual data labeling, to select the large-scale population of Twitter accounts maintained by English-speaking HCPs, focusing on individuals rather than official organizations. We analyzed the topics and emotions in their discourses during 2020. The topic distributions were obtained using the latent Dirichlet allocation algorithm. We defined a measure of topic cohesion and described the most cohesive topics. The emotions expressed in tweets during 2020 were compared to those in 2019. Finally, the emotion intensities were cross-correlated with the pandemic waves to explore possible associations between the pandemic development and emotional response.

RESULTS

We analyzed the timelines of 53,063 Twitter profiles, 90% of which were maintained by individual HCPs. Professional topics accounted for 44.5% of tweets by HCPs from January 1, 2019, to December 6, 2020. Events such as the pandemic waves, US elections, or the George Floyd case affected the HCPs' discourse. The levels of joy and sadness exceeded their minimal and maximal values from 2019, respectively, 80% of the time (P=.001). Most interestingly, fear preceded the pandemic waves, in terms of the differences in confirmed cases, by 2 weeks with a Spearman correlation coefficient of ρ(47 pairs)=0.340 (P=.03).

CONCLUSIONS

Analyses of longitudinal data over the year 2020 revealed that a large fraction of HCP discourse is directly related to professional content, including the increase in the volume of discussions following the pandemic waves. The changes in emotional patterns (ie, decrease in joy and increase in sadness, fear, and disgust) during the year 2020 may indicate the utmost importance in providing emotional support for HCPs to prevent fatigue, burnout, and mental health disorders during the postpandemic period. The increase in fear 2 weeks in advance of pandemic waves indicates that HCPs are in a position, and with adequate qualifications, to anticipate pandemic development, and could serve as a bottom-up pathway for expressing morbidity and clinical situations to health agencies.

摘要

背景

COVID-19 大流行影响了全球人口,对健康、经济、社会和政治都产生了极大影响。医疗保健专业人员(HCPs)是应对大流行的核心力量,也是维持应对能力的最重要因素之一。然而,他们也容易受到因资源匮乏和个人复杂问题而导致的长期应急管理带来的心理健康影响。然而,目前缺乏针对 HCP 人群的纵向研究。

目的

本研究旨在分析 COVID-19 大流行期间,HCP 在 Twitter 上发布的在线讨论中所表达的心态,时间范围为大流行开始至 2020 年底。

方法

本研究的研究对象是来自数百个医疗保健组织和普通 HCP 关注的 Twitter 账户的关注者。我们使用主动学习(一种迭代使用机器学习和手动数据标记的过程)来选择英语 HCP 维护的大规模 Twitter 账户人群,重点是个人而不是官方组织。我们分析了 2020 年他们讨论的主题和情绪。主题分布是使用潜在狄利克雷分配算法获得的。我们定义了一个主题内聚度的度量,并描述了最内聚的主题。将 2020 年的推文所表达的情绪与 2019 年的情绪进行了比较。最后,将情绪强度与大流行波进行交叉相关,以探讨大流行发展与情绪反应之间可能存在的关联。

结果

我们分析了 53063 个 Twitter 个人资料的时间线,其中 90%由个人 HCP 维护。2019 年 1 月 1 日至 2020 年 12 月 6 日期间,HCP 的专业主题占其推文的 44.5%。大流行波、美国大选或乔治·弗洛伊德案等事件影响了 HCP 的讨论。喜悦和悲伤的水平分别在 80%的时间(P=.001)超过了它们的最小和最大数值。最有趣的是,恐惧在大流行波之前两周就出现了,其差异在确诊病例中,Spearman 相关系数为ρ(47 对)=0.340(P=.03)。

结论

对 2020 年纵向数据的分析表明,很大一部分 HCP 讨论直接与专业内容相关,包括大流行波之后讨论量的增加。2020 年情绪模式的变化(即喜悦减少,悲伤、恐惧和厌恶增加)可能表明,在大流行后期间,为 HCP 提供情感支持至关重要,以防止疲劳、倦怠和心理健康障碍。大流行波前两周恐惧的增加表明,HCP 处于能够预测大流行发展的位置,并且具有足够的资格,可以作为向卫生机构表达发病率和临床情况的自下而上途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2cb4/8544741/6c50caf9ed10/jmir_v23i10e30217_fig1.jpg

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