Author: Elyashar, Aviad; Plochotnikov, Ilia; Cohen, Idan-Chaim; Puzis, Rami; Cohen, Odeya
Title: The State of Mind of Healthcare Professionals in the Light of the COVID-19: Insights from Text Analysis of Twitter's Online Discourses Cord-id: qmkzsq9h Document date: 2021_1_1
ID: qmkzsq9h
Snippet: BACKGROUND: The COVID-19 pandemic has affected populations worldwide, with extreme health, economic, social, and political implications. Healthcare 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, managing a long-lasting emergency under lack of resources and complicated personal concerns. However, there is a lack of longitudinal studies that investigate the HC
Document: BACKGROUND: The COVID-19 pandemic has affected populations worldwide, with extreme health, economic, social, and political implications. Healthcare 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, managing a long-lasting emergency under lack of resources and complicated personal concerns. However, there is a lack of longitudinal studies that investigate the HCP population. OBJECTIVE: To analyse the state of mind of HCPs as expressed in online discussions published on Twitter in light of COVID-19, from the pandemic onset until the end of 2020. METHODS: The population for this study was selected from followers of a few hundred Twitter accounts of healthcare 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 discourse during 2020. The topic distributions were obtained using the Latent Dirichlet Allocation (LDA) algorithm. We defined a measure of topic cohesion and described the most cohesive topics. The emotions expressed in tweets during 2020 were compared to 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 timelines of 53,063 Twitter profiles, 90% of which are maintained by individual HCPs. Professional topics account for 44.5% of tweets by HCPs from Jan. 1st to Dec. 6th, 2020. Events such as the pandemic waves, U.S. elections, or the George Floyd case affect the HCPs' discourse. The levels of joy and sadness exceed their minimal and maximal values yesteryear, respectively, 80% of the time, P= .001. Most interestingly, fear precedes the pandemic waves (in terms of the differences in confirmed cases) by two weeks with a Spearman correlations coefficient of Ï(47)= .34, P= .026. CONCLUSIONS: Analyses of longitudinal data over the 2020 year reveal that a large fraction of HCP discourse is related directly to professional content, including the increase in the volume of discussions following the pandemic waves. The changes in emotional patterns (decrease of joy, an increase of 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 postpandemic period. The increase of fear two weeks in advance of pandemic waves indicates that HCPs are in a position and with adequate qualification to anticipate the pandemic development, and could serve as a bottom-up pathway for expressing the morbidity and clinical situation to health agencies.
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