JMIR Publications

ABSTRACT

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 one of 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. Analysing online social networks is an accepted method to explore insights during routine and emergencies. 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 analysed 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 identify causal relationships.

Results:

We analysed 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 daily death cases) by one week with a Pearson correlation coefficient of r(47)=.388, P=.001.

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 in the post-pandemic period. The increase of fear one week in advance of pandemic waves indicates that many HCPs are in a position and with adequate qualification to anticipate the pandemic development.