Public Health

Comprehensive Summary

Researchers analyzed how US health care professionals (HCPs) expressed their emotions during the COVID-19 pandemic by examining more than 8.7 million tweets from January 2019 to May 2022. They used machine learning to identify 1,450 HCP Twitter accounts and matched them with 1,387 non-HCP accounts of similar age, gender, and ethnicity. Six key emotions were tracked: fear, sadness, joy, anger, surprise, and disgust across five stages of the pandemic. HCPs consistently showed higher levels of fear and sadness, especially in the early phases of the pandemic, while displaying lower levels of anger, surprise, and disgust than the general public. Their joy decreased at the start of the pandemic, but then rose above the levels of non-HCPs from the second phase onward. By the end of the study, most emotions returned to their pre-pandemic levels, but sadness among HCPs remained elevated. The researchers also found that HCP fear levels spiked about three weeks before national COVID-19 case counts peaked, suggesting that the emotions expressed by HCPs on social media can serve as an early signal of rising infection rates.

Outcomes and Implications

These findings highlight the need for strong mental and emotional support for health care workers during prolonged public health emergencies. HCPs experienced heavier emotional burdens than the general population, and their sadness lingered even after the number of cases dropped. Hospitals and health systems can utilize these insights to enhance mental health resources, peer support networks, and crisis counseling for frontline workers. For researchers and physicians, this study shows that monitoring HCP discussions on social media can provide real-time clues about stress levels in the workforce and early signs of emerging public health threats. It also underscores the importance of continuing to check for emotional strain in health care professionals even after a crisis appears to be over.

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© 2025 AIIM. Created by AIIM IT Team

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© 2025 AIIM. Created by AIIM IT Team

AIIM Research

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© 2025 AIIM. Created by AIIM IT Team