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Accepted for/Published in: JMIR Infodemiology

Date Submitted: Apr 12, 2022
Date Accepted: Feb 10, 2023

The final, peer-reviewed published version of this preprint can be found here:

State and Federal Legislators’ Responses on Social Media to the Mental Health and Burnout of Health Care Workers Throughout the COVID-19 Pandemic: Natural Language Processing and Sentiment Analysis

Abrams MP, Pellulo A, Meisel ZF, Merchant RM, Purtle J, Agarwal AK

State and Federal Legislators’ Responses on Social Media to the Mental Health and Burnout of Health Care Workers Throughout the COVID-19 Pandemic: Natural Language Processing and Sentiment Analysis

JMIR Infodemiology 2023;3:e38676

DOI: 10.2196/38676

PMID: 37013000

PMCID: 10007003

State and Federal Legislators’ Response to the Mental Health and Burnout of Health Care Workers Throughout the COVID-19 Pandemic: Natural Language Processing and Sentiment Analysis of Legislators' Social Media Posts

  • Matthew Phillip Abrams; 
  • Arthur Pellulo; 
  • Zachary F Meisel; 
  • Raina M Merchant; 
  • Jonathan Purtle; 
  • Anish K Agarwal

ABSTRACT

Background:

Burnout and the mental health burden of the COVID-19 pandemic has disproportionately impacted health care workers. The links between state policies, COVID-19 case counts, strains on health care systems, and the mental health of health care workers continue to evolve. The language used by state and federal legislators in public-facing venues such as social media is important as it impacts public opinion and behavior, as well as reflects current policy leader opinions and planned legislation.

Objective:

The objective of this study was to examine legislators’ social media content on Twitter and Facebook throughout the COVID-19 pandemic to thematically characterize policy makers’ attitudes and perspectives related to the mental health and burnout within the health care workforce.

Methods:

Legislators’ social media posts about mental health and burnout within the health care workforce were collected from January 2020 to November 2021 using Quorum, a digital database of policy related documents. The total number of relevant social media posts per state legislator per calendar month were calculated and compared with COVID-19 case volume. Differences between themes expressed in Democratic and Republican posts were estimated using the Pearson chi-square test. Words within social media posts most associated with each political party were determined. Machine-learning was used to evaluate naturally occurring themes in the burnout- and mental health-related social media posts.

Results:

4,165 social media posts (1,400 Tweets and 2,765 Facebook posts) were generated by 2,047 unique state and federal legislators and 38 government entities. The majority of posts (55.68%, n = 2,319) were generated by Democrats, followed by Republicans (40.34%; n = 1,600). Among both parties, the volume of burnout-related posts was greatest during the initial Covid-19 surge. However, there was significant variation in the themes expressed by the two major political parties. Themes most correlated with Democratic posts were: 1) “Frontline Care and Burnout”, 2) “Vaccines,” 3) “COVID-19 Outbreaks,” and 4) “Mental Health Services.” Themes most correlated with Republican social media posts were: 1) “Legislation,” 2) “Call for Local Action,” 3) “Government Support,” and 4) “Health Care Worker Testing and Mental Health.”

Conclusions:

State legislators use social media to share opinions and thoughts on key topics including burnout and mental health strain among health care workers. Variations in the volume of posts indicated that a focus on burnout and the mental health of the health care workforce existed early in the pandemic but has waned. Significant differences emerged in the content posted by the two major US political parties, underscoring how each prioritized different aspects of the crisis. Clinical Trial: N/A


 Citation

Please cite as:

Abrams MP, Pellulo A, Meisel ZF, Merchant RM, Purtle J, Agarwal AK

State and Federal Legislators’ Responses on Social Media to the Mental Health and Burnout of Health Care Workers Throughout the COVID-19 Pandemic: Natural Language Processing and Sentiment Analysis

JMIR Infodemiology 2023;3:e38676

DOI: 10.2196/38676

PMID: 37013000

PMCID: 10007003

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© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.