Evidence map›Paper›PMID 37013000›Full record

ArticleJMIR infodemiology2023

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.

Matthew P Abrams, Arthur P Pelullo, Zachary F Meisel, Raina M Merchant, Jonathan Purtle, Anish K Agarwal

Full text read
In one paragraph

Article in JMIR infodemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Matthew P AbramsDepartment of Emergency Medicine Perelman School of Medicine University of Pennsylvania Philadelphia, PA United States.ORCID https://orcid.org/0000-0001-6059-4857
Arthur P PelulloCenter for Digital Health University of Pennsylvania Philadelphia, PA United States.ORCID https://orcid.org/0000-0002-3667-4301
Zachary F MeiselDepartment of Emergency Medicine Perelman School of Medicine University of Pennsylvania Philadelphia, PA United States.ORCID https://orcid.org/0000-0001-8474-7993
Raina M MerchantDepartment of Emergency Medicine Perelman School of Medicine University of Pennsylvania Philadelphia, PA United States.ORCID https://orcid.org/0000-0002-9801-6881
Jonathan PurtleDepartment of Public Health Policy & Management School of Global Public Health New York University New York, NY United States.ORCID https://orcid.org/0000-0001-6908-5944
Anish K AgarwalDepartment of Emergency Medicine Perelman School of Medicine University of Pennsylvania Philadelphia, PA United States.ORCID https://orcid.org/0000-0003-2175-0196

Funding

Mentoring and Patient Oriented Research in Cardiovascular Health and Digital Data ScienceK24HL157621 · NHLBI · UNIVERSITY OF PENNSYLVANIA · PI MERCHANT, RAINA · 2021 to 2025
$615k
NHLBI NIH HHS K24 HL157621
6 · The paper itself

Abstract

Background: Burnout and the mental health burden of the COVID-19 pandemic have disproportionately impacted health care workers. The links between state policies, federal regulations, 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, and it also 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 mental health and burnout in the health care workforce. Methods: Legislators' social media posts about mental health and burnout in 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 was 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: A total of 4165 social media posts (1400 tweets and 2765 Facebook posts) were generated by 2047 unique state and federal legislators and 38 government entities. The majority of posts (n=2319, 55.68%) were generated by Democrats, followed by Republicans (n=1600, 40.34%). 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 2 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 and federal 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 2 major US political parties, underscoring how each prioritized different aspects of the crisis.

Indexed as

burnoutcontent analysisCOVID-19healthcare workerhealth care workforcehealthcare workforceinfodemiologylegislatormental healthmental well-beingpolicypolicy makerpsychological distresssocial mediathematic analysisTwitterwellness

Identifiers

PMID37013000
PMCPMC10007003

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read19
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.