Factors contributing to healthcare professional burnout during the COVID-19 pandemic: A rapid turnaround global survey

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Background

Healthcare professionals (HCPs) on the front lines against COVID-19 may face increased workload and stress. Understanding HCPs’ risk for burnout is critical to supporting HCPs and maintaining the quality of healthcare during the pandemic.

Methods

To assess exposure, perceptions, workload, and possible burnout of HCPs during the COVID-19 pandemic we conducted a cross-sectional survey. The main outcomes and measures were HCPs’ self-assessment of burnout, indicated by a single item measure of emotional exhaustion, and other experiences and attitudes associated with working during the COVID-19 pandemic.

Findings

A total of 2,707 HCPs from 60 countries participated in this study. Fifty-one percent of HCPs reported burnout. Burnout was associated with work impacting household activities (RR = 1·57, 95% CI = 1·39–1·78, P<0·001), feeling pushed beyond training (RR = 1·32, 95% CI = 1·20–1·47, P<0·001), exposure to COVID-19 patients (RR = 1·18, 95% CI = 1·05–1·32, P = 0·005), and making life prioritizing decisions (RR = 1·16, 95% CI = 1·02–1·31, P = 0·03). Adequate personal protective equipment (PPE) was protective against burnout (RR = 0·88, 95% CI = 0·79–0·97, P = 0·01). Burnout was higher in high-income countries (HICs) compared to low- and middle-income countries (LMICs) (RR = 1·18; 95% CI = 1·02–1·36, P = 0·018).

Interpretation

Burnout is present at higher than previously reported rates among HCPs working during the COVID-19 pandemic and is related to high workload, job stress, and time pressure, and limited organizational support. Current and future burnout among HCPs could be mitigated by actions from healthcare institutions and other governmental and non-governmental stakeholders aimed at potentially modifiable factors, including providing additional training, organizational support, and support for family, PPE, and mental health resources.

Related collections

Most cited references 26

Record: found
Abstract: found
Article: not found

Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

Paul A. Harris, Robert Taylor, Robert Thielke … (2009)

Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.

0 comments Cited 9718 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

An interactive web-based dashboard to track COVID-19 in real time

Ensheng Dong, Hongru Du, Lauren Gardner (2020)

In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.

0 comments Cited 4597 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: found

Is Open Access

Factors Associated With Mental Health Outcomes Among Health Care Workers Exposed to Coronavirus Disease 2019

Jianbo Lai, Simeng Ma, Ying Wang … (2020)

Key Points Question What factors are associated with mental health outcomes among health care workers in China who are treating patients with coronavirus disease 2019 (COVID-19)? Findings In this cross-sectional study of 1257 health care workers in 34 hospitals equipped with fever clinics or wards for patients with COVID-19 in multiple regions of China, a considerable proportion of health care workers reported experiencing symptoms of depression, anxiety, insomnia, and distress, especially women, nurses, those in Wuhan, and front-line health care workers directly engaged in diagnosing, treating, or providing nursing care to patients with suspected or confirmed COVID-19. Meaning These findings suggest that, among Chinese health care workers exposed to COVID-19, women, nurses, those in Wuhan, and front-line health care workers have a high risk of developing unfavorable mental health outcomes and may need psychological support or interventions.

0 comments Cited 3353 times – based on 0 reviews      Review now

Bookmark

All references

Author and article information

Contributors

Luca A. Morgantini:

ORCID: http://orcid.org/0000-0002-8965-6414

Role: ConceptualizationRole: Data curationRole: InvestigationRole: MethodologyRole: Project administrationRole: ResourcesRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing

Ushasi Naha: Role: InvestigationRole: Writing – original draftRole: Writing – review & editing

Heng Wang: Role: Data curationRole: Formal analysisRole: Validation

Simone Francavilla:

ORCID: http://orcid.org/0000-0003-3314-939X

Role: ConceptualizationRole: Investigation

Ömer Acar: Role: ConceptualizationRole: InvestigationRole: Writing – review & editing

Jose M. Flores: Role: Data curationRole: Validation

Simone Crivellaro: Role: SupervisionRole: Writing – review & editing

Daniel Moreira: Role: ConceptualizationRole: MethodologyRole: SupervisionRole: Writing – review & editing

Michael Abern: Role: ConceptualizationRole: MethodologyRole: SupervisionRole: Writing – review & editing

Martin Eklund: Role: Formal analysisRole: SupervisionRole: Validation

Hari T. Vigneswaran:

ORCID: http://orcid.org/0000-0001-9703-2655

Role: Data curationRole: InvestigationRole: MethodologyRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing

Stevan M. Weine: Role: ConceptualizationRole: Data curationRole: Formal analysisRole: MethodologyRole: SupervisionRole: ValidationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing

Michio Murakami: Role: Editor

Journal

Journal ID (nlm-ta): PLoS One

Journal ID (iso-abbrev): PLoS ONE

Journal ID (publisher-id): plos

Journal ID (pmc): plosone

Title: PLoS ONE

Publisher: Public Library of Science (San Francisco, CA USA )

ISSN (Electronic): 1932-6203

Publication date (Electronic): 3 September 2020

Publication date Collection: 2020

Publication date PMC-release: 3 September 2020

Volume: 15

Issue: 9

Electronic Location Identifier: e0238217

Affiliations

[1 ] Department of Urology, College of Medicine, University of Illinois at Chicago, Chicago, Illinois, United States of America

[2 ] Department of Epidemiology and Biostatistics, School of Public Health, University of Illinois at Chicago, Chicago, Illinois, United States of America

[3 ] Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden

[4 ] Department of Psychiatry, College of Medicine, University of Illinois at Chicago, Chicago, Illinois, United States of America

[5 ] Center for Global Health, University of Illinois at Chicago, Chicago, Illinois, United States of America

Fukushima Medical University School of Medicine, JAPAN

Author notes

Competing Interests: The authors have declared that no competing interests exist.

* E-mail: lmorga5@ 123456uic.edu

Author information

Luca A. Morgantini http://orcid.org/0000-0002-8965-6414

Simone Francavilla http://orcid.org/0000-0003-3314-939X

Hari T. Vigneswaran http://orcid.org/0000-0001-9703-2655

Article

Publisher ID: PONE-D-20-13536

DOI: 10.1371/journal.pone.0238217

PMC ID: 7470306

PubMed ID: 32881887

SO-VID: 6465e035-fbf3-42d2-9bf6-0e67597dc300

License:

This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

History

Date received : 8 May 2020

Date accepted : 12 August 2020

Page count

Figures: 2, Tables: 1, Pages: 11

Funding

The authors received no specific funding for this work.

Custom metadata

Data Availability All relevant data are within the manuscript and its Supporting Information files.

Outbreaks COVID-19

ScienceOpen disciplines: Uncategorized

Data availability:

ScienceOpen disciplines: Uncategorized

Comments

Comment on this article

scite_

Cited by 172

See all cited by

Most referenced authors 645

See all reference authors

- Version 1

Factors contributing to healthcare professional burnout during the COVID-19 pandemic: A rapid turnaround global survey

Read this article at

Abstract

Background

Methods

Findings

Interpretation

Related collections

PLOS: COVID-19 pandemic

Most cited references 26

Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

An interactive web-based dashboard to track COVID-19 in real time

Factors Associated With Mental Health Outcomes Among Health Care Workers Exposed to Coronavirus Disease 2019

Author and article information

Contributors

Journal

Affiliations

Author notes

Author information

Article

History

Page count

Funding

Categories

Custom metadata

Comments

Comment on this article

Similar content 463

Cited by 172

Most referenced authors 645