Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 283

The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.

Examining the Impact of the COVID-19 Pandemic on Burnout and Stress Among U.S. Nurses

Open access
Martin, Brendan, Kaminski-Ozturk, Nicole, O’Hara, Charlie, Smiley, Richard·2023·Journal of Nursing Regulation

Abstract

Background The COVID-19 pandemic has amplified long-standing issues of burnout and stress among the U.S. nursing workforce, renewing concerns of projected staffing shortages. Understanding how these issues affect nurses’ intent to leave the profession is critical to accurate workforce modeling. Purpose To identify the personal and professional characteristics of nurses experiencing heightened workplace burnout and stress. Methods We used a subset of data from the 2022 National Nursing Workforce Survey for analysis. Binary logistic regression models and natural language processing were used to determine the significance of observed trends. Results Data from a total of 29,472 registered nurses (including advanced practice registered nurses) and 24,061 licensed practical nurses/licensed vocational nurses across 45 states were included in this analysis. More than half of the sample (62%) reported an increase in their workload during the COVID-19 pandemic. Similarly high proportions reported feeling emotionally drained (50.8%), used up (56.4%), fatigued (49.7%), burned out (45.1%), or at the end of their rope (29.4%) “a few times a week” or “every day.” These issues were most pronounced among nurses with 10 or fewer years of experience, driving an overall 3.3% decline in the U.S. nursing workforce during the past 2 years. Conclusion High workloads and unprecedented levels of burnout during the COVID-19 pandemic have stressed the U.S. nursing workforce, particularly younger, less experienced RNs. These factors have already resulted in high levels of turnover with the potential for further declines. Coupled with disruptions to prelicensure nursing education and comparable declines among nursing support staff, this report calls for significant policy interventions to foster a more resilient and safe U.S. nursing workforce moving forward.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1016/s2155-8256(23)00063-7

Cites

28 of 28 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 28 references

Cited by

See all 283

Metadata

Authors
Martin, B., Kaminski-Ozturk, N., O’Hara, C., & Smiley, R.
Venue
Journal of Nursing Regulation
Publisher
Elsevier BV
Published
2023-04
Volume
14
Issue
1
Pages
4-12
ISSN
2155-8256 (ISSN-L)
OpenAlex
W4362638751
Cited by
283
References
28
FWCI
92.50
Type
journal article
Language
en
Open access
bronze

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Examining the Impact of the COVID-19 Pandemic on Burnout and Stress Among U.S. Nurses. https://app.cochat.ai/papers/10.1016/s2155-8256(23)00063-7
The paper
Martin, B., Kaminski-Ozturk, N., O’Hara, C., & Smiley, R. (2023). Examining the Impact of the COVID-19 Pandemic on Burnout and Stress Among U.S. Nurses. Journal of Nursing Regulation. https://doi.org/10.1016/s2155-8256(23)00063-7

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.