Abstract

Background: Nurse burnout is a global health priority that has been compounded by Coronavirus 2019 (COVID-19). Organizational theory states that nurse burnout is directly impacted by operant mechanisms (nurse characteristics, nurse specialization) and hospital-wide models. The purpose of this study is to determine the relationship between hospital wide models (evidence-based care, team-based care, discharge planning, care coordination), operant mechanisms (nurse characteristics and specialization), and outcomes (nurse burnout) before and after COVID-19.

Design: A cross-sectional design was applied, using secondary data analysis.

Methods: A secondary data analysis using the 2018 and 2022 NSSRN data set was used to analyze frequencies of operant mechanisms (nurse characteristics, nurse specialization) and hospital-wide models. Chi-square for independence test was used to compare the difference in nurse characteristics between those who left the profession before and after COVID-19, as well as to describe the relationship between operant mechanisms, hospital-wide models, and nurse burnout. Significant results were analyzed using a general linear regression to determine predictive and protective factors.

Results: Participants were older in age, 30 to 64 (85%) in 2018, than in 2022, with nurses only ranging in age from 30 to 54 (51.6%).Nurses were found to not be working in nursing due to retirement, family caregiving, and burnout. Evidence-based care and team-based care were both reported at least somewhat in over half the sample in 2018 and 2022.The highest degree in nursing, years since graduation, age, year (before and after COVID-19), advanced practice certification, and team-based care were found to the predictive factors in the general linear regression analysis. Evidence-based care was not found statistically significant in the general linear regression analysis.

Conclusions: The findings indicate that COVID-19 did influence nurse burnout. Highest degree in nursing, years since graduation, age, year, advanced practice certification, and team-based care were found to be predictive factors for nurse burnout, while evidence-based care was found to be a protective factor. Future research should focus on investigating hospital-wide models that mitigate burnout and are prepared for catastrophic events, as well as the socio-economic, cultural and health disparities within burnout to provide further information on burnout and the effects on these groups.

Notes

Extensive reference list included in attached slide deck.

Description

This session explores how hospital-wide models and nurse characteristics influenced nurse burnout before and after COVID-19, using national nursing workforce data. Participants will gain insight into predictive and protective factors, including team-based care and education level, to better understand strategies for reducing burnout and strengthening resilience in nursing practice.

Author Details

Bridget Webb, PhD, RN, AHN-BC, CNE;

Jennifer Mallow, PhD, RN, FNP-BC, FAAN;

Suzy Mascaro Walter, PhD, APRN, FNP-BC, CNRN;

Kesheng Wang, PhD, MA, BS;

Tina Antil Keener, PhD, RN CPNP, CNE;

Tim Cunningham, DrPH, RN, FAAN

Sigma Membership

Alpha Rho

Type

Presentation

Format Type

Text-based Document

Study Design/Type

Cross-Sectional

Research Approach

Mixed/Multi Method Research

Keywords:

Stress/Coping, Psychological Stress, Coping, Workforce, Psychological Burnout, COVID-19 Pandemic

Conference Name

Creating Healthy Work Environments

Conference Host

Sigma Theta Tau International

Conference Location

Washington, DC, USA

Conference Year

2026

Rights Holder

All rights reserved by the author(s) and/or publisher(s) listed in this item record unless relinquished in whole or part by a rights notation or a Creative Commons License present in this item record. All permission requests should be directed accordingly and not to the Sigma Repository. All submitting authors or publishers have affirmed that when using material in their work where they do not own copyright, they have obtained permission of the copyright holder prior to submission and the rights holder has been acknowledged as necessary.

Review Type

Abstract Review Only: Reviewed by Event Host

Acquisition

Proxy-submission

Date of Issue

2026-5

Click above link to access the slide deck.

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Organizational Theory and Nurse Burnout: A Secondary Data Analysis Before and After COVID-19

Washington, DC, USA

Background: Nurse burnout is a global health priority that has been compounded by Coronavirus 2019 (COVID-19). Organizational theory states that nurse burnout is directly impacted by operant mechanisms (nurse characteristics, nurse specialization) and hospital-wide models. The purpose of this study is to determine the relationship between hospital wide models (evidence-based care, team-based care, discharge planning, care coordination), operant mechanisms (nurse characteristics and specialization), and outcomes (nurse burnout) before and after COVID-19.

Design: A cross-sectional design was applied, using secondary data analysis.

Methods: A secondary data analysis using the 2018 and 2022 NSSRN data set was used to analyze frequencies of operant mechanisms (nurse characteristics, nurse specialization) and hospital-wide models. Chi-square for independence test was used to compare the difference in nurse characteristics between those who left the profession before and after COVID-19, as well as to describe the relationship between operant mechanisms, hospital-wide models, and nurse burnout. Significant results were analyzed using a general linear regression to determine predictive and protective factors.

Results: Participants were older in age, 30 to 64 (85%) in 2018, than in 2022, with nurses only ranging in age from 30 to 54 (51.6%).Nurses were found to not be working in nursing due to retirement, family caregiving, and burnout. Evidence-based care and team-based care were both reported at least somewhat in over half the sample in 2018 and 2022.The highest degree in nursing, years since graduation, age, year (before and after COVID-19), advanced practice certification, and team-based care were found to the predictive factors in the general linear regression analysis. Evidence-based care was not found statistically significant in the general linear regression analysis.

Conclusions: The findings indicate that COVID-19 did influence nurse burnout. Highest degree in nursing, years since graduation, age, year, advanced practice certification, and team-based care were found to be predictive factors for nurse burnout, while evidence-based care was found to be a protective factor. Future research should focus on investigating hospital-wide models that mitigate burnout and are prepared for catastrophic events, as well as the socio-economic, cultural and health disparities within burnout to provide further information on burnout and the effects on these groups.