Abstract
Background: High-stress environments, heavy workloads, and the emotional demands of patient care, which are common challenges faced by nurses, are factors that can lead to burnout. Shift work can make traditional burnout interventions costly and difficult to implement. Artificial intelligence (AI) could offer solutions that are less constrained by time, resources, and labor.
Aim: To investigate the effectiveness of an AI-assisted intervention in reducing nurse burnout.
Methods: A single-blind, three-group, randomized controlled trial of 120 nurses (40 per group) was conducted from June 2023 to July 2023. The AI-assisted tailored intervention included two 2-week programs, delivering one of four programs to the intervention group: mindfulness meditation, acceptance commitment therapy, storytelling and reflective writing, or laughter therapy. The experimental group received tailored programs based on demographic and work-related characteristics, job stress, stress response, coping strategy, and burnout dimensions (client-related, personal, and work-related). Control Group 1 self-selected their programs, while Control Group 2 was provided with online information on burnout reduction. Primary outcomes, client-related, personal, and work-related burnout, were measured at baseline, week 2, and week 4. Secondary outcomes, job stress, stress responses, and coping strategies, were assessed at baseline and week 4. Data were analyzed using ANOVA, repeated measures ANOVA, and the Scheffé test for post hoc analysis.
Results: The experimental group showed significant reductions in client-related burnout (F = 7.725, p = 0.001) and personal burnout (F = 10.967, p < 0.0001) compared to the other groups. Significant effects of time and time × group interactions were observed for client-related and personal burnout, with time effects noted for work-related burnout. Stress response reduction was highest in Control Group 1, followed by the experimental group and Control Group 2 (F = 3.07, p = 0.017).
Notes
Open Access Details:
This is an open access article originally published under the terms of a Creative Commons License, which permits the Sigma Repository to post a copy in its collections. The license is attached to this item record; please click on the license for further details.
Original Article Citation:
Baek, G., & Cha, C. (2025). AI-Assisted Tailored Intervention for Nurse Burnout: A Three-Group Randomized Controlled Trial. Worldviews on evidence-based nursing, 22(1), e70003. https://doi.org/10.1111/wvn.70003
No changes have been made to this article.
Sigma Membership
Lambda Alpha at-Large
Type
Article
Format Type
Text-based Document
Study Design/Type
Randomized Controlled Trial
Research Approach
Quantitative Research
Keywords:
Burnout, Burnout Prevention, Artificial Intelligence, AI, AI-assisted Intervention
Recommended Citation
Baek, Gumhee and Cha, Chiyoung, "AI-Assisted Tailored Intervention for Nurse Burnout: A Three-Group Randomized Controlled Trial" (2026). Individual Articles. 45.
https://www.sigmarepository.org/individual_articles/45
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
Publisher
Wiley Periodicals LLC on behalf of Sigma Theta Tau International
Version
Publisher's Version
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Review Type
External Review: Previously Published Material
Acquisition
Indexed Previously Published Material (Per Creative Commons License)
Date of Issue
2026-01-13
Full Text of Presentation
wf_yes
Description
This study was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean Government (MSIT) (No. 2021R1A2C2008166 and RS-2024-00351194).