Fengshi Jing1,2†
Mengyuan Cheng1,2†
Jing Li3‡Chaocheng He4
Hao Ren1
Jiandong Zhou5
Hanchu Zhou6,7
Zhongzhi Xu8Weiming Chen9‡
Weibin Cheng1,7*- 1Institute for Healthcare Artificial Intelligence Application, Guangdong Second Provincial General Hospital, Guangzhou, China
- 2UNC Project-China, UNC Global, School of Medicine, The University of North Carolina, Chapel Hill, NC, United States
- 3Guangzhou Baiyun International Airport Co., Ltd, Guangzhou, China
- 4School of Information Management, Wuhan University, Wuhan, China
- 5Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- 6School of Traffic and Transportation Engineering, Central South University, Changsha, China
- 7School of Data Science, City University of Hong Kong, Kowloon, Hong Kong SAR, China
- 8School of Public Health, Sun Yat-Sen University, Guangzhou, China
- 9Health Medicine Department, Guangdong Second Provincial General Hospital, Guangzhou, China
A Correction on
Social, lifestyle, and health status characteristics as a proxy for occupational burnout identification: A network approach analysis
By Jing F, Cheng M, Li J, He C, Ren H, Zhou J, Zhou H, Xu Z, Chen W and Cheng W (2023). Front. Psychiatry. 14:1119421. doi: 10.3389/fpsyt.2023.1119421
An incorrect Funding statement was provided. The authors previously used the funding proposal application numbers instead of grant numbers. The statement previously said:
“This work was supported by the Key-Area Research and Development Program of Guangdong Province (2020B0101130020), and by the Guangzhou Science and Technology Project (No. SL2022A03J00781 and No. SL2022A04J01130)”.
The corrected statement appears below:
“This work was supported by the Key-Area Research and Development Program of Guangdong Province (2020B0101130020), and by the Guangzhou Science and Technology Project (No. 2023A03J0286 and No. 2023A04J1715)”.
The original version of this article has been updated.
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Keywords: occupational burnout, network science, health management, exponential random graph model, social networks
Citation: Jing F, Cheng M, Li J, He C, Ren H, Zhou J, Zhou H, Xu Z, Chen W and Cheng W (2025) Correction: Social, lifestyle, and health status characteristics as a proxy for occupational burnout identification: a network approach analysis. Front. Psychiatry 16:1642874. doi: 10.3389/fpsyt.2025.1642874
Received: 07 June 2025; Accepted: 09 June 2025;
Published: 23 June 2025.
Approved by:
Frontiers Editorial Office, Frontiers Media SA, SwitzerlandCopyright © 2025 Jing, Cheng, Li, He, Ren, Zhou, Zhou, Xu, Chen and Cheng. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Weibin Cheng, Y2h3YjgxN0BnbWFpbC5jb20=
†These authors have contributed equally to this work and share first authorship
‡These authors share senior authorship