Machine-learning-based model for analysing and accurately predicting factors related to burnout in healthcare workers
A significant correlation was found between job satisfaction and burnout levels. Physicians and surgeons with less than a decade of professional experience are more prone to high levels of burnout. The RF model proved effective for predicting the burnout level among medical staff, consistently achieving an accuracy rate close to 80%. These findings can serve as valuable insights for hospital administrators in their effort to prevent and mitigate burnout among medical staff.
Authors
- Ching‐Wen Chien (ORCID: https://orcid.org/0000-0001-7260-8427)
- Chao Liu (ORCID: https://orcid.org/0000-0003-3300-1360)
- Lifeng Qin (ORCID: https://orcid.org/0000-0001-5307-5792)
- Yen‐Ching Chuang (ORCID: https://orcid.org/0000-0003-1136-8727)
- Tao-Hsin Tung
- Lijie Ren (ORCID: https://orcid.org/0000-0002-8085-0907)
Institutions
- Wenzhou Medical University (CN)
- Zhejiang Taizhou Hospital (CN)
- Shenzhen Second People's Hospital (CN)
- Taizhou University (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- BMJ Public Health
- Published
- 2025-09-01
- DOI
- https://doi.org/10.1136/bmjph-2023-000777
- Primary Topic
- Healthcare professionals’ stress and burnout
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China