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影响中国 ICU 医护人员离职意愿的因素:来自横断面调查和 XGBoost 分析的见解
Authors Wu J, Zhang C, He F, Wang Y, Zeng L, Liu W, Zhao D, Mao J, Gao F
Received 23 August 2023
Accepted for publication 2 November 2023
Published 22 November 2023 Volume 2023:16 Pages 2543—2553
DOI https://doi.org/10.2147/RMHP.S432847
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Gulsum Kubra Kaya
Background: The intention to leave among intensive care unit (ICU) healthcare professionals in China has become a concerning issue. Therefore, understanding the factors influencing the intention to leave and implementing appropriate measures have become urgent needs for maintaining a stable healthcare workforce.
Objective: This study aims to investigate the current status of intention to leave among ICU healthcare professionals in China, explore the relevant factors affecting this intention, and provide targeted recommendations to reduce the intention to leave among healthcare professionals.
Methods: A cross-sectional survey was conducted, involving ICU healthcare professionals from 3-A hospitals of the 34 provinces in China. The survey encompassed 22 indicators, including demographic information (marital status, children, income), work-related factors (weekly working hours, night shift frequency, hospital environment), and psychological assessment (using Symptom Checklist-90 (SCL-90)). The data from a sample population of 3653 individuals were analyzed using the extreme gradient boosting (XGBoost) method to predict intention to leave.
Results: The survey results revealed that 62.09% (2268 individuals) of the surveyed ICU healthcare professionals expressed an intention to leave. The XGBoost model achieved a predictive accuracy of 75.38% and an Area Under the Curve (AUC) of 0.77.
Conclusion: Satisfaction with income was found to be the strongest predictor of intention to leave among ICU healthcare professionals. Additionally, factors such as years of experience, night shift frequency, and pride in hospital work were found to play significant roles in influencing the intention to leave.
Keywords: ICU healthcare professionals, intention to leave, cross-sectional survey, extreme gradient boosting, XGBoost