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Factors Affecting Intention to Leave Among ICU Healthcare Professionals in China: Insights from a Cross-Sectional Survey and XGBoost Analysis

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 healthca...

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Autores principales: Wu, Jiangnan, Zhang, Chao, He, Feng, Wang, Yuan, Zeng, Liangnan, Liu, Wei, Zhao, Di, Mao, Jingkun, Gao, Fei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10676671/
https://www.ncbi.nlm.nih.gov/pubmed/38024488
http://dx.doi.org/10.2147/RMHP.S432847
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author Wu, Jiangnan
Zhang, Chao
He, Feng
Wang, Yuan
Zeng, Liangnan
Liu, Wei
Zhao, Di
Mao, Jingkun
Gao, Fei
author_facet Wu, Jiangnan
Zhang, Chao
He, Feng
Wang, Yuan
Zeng, Liangnan
Liu, Wei
Zhao, Di
Mao, Jingkun
Gao, Fei
author_sort Wu, Jiangnan
collection PubMed
description 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.
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spelling pubmed-106766712023-11-22 Factors Affecting Intention to Leave Among ICU Healthcare Professionals in China: Insights from a Cross-Sectional Survey and XGBoost Analysis Wu, Jiangnan Zhang, Chao He, Feng Wang, Yuan Zeng, Liangnan Liu, Wei Zhao, Di Mao, Jingkun Gao, Fei Risk Manag Healthc Policy Original Research 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. Dove 2023-11-22 /pmc/articles/PMC10676671/ /pubmed/38024488 http://dx.doi.org/10.2147/RMHP.S432847 Text en © 2023 Wu et al. https://creativecommons.org/licenses/by-nc/3.0/This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/ (https://creativecommons.org/licenses/by-nc/3.0/) ). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Wu, Jiangnan
Zhang, Chao
He, Feng
Wang, Yuan
Zeng, Liangnan
Liu, Wei
Zhao, Di
Mao, Jingkun
Gao, Fei
Factors Affecting Intention to Leave Among ICU Healthcare Professionals in China: Insights from a Cross-Sectional Survey and XGBoost Analysis
title Factors Affecting Intention to Leave Among ICU Healthcare Professionals in China: Insights from a Cross-Sectional Survey and XGBoost Analysis
title_full Factors Affecting Intention to Leave Among ICU Healthcare Professionals in China: Insights from a Cross-Sectional Survey and XGBoost Analysis
title_fullStr Factors Affecting Intention to Leave Among ICU Healthcare Professionals in China: Insights from a Cross-Sectional Survey and XGBoost Analysis
title_full_unstemmed Factors Affecting Intention to Leave Among ICU Healthcare Professionals in China: Insights from a Cross-Sectional Survey and XGBoost Analysis
title_short Factors Affecting Intention to Leave Among ICU Healthcare Professionals in China: Insights from a Cross-Sectional Survey and XGBoost Analysis
title_sort factors affecting intention to leave among icu healthcare professionals in china: insights from a cross-sectional survey and xgboost analysis
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10676671/
https://www.ncbi.nlm.nih.gov/pubmed/38024488
http://dx.doi.org/10.2147/RMHP.S432847
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