Machine learning-driven identification of key risk factors for predicting depression among nurses

Background Since the outbreak of the coronavirus disease (COVID-19) in 2019, caused by SARS-CoV-2, the disease has become a global health threat due to its high infectivity, morbidity, and mortality rates. With China’s comprehensive relaxation of pandemic control policies in 2022, the risk of infect...

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Bibliographic Details
Published in:	BMC nursing Vol. 24; no. 1; pp. 368 - 11
Main Authors:	Qi, Xiaoyan, Huang, Xin
Format:	Journal Article
Language:	English
Published:	London BioMed Central 03.04.2025 BioMed Central Ltd Springer Nature B.V BMC
Subjects:	China COVID-19 Cross-sectional study Datasets Depression Depression, Mental Epidemics Full reopening Health aspects Health risks Hospitals Infections Insomnia Machine learning Medicine Medicine & Public Health Mental depression Mental disorders Mental health Nurses Nursing Nursing Management Nursing Research Pandemics Patients Psychological aspects Questionnaires Risk factors Sample size Statistical models Stress China Anhui China COVID-19 Full reopening Machine learning Depression Cross-sectional study Risk factors Python
ISSN:	1472-6955, 1472-6955
Online Access:	Get full text
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