• Preventive medicine · Oct 2023

    Latent class analysis of healthcare workers' perceptions of workers' job demands in mobile cabin hospitals in China.

    • Hongmei Yi, Sha Wei, Jingyan Song, Mingzhao Xiao, Li Wang, and Qinghua Zhao.
    • Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
    • Prev Med. 2023 Oct 1; 175: 107678107678.

    BackgroundOwing to the outbreak of the Omicron variant of SARS-CoV-2 in Shanghai, China, partitioned dynamic closure and control management plans were implemented on March 28, 2022. This created huge emergency pressure on Shanghai's medical and healthcare systems. However, the perceptions of job demands of healthcare workers (HCWs) and classification of frontline HCWs in mobile cabin hospitals are unknown.MethodsIn this study, we investigated the job demands of 1223 frontline HCWs working in mobile cabin hospitals during the COVID-19 pandemic April 2022 to May 2022. We performed latent class analysis to identify classification features of job demands. A binary multivariate logistic regression model was used to explore the influencing factors of latent class.ResultsThe total mean job demand score was 132.26 (SD = 9.53), indicating a high level of job demand. A two-class model provided the best fit. The two classes were titled "middle-demand group" (17.66%) and "high-demand group" (82.34%). A regression analysis suggested that female HCWs, HCWs satisfied with the doctor/nurse-patient relationship, HCWs who believed that the risk of working in mobile cabin hospitals was high, and HCWs without physical discomfort during the pandemic were more likely to be in the "high-demand group".ConclusionCharacteristics of the "high-demand group" subtype suggest that attention should be paid to the physical condition of frontline HCWs and the job demands of female HCWs. Managers should strengthen the training of HCWs in terms of their communication skills as well as their knowledge and technical skills to aid epidemic prevention and control.Copyright © 2023. Published by Elsevier Inc.

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