Mental workload of frontline nurses aiding in the COVID‐19 pandemic: A latent profile analysis.
Aims: To investigate the mental workload level of nurses aiding the most affected area during the Coronavirus disease 2019 (COVID‐19) pandemic and explore the subtypes of nurses regarding their mental workload. Design: Cross‐sectional study. Methods: A sample of 446 frontline nurses participated fro...
| Publicado en: | Journal of Advanced Nursing (John Wiley & Sons, Inc.) Vol. 77; no. 5; pp. 2374 - 2386 |
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| Autores principales: | , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
John Wiley & Sons, Inc.
May2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=149651713&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 149651713 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 03092402 LVDY jtl: Journal of Advanced Nursing (John Wiley & Sons, Inc.) issn: 03092402 maglogo: N pubinfo: dt: May2021 vid: 77 iid: 5 pid: 52269 pub: John Wiley & Sons, Inc. artinfo: ui: 149651713 148744450 149651713 149651713 10.1111/jan.14769 149651713 ppf: 2374 ppct: 12 formats: tig: atl: Mental workload of frontline nurses aiding in the COVID‐19 pandemic: A latent profile analysis. aug: au: Shan, Yawei Shang, Jing Yan, Yan Lu, Gendi Hu, Deying Ye, Xuchun affil: School of Nursing, Naval Medical University (Second Military Medical University), Shanghai University of Traditional Chinese Medicine, Shanghai, China sug: subj: Task Performance and Analysis Workload Measurement Nursing Staff, Hospital Psychosocial Factors COVID-19 Pandemic Psychosocial Factors Human Cross Sectional Studies Scales Socioeconomic Factors Coping Self Assessment Workload Descriptive Statistics Employment Status Income Psychological Well-Being China Funding Source Self Report Questionnaires Summated Rating Scaling Data Analysis Software T-Tests One-Way Analysis of Variance Chi Square Test Female Male Adult Stress, Occupational Adult: 19-44 years Female Male ab: Aims: To investigate the mental workload level of nurses aiding the most affected area during the Coronavirus disease 2019 (COVID‐19) pandemic and explore the subtypes of nurses regarding their mental workload. Design: Cross‐sectional study. Methods: A sample of 446 frontline nurses participated from March 8 to 19, 2020. A latent profile analysis was performed to identify clusters based on the six subscales of the Chinese version of the National Aeronautics and Space Administration Task Load Index. The differences among the classes and the variables including sociodemographic characteristics, psychological capital and coping style were explored. Results: The level of mental workload indicates that the nurses had high self‐evaluations of their performance while under extremely intensive task loads. The following three latent subtypes were identified: 'low workload & low self‐evaluation' (8.6%); 'medium workload & medium self‐evaluation' (35.3%) and 'high workload & high self‐evaluation' (56.1%) (Classes 1, 2, and 3, respectively). Nurses with shared accommodations, fewer years of practice, junior professional titles, lower incomes, nonmanagement working positions, lower psychological capital levels and negative coping styles had a higher likelihood of belonging to Class 1. In contrast, senior nurses with higher psychological capital and positive coping styles were more likely to belong to Classes 2 and 3. Conclusion: The characteristics of the 'low workload & low self‐evaluation' subtype suggest that attention should be paid to the work pressure and psychological well‐being of junior nurses. Further research on regular training program of public health emergency especially for novices is needed. Personnel management during public health events should be focused on the allocation between novice and senior frontline nurses. Impact: This study addresses the level of mental workload of frontline nurses who aid in the most severe area of the COVID‐19 pandemic in China and delineates the characteristics of the subtypes of these nurses. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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