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Prediction model for abnormal eating behaviour among hospital nurses: A structural equation modelling approach

Title
Prediction model for abnormal eating behaviour among hospital nurses: A structural equation modelling approach
Authors
Kim O.Jung H.
Ewha Authors
김옥수
SCOPUS Author ID
김옥수scopus
Issue Date
2021
Journal Title
International Journal of Nursing Practice
ISSN
1322-7114JCR Link
Citation
International Journal of Nursing Practice vol. 27, no. 5
Keywords
depressioneating behavioureating disordernursesshift worksleep
Publisher
John Wiley and Sons Inc
Indexed
SCIE; SSCI; SCOPUS WOS scopus
Document Type
Article
Abstract
Background: Nurses are at a high risk of developing abnormal eating behaviour. However, few studies have attempted to identify the factors that influence such behaviour. Aim: This study identifies factors that can predict abnormal eating behaviour in hospital nurses. Design: This study adopted a cross-sectional, descriptive correlational research design. Methods: A literature review was used to establish a hypothetical model, comprising the eight factors of shift work, job stress, depression, sleep quality, fatigue, coping strategy (active coping and passive coping) and abnormal eating behaviour. A convenience sample of 298 nurses aged less than 45 was recruited from two university hospitals, and structured questionnaire was administered between March and April 2017. The hypothesized model was tested using structural equation modelling. Results: Sleep quality and passive coping directly affect abnormal eating behaviour, which implies that poor sleep quality and increased passive coping worsens the behaviour. Shift work and depression indirectly affect abnormal eating behaviours. Conclusion: Nursing managers and health policy makers should adopt strategies such as improving the shift-work pattern, providing adequate rest time after a night shift and enabling coping strategies by providing educational programs for hospital nurses. © 2021 John Wiley & Sons Australia, Ltd
DOI
10.1111/ijn.13006
Appears in Collections:
간호대학 > 간호학전공 > Journal papers
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