Analysis of mental health symptoms and insomnia levels of intensive care nurses during the COVID-19 pandemic with a structural equation model

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dc.authorid0000-0003-2690-2179en_US
dc.authorid0000-0002-2924-272Xen_US
dc.contributor.authorKandemir, Didem
dc.contributor.authorTemiz, Zeynep
dc.contributor.authorÖzhanlı, Yasemin
dc.contributor.authorErdoğan, Hatice
dc.contributor.authorKanbay, Yalçın
dc.date.accessioned2024-07-12T21:21:12Z
dc.date.available2024-07-12T21:21:12Z
dc.date.issued2021en_US
dc.departmentYüksekokullar, Hemşirelik Yüksekokulu, Hemşirelik Bölümüen_US
dc.description.abstractBackground: Faced with this critical situation and directly involved in the treatment and care of COVID-19 patients, front-line healthcare workers are at high risk in terms of mental health symptoms. Aims and Objectives: To determine the stress, anxiety, depression, and insomnia levels of intensive care nurses during the pandemic with a structural equation model. Design: A multi-site survey study. Methods: The study was performed with 194 nurses working in the intensive care units of five hospitals in Istanbul in July 2020. Data were collected using the Depression Anxiety Stress-21 Scale and Insomnia Severity Index electronically. The data were evaluated with descriptive statistics in SPSS package program. In order to test the structural model and hypotheses of the research, path analysis was performed with LISREL statistical software program. A validation study for the suitability of these scales to the study sample was done by the researchers using the confirmatory factor analysis method. The study conforms to the TREND checklist. Results: In this study, the majority of the intensive care nurses had moderate to extremely severe depression (65.5%), anxiety (58.3%) and stress (72.3%) scores; in addition, 39.7% of the nurses experienced moderate or severe insomnia. Within the framework of a structural model; the effects of stress, anxiety and insomnia on depression, which is the dependent variable, were found to be statistically significant (p < .001). Conclusions: It was found that the majority of the intensive care nurses fighting COVID-19 on the front-line experienced stress, anxiety, depression and insomnia at levels ranging from moderate to extremely severe; in addition, it was determined that there is a positive relationship between stress, anxiety, insomnia and depression. Relevance to clinical practice: This study, in which we have determined the mental health symptoms and insomnia levels of intensive care nurses, who are in the frontline during the COVID-19 pandemic, constitutes the scientific basis for the effective coping strategies that the authorities will take in this subject.en_US
dc.identifier.citationKandemir, D., Temiz, Z., Özhanlı, Y., Erdoğan, H. and Kanbay, Y. (2021). Analysis of mental health symptoms and insomnia levels of intensive care nurses during the COVID-19 pandemic with a structural equation model. Journal Of Clinical Nursing, 31, p.601-611.en_US
dc.identifier.doi10.1111/jocn.15918
dc.identifier.endpage611en_US
dc.identifier.pmid34121260en_US
dc.identifier.scopus2-s2.0-85107811458en_US
dc.identifier.startpage601en_US
dc.identifier.urihttps://doi.prg/10.1111/jocn.15918
dc.identifier.urihttps://hdl.handle.net/20.500.12415/5250
dc.identifier.volume31en_US
dc.identifier.wosWOS:000661018300001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.institutionauthorKandemir, Didem
dc.institutionauthorErdoğan, Hatice
dc.language.isoenen_US
dc.publisherWileyen_US
dc.relation.ispartofJournal Of Clinical Nursingen_US
dc.relation.publicationcategoryUluslararası Hakemli Dergide Makale - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.snmzKY01855
dc.subjectCOVID-19en_US
dc.subjectInsomniaen_US
dc.subjectIntensive care nursingen_US
dc.subjectMental healthen_US
dc.subjectPandemicen_US
dc.titleAnalysis of mental health symptoms and insomnia levels of intensive care nurses during the COVID-19 pandemic with a structural equation modelen_US
dc.typeArticle
dspace.entity.typePublication

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