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

Background 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 ca...

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Veröffentlicht in:Journal of clinical nursing 2022-03, Vol.31 (5-6), p.601-611
Hauptverfasser: Kandemir, Didem, Temiz, Zeynep, Ozhanli, Yasemin, Erdogan, Hatice, Kanbay, Yalcin
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Sprache:eng
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Zusammenfassung:Background 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 
ISSN:0962-1067
1365-2702
DOI:10.1111/jocn.15918