Sleep quality among emergency nurses and its influencing factors during COVID-19 pandemic: a cross-sectional study
Abstract
Background COVID-19 has probably contributed to sleep disturbance among nurses, especially those working at emergency departments (EDs). Sleep disorders in nurse managers can negatively impact their health and impair work performance and decision-making. This study aimed to explore the quality of sleep among nurses working in EDs and its influencing factors during the COVID-19 pandemic. Method In this study, a cross-sectional design was employed to assess the sleep quality of nurses working in EDs during the COVID-19 pandemic. The research recruited a convenience sample of emergency nurses, who were selectively sourced from four hospitals in Hail City. This recruitment occurred over the period from April to July 2022. Descriptive data analysis was conducted using SPSS, with the significance level set at 0.05. Results Among the 216 participants in the study, the majority (55.6%) were aged between 30 and 39 years, and 73.6% were female. Additionally, 64.4% were married, while 69.4% had a bachelor’s degree, 20% held a diploma, and the remaining had a master’s degree. Notably, a significant 81.5% of the nurses reported poor sleep quality, as assessed by the Pittsburgh Sleep Quality Index (PSQI), with an overall mean score of 10.55 indicating poor sleep. The study highlighted that poor sleep quality among nurses was linked to being female, being married, and not exercising regularly. Better sleep was associated with nurses who manage fewer patients per shift and have adequate…
How strong is the evidence?
Evidence Hub reads this as a cross-sectional, done in people. Its evidence level is 4 of 5 (Low · observational). Observational designs can show an association but not prove cause. Reported size: 216 participants or records.
Read the paper
Related studies
- The Matrisome: In Silico Definition and In Vivo Characterization by Proteomics of Normal and Tumor Extracellular Matrices
- The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities
- In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling
- In silico prediction of splice-altering single nucleotide variants in the human genome
- In silico clinical trials: how computer simulation will transform the biomedical industry
- In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.