Prevalence and factors associated with poor sleep quality among nurses in COVID-19 wards.

Prevalence and factors associated with poor sleep quality among nurses in COVID-19 wards.

Publication date: Jul 18, 2024

The COVID-19 pandemic has significantly impacted the working conditions of nurses, leading to a detrimental effect on their sleep quality. This cross-sectional study aimed to investigate the prevalence of poor sleep quality and its associated factors among nurses working in COVID-19 wards in Kermanshah, Iran. A total of 97 nurses were selected through simple random sampling from COVID-19 wards. Data was collected using a demographic information sheet and the Pittsburgh Sleep Quality Index. Descriptive and inferential statistical methods, including chi-square and multiple logistic regression, were used for data analysis. The results showed that 74. 2% (n = 72) of the nurses experienced poor sleep quality. Significant associations were found between poor sleep quality and work experience (p = 0. 045) as well as the type of work shift (p = 0. 001). However, no significant relationships were observed between poor sleep quality and factors such as age, sex, body mass index, overtime hours per month, physical activity, or underlying diseases. The high prevalence of poor sleep quality among nurses working in COVID-19 wards underscores the necessity of implementing targeted interventions to address this issue. In this regard, in addition to periodic shift schedule changes and reductions in working hours, it is necessary to adopt purposeful measures to improve working conditions and enhance the physical and mental health of nurses. These measures may include providing sufficient human resources to reduce the workload and fatigue of nurses, appropriate scheduling of working hours, and the implementation of stress management programs.

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Concepts Keywords
Iran Adult
Nurses COVID-19
Overtime COVID-19
Pandemic Cross-Sectional Studies
Sleep Female
Humans
Iran
Male
Middle Aged
Nurses
Nurses
Nursing Staff, Hospital
Prevalence
Prevalence
Risk Factors
SARS-CoV-2
Sleep disorders
Sleep Quality
Surveys and Questionnaires
Young Adult

Semantics

Type Source Name
disease MESH sleep quality
disease MESH COVID-19
drug DRUGBANK Coenzyme M
disease MESH Sleep disorders
disease MESH hypertension
disease VO population
drug DRUGBANK Etoperidone
disease VO Gap
drug DRUGBANK Methionine
disease MESH marital status
disease VO monthly
disease IDO history
disease MESH sleep latency
disease VO efficiency
disease IDO process
disease IDO quality
disease VO time
disease VO frequency
disease MESH overweight
disease VO volume
disease MESH infection
disease MESH retirement
pathway KEGG Circadian rhythm
drug DRUGBANK Pentaerythritol tetranitrate
disease MESH obesity
disease MESH insomnia
disease MESH weight gain
disease MESH cardiovascular diseases
disease VO effective
disease IDO intervention
disease MESH lifestyle
disease MESH cognitive impairments
drug DRUGBANK Trestolone
disease MESH Burnout
drug DRUGBANK Copper
disease MESH emergency
disease MESH job stress
disease MESH sleepiness
disease VO protocol
disease MESH sleep deprivation
disease VO report

Original Article

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