The COVID-19 pandemic, which emerged as a global health crisis in late 2019, profoundly impacted health worldwide. By early 2022, the World Health Organization (WHO) reported a significant rise in global COVID-19 cases, with a sharp increase in reported cases, totaling approximately 23.5 million weekly (World Health Organization, 2024). The COVID-19 pandemic heightened stress, anxiety, and uncertainty due to increased cases and hospitalizations. These factors significantly impact sleep, causing disturbances, disrupted routines, and changes in work environments, particularly affecting frontline workers like nurses in Eds (Madkhali et al., 2022; Guerrera et al., 2024). The surge in patient numbers overwhelmed healthcare systems, especially in EDs, increasing the workload for nurses. This resulted in longer, irregular hours and disrupted sleep patterns, leading to sleep problems, anxiety, and depression (Pollard et al., 2020).

Quality sleep is crucial for nurses in high-stress environments like EDs; it is essential for maintaining physical and mental wellbeing, cognitive function, and overall quality of life (Abraham et al., 2017; Zeng et al., 2020). Nurses regularly face numerous work-related pressures, including heavy workloads, the need to manage interactions with patients and their families, shift work, and overtime (Bae and Fabry, 2014; Alshammari et al., 2022). Sleep problems among nurses, including insomnia, insufficient sleep, deprivation, and poor quality, are prevalent, with rates ranging from 57 to 83% (Qiu et al., 2020) and up to 50% worldwide experience short sleep durations (Furihata et al., 2020; Stimpfel et al., 2020). Low-quality sleep will not only affect their health and wellbeing but also has significant implications for patient care and safety as it can impair cognitive functions such as memory, attention, and decision-making, which are critical in the fast-paced and often high-stakes environment of an ED.

The unique stressors of the COVID-19 pandemic, including the fear of virus contraction, treating severely ill patients, and witnessing suffering, contribute to increased stress and anxiety among ED nurses (Fawaz et al., 2020). The pandemic also alters ED working conditions, with added complexities like personal protective equipment (PPE) and infection control protocols, impacting nurses’ physical exhaustion and sleep quality (Fawaz et al., 2020; Hoedl et al., 2021). The nature of shift work, especially night shifts inherent in emergency nursing, significantly affects the sleep quality of ED nurses. This, combined with rotating schedules, can disrupt circadian rhythms, leading to shift work sleep disorder. The pandemic’s demand for extended and irregular shifts further exacerbates these disruptions, impacting sleep quality (Dong et al., 2020).

Several factors influence their sleep quality, including gender, marital status, exercise habits, monthly income, and patient load (Krueger and Friedman, 2009). Female nurses often report poorer sleep quality due to the additional societal and domestic responsibilities they bear, which increase their stress levels (Almeida et al., 2020). Marital status also impacts sleep quality, with various statuses such as being single, married, divorced, or widowed influencing stress and sleep patterns differently (Troxel et al., 2007). Regular physical exercise is known to improve sleep quality by reducing stress and anxiety (Kredlow et al., 2015). Financial stability, indicated by higher monthly income, is associated with better sleep quality due to reduced financial stress and access to comfortable living conditions (Du et al., 2021). Lastly, the number of patients a nurse is responsible for during a shift significantly affects their stress levels, which in turn impacts sleep quality, with higher patient loads leading to increased stress and poorer sleep (Aiken et al., 2002). These factors, particularly in the context of nurses, need to be thoroughly explored to understand their impact on sleep quality. Poor sleep quality not only affects nurses directly but also has broader implications for healthcare systems and patient care. Studies show that sleep issues can reduce productivity, potentially lowering nursing care standards (Dong et al., 2017). Sleep-deprived nurses may struggle to maintain attention and vigilance, crucial for patient safety and effective care delivery (Stimpfel et al., 2020), increasing the risk of errors, a significant concern in EDs (Wardle-Pinkston et al., 2019).

The research aims to provide valuable insights into the pandemic’s impact on healthcare workers, specifically focusing on the sleep quality of ED nurses. It seeks to inform strategies for supporting their health and wellbeing by addressing the challenges they face during the pandemic (Alshammari et al., 2023). Additionally, the study aims to contribute to the broader discourse on healthcare worker support during crises, emphasizing the necessity of systemic changes to ensure their wellbeing, considering their integral role in healthcare systems.

Aim of the study: This study aimed to explore the quality of sleep among nurses working in EDs and its influencing factors during the COVID-19 pandemic.

Research questions:

Research hypothesis

Table 1 shows that most of the respondents (55.6%) aged between 30 and 39 years old, with an overall mean (SD) of 33.1 (6.6). A higher proportion were females (73.6%), married (64.4%), had bachelor’s degrees (69.4%), almost two-thirds of the nurses (42.1%) earned a monthly salary of 6,000–8,000 Saudi Riyal and 47.2% of them were having one to three dependents. Regarding their working status, the results show that the majority of nurses were registered nurses (56.5%), 46.3 of them had night shifts at least 7 times a month, 47.7 % worked for at least 45 h a week, and 56.9 % of them had less than 30 patients admitted per shift. As regards the health-related factors; 44.0 % of the studied nurses had normal BMI, 77.3 % of them took tea and coffee daily, slightly more than half practice smoking daily (50.9%). However, 6.9% of them never smoke, and 58.8% of them were sometimes practicing exercise.

Table 2 reveals that highest mean scores of the PSQI components were for Component 5 (sleep disturbances), Component 1 (subjective sleep quality), Component 3 (sleep duration), and Component 4 (habitual sleep efficiency), with a global mean score of 10.55. It was also notable that the score for the use of sleep medications among nurses is relatively low (1.44), suggesting a relatively infrequent reliance on pharmacological aids for sleep. The mean score for daytime disfunction was 0.42, indicating relatively high efficiency of daily work among the participants even with poor sleep quality.

Figure 1 illustrates that 81.5% of the participants were categorized as having poor sleep quality according to the PSQI scale. Conversely, only 18.5% of them demonstrated normal sleep quality.

As shown in Table 3, the overall mean scores of the PSQI were significantly associated with gender, marital status, monthly income, patient load per shift, and practicing exercise. Female nurses, those who had moderate income, who had higher number of admitted patients per shift, and those who never practice exercise had higher mean PSQI scores indicative of poorer sleep quality compared to other categories (p-value < 0.05). However, there were no significant differences in sleep quality across other variables.

Table 4 Presents that The PSQI of the studied subjects was best predicted by gender, income, and workload (number of patients in the charge of night shift).

This study aims to investigate the sleep quality of Saudi emergency nurses during the COVID-19 pandemic and identify the factors influencing it. Sleeping problems are common among nurses and could have a variety of unpleasant effects. A change in sleep quality might impair productivity and lower the standard of nursing care (Dong et al., 2020).

The findings of the current study showed that a majority of respondents (81.5%) experienced poor sleep quality (Figure 1), with a global mean PSQI score of 10.55 (Table 2), indicative of poor sleep quality among nurses. This finding is consistent with findings from other studies, including those by Furihata et al. (2020), Khatony et al. (2020), Qiu et al. (2020), Stimpfel et al. (2020), and Vadi et al. (2022), all of which reported the poor sleep quality is a common problem among nurses. Further supporting this, Dong et al. (2017) found that 64% of nurses reported sleep disturbances within the nursing profession.

The sleep quality among the nurses in this study was found to be associated with gender, as female nurses exhibiting higher instances of poor sleep quality. This observation aligns with the findings of Cattani et al. (2021), who also reported an association between sleep quality and gender. Similarly, Alharbi et al. (2021) noted that being female was linked to poorer sleep. Additionally, Yilmaz et al. (2021), concluded that female nurses were more prone to experiencing poor sleep quality. The observed findings can be interpreted through various ways. Female nurses often have to balance their professional duties with familial caregiving responsibilities (Yilmaz et al., 2021). This dual role can elevate stress levels and limit the time available for restful sleep (DePasquale et al., 2019). Another explanation is the hormonal changes associated with the menstrual cycle, pregnancy, and menopause can profoundly affect sleep patterns, as noted by Baker and Lee (2022). Societal and cultural expectations can influence sleep quality. In many cultures, women face additional pressures that can lead to increased stress and disrupted sleep (Knutson, 2013). Additionally, some studies have proposed that women are generally more likely than men to recognize and report problems associated with sleep disturbances (Knutson, 2013).

Furthermore, a link was found between sleep quality and monthly income, where emergency nurses earning lower salaries experienced more sleep difficulties. This finding aligns with Gao et al. (2022) research, which identified low monthly income as a contributing factor to poor sleep quality in most participants. Similarly, a study conducted in Jordan by Suleiman et al. (2020) established a positive correlation between the amount of salary and sleep quality, further emphasizing the impact of income on sleep. The findings can be attributed to several factors. Financial stress from lower income can increase anxiety and worry, adversely affecting sleep. Additionally, lower income often limits access to a conducive sleep environment, potentially resulting in less comfortable living conditions and exposure to disruptive factors like noise and inadequate temperature control (Johnson et al., 2018).

Besides personal factors, the study found that the quantity of patients a nurse managed per shift associated negatively with their sleep quality (the higher the number of patients, the higher PSQI scores and poor sleep). This aligns with findings from a French longitudinal cohort study by Badahdah et al. (2020), which connected sleep issues to both intensive labor and extended workdays. Supporting this, research by Dong et al. (2017) and Dong et al. (2020) suggests that primary and registered nurses are particularly prone to sleep disorders. Factors such as longer working hours and the patient load per shift were also identified as contributors to reduced sleep quality. Dealing with more patients, especially in an ED setting, often involves managing critical and high-stress situations. This can lead to emotional and mental fatigue, which makes it harder to unwind and achieve restful sleep.

Our study’s results show that sleep quality was not significantly associated with sociodemographic factors such as age, education level, and professional rank. This aligns with findings by Johnson et al. (2018) and Segon et al. (2022), who also reported no significant correlation between age, educational status, and sleep deprivation. In addition, Badahdah et al. (2020) and Wang et al. (2021) observed no substantial link between poor sleep quality and professional rank in their research.

The current findings indicate a statistically significant difference in the PSQI total scores among nurses in relation to their exercise habits. This might be due to the stress-reducing effects of exercise, which in turn could improve sleep quality. This observation is consistent with the studies by Strand et al. (2013) and Chen et al. (2022), which noted that the frequency of exercise positively influenced the sleep quality of nurses.

Our study’s results indicate that there was no significant association between poor sleep quality and habits like smoking or consuming tea and coffee. This contrasts with the findings of Strand et al. (2013), Omar et al. (2022), and Sayik et al. (2022), who observed that both smokers and tea/coffee drinkers tended to have lower overall PSQI-mean scores, suggesting poorer sleep quality. This difference in findings could be attributed to factors such as the timing and quantity of smoking or caffeine consumption. Specifically, consuming caffeine later in the day may have a more significant impact on sleep compared to morning intake. This variable, which can crucially affect sleep quality, might not have been consistently accounted for across different studies. Additionally, it’s noteworthy that our study did not measure these aspects, which could further explain the variation in results.

In relation to predictor variables of sleep quality, the present study showed that sleep quality among the studied subjects was best predicted by gender, income, and workload (number of patients in the charge of night shift), answering research question (2). These findings were in the same line with (Kim-Godwin et al., 2021), who pointed out that the nurses working full time (t = 2.41, p = 0.02), showed poor overall sleep quality. While these findings contradicted (Chen et al., 2022) who revealed that nurse managers’ sleep quality can be greatly affected by demographic characteristics such as their ages and exercise regularity.

This study has several limitations that should be considered. Firstly, the cross-sectional nature of the research design prevents the establishment of cause-and-effect relationships. Secondly, focusing on a specific government institution in the northern region of Saudi Arabia raises concerns regarding selection bias, thus limiting the generalizability of the findings. Additionally, exclusively including emergency nurses, may not accurately reflect the experiences of nurses in other specialties or departments, cautioning against extrapolating these findings to a broader nursing population. Furthermore, the study did not account for some potentially relevant factors, such as the psychological impact of the COVID-19 pandemic, individual health conditions, or personal coping mechanisms, which might influence sleep quality. Moreover, there is a possibility that some observed disturbances may be normative rather than solely attributable to the pandemic. Factors beyond the pandemic, such as societal stressors and individual circumstances, may contribute to sleep disruptions during the study period. Therefore, we encourage future research to explore these complexities further, ensuring a nuanced understanding of sleep disturbances in the context of both pandemics and broader societal influences. Finally, the study failed to explore the influence of COVID-related stress on sleep quality among nurses. This overlooks a crucial aspect of their wellbeing, particularly in high-stress environments like EDs during the pandemic. Future research should examine this association to provide a more comprehensive understanding of nurses’ sleep patterns.

The study reveals a high prevalence of poor sleep quality among emergency nurses during the COVID-19 pandemic. Factors such as gender, marital status, monthly income, the number of patients managed per shift, and exercise habits significantly associated with poor sleep quality in this group. These findings underline the multifaceted nature of sleep disturbances in a high-stress healthcare environment and emphasize the need for targeted interventions to address these issues. Healthcare institutions should consider implementing policies and programs aimed at improving sleep quality among nurses. This could include scheduling reforms to reduce overwork, stress reduction workshops, and health promotion activities that encourage exercise. Creating a support system within the workplace to address the unique challenges faced by different demographic groups, such as female nurses or those with lower incomes, is also crucial.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Ethical approval for the study was obtained from the Institutional Review Board (IRB), represented by the Health Cluster in Hail city [registered with the King Abdullah City for Science and Technology (KACS) in the KSA, under the registration number H-08-L-074, with Approval No: 2022-23]. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

AwA: Writing – original draft, Writing – review & editing. MA: Writing – original draft, Writing – review & editing. BA: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Software, Supervision, Validation, Visualization, Writing – original draft, Writing – review & editing. FA: Writing – original draft, Writing – review & editing. AsA: Writing – original draft, Writing – review & editing. TAA: Writing – original draft, Writing – review & editing. SM: Writing – original draft, Writing – review & editing. DC: Writing – original draft, Writing – review & editing. MB: Writing – original draft, Writing – review & editing. AhA: Writing – original draft, Writing – review & editing. OE: Writing – original draft, Writing – review & editing. SN: Writing – original draft, Writing – review & editing. RA: Writing – original draft, Writing – review & editing. TNA: Writing – original draft, Writing – review & editing. HA: Writing – original draft, Writing – review & editing. BS: Data curation, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing.