Background
Quality of work life (QWL) is a comprehensive approach that aims to sustain and improve performance through maintaining employees’ well-being [1]. It is an integrative strategy that improves employee satisfaction and is necessary for attracting and retaining them [2, 3]. Recently, improving QWL has become a global concern and organizations are striving to achieve this objective [4]. The health and well-being of the nurses have a great impact on the clinical performance and the quality of care services provided for patients. Therefore, improvement of QWL is essential for them [5]. QWL that experience of nurses consists of compassion satisfaction (positive aspect) and compassion fatigue (negative aspect). Burnout and secondary traumatic stress are two components of the compassion fatigue. Factors such as work-related stress, work‒life imbalance, and rotation shifts can significantly impact nurses’ QWL [6]. Although nurses have been trained to provide patient care and improve their patient’s quality of life, their QWL has been largely ignored [7]. A recent study reported that low QWL during the COVID-19 pandemic was associated with burnout, job dissatisfaction, fatigue, work‒life imbalance and impairment of psychological health [8], High levels of compassion fatigue can directly influence mental health in nurses such as sleep disorders [9].Therefore, nurse managers must be responsible for nurses’ QWL. A study among intensive care units (ICUs) and emergency nurses revealed that extra working hours were a determinant of lower QWL among nurses [10]. ICUs can be stressful because of critical life-threatening situations and high levels of morbidity, mortality, and ethical dilemmas [11]. ICU nurses encountered staffing shortages, heavy workloads, increased patient turnover and inadequate medical supplies and resources [12, 13]. As a result, nurses were faced a tremendous amount of stress in the workplace which affected adversely on their sleep quality [13].Poor sleep quality is a prevalent concern among nurses, with substantial implications for their physical health and psychological well-being [14]. This may lead to a number of negative outcomes, such as medical errors [15], fatigue, reduced quality of care [16], job dissatisfaction, burnout, and absenteeism, all of which negatively impact nurses and threaten patients’ safety [8]. The prevalence of this problem among nurses varies across countries. For example, in the United States, 77.4% of nurses working in six hospitals reported poor sleep quality [17]. In China, 76.3% of emergency nurses reported poor sleep [18]. In Iran, 74.2% of nurses in the context of the pandemic experienced poor sleep quality [19]. Many factors were associated with poor sleep quality including: high occupational stress, frontline work, workload, female gender, less exercise, long work hours per week, inappropriate nurse - patient ratio, lack of social support, night shift, years of work experience, anxiety, worried about being infected, and degree of fear with COVID-19 [18, 20].
A study conducted on oncology and ICU nurses revealed that ICU nurses had poorer sleep quality than oncology nurses. ICU nurses often need to deal with critical patients, which may lead to serious psychological harm [21]. A recent meta-analysis revealed that the sleep quality of frontline healthcare providers during the COVID-19 pandemic was significantly poorer than that of the general population [20]. Sleep quality play a mediating role in the relationship between perceived stress and job burnout. A higher level of perceived stress leads to poorer sleep quality and results in an increased risk of burnout [22].
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Considering the importance and vital role of ICU nurses in providing nursing care, the evaluation of the status of QWL and sleep quality is essential for nurse managers and policymakers to plan and employ interventions to improve nurses and patient outcomes. However, few studies have investigated the QWL and sleep quality of ICU nurses, along with their associated factors, during the COVID-19 pandemic in developing countries, especially Iran. Moreover, given that the factors that influence sleep quality among ICU nurses during the COVID-19 crisis may vary across different contexts and healthcare settings worldwide, the effect of context cannot be ignored. Therefore, the present study aimed to examine the relationship between professional quality of life (Pro QOL) and sleep quality among ICU nurses during the COVID-19 pandemic.
Study design
This cross-sectional and multicentre descriptive study was conducted on 273 nurses in 20 COVID-19 ICUs in four major educational hospitals in Shiraz, Iran, from July 2021 to June 2022. The sampling method was stratified randomly with a proportional allocation.
Participants and setting
The sample size was calculated via G* Power software with a power of 80%, an α of 0.05 and, using a similar method [23], considering correlation-coefficient between two variables the QWL and sleep quality (r = 0.18). The calculated sample size came to be 240. Further, taking a 14% attrition rate, a sample size of 273 participants was determined.
The study population consisted of all nurses working in the adult COVID-19 ICUs of university teaching hospitals. The inclusion criteria for participants included willingness to participate in the study, a bachelor’s degree in nursing, and at least six months of clinical experience working in a COVID-19 ICU. The use of psychiatric or hypnotic medications, history of mental or sleep disorders and incomplete completion of the questionnaire served as the exclusion criteria.
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Measures
Data were collected via a demographic and clinical information form including eight items: age, sex, marital status, education, years of work experiences in the ICU, type of ICU, type of shift, and history of infection with coronavirus, Professional Quality of Life Scale (ProQOL) Version 5 (2009), and the Pittsburgh Sleep Quality Index (PSQI).
Professional quality of life scale
The ProQOL scale was developed by Stemm [24]. It consists of 30 items divided into 3 subscales: compassion satisfaction (10 items), burnout (10 items), and secondary traumatic stress (10 items). The subscales of burnout and secondary traumatic stress are grouped as compassion fatigue. Each subscale score is determined by the sum of all its items, resulting in a score ranging from 10 to 50 for each subscale. The items are scored on a 5-point Likert scale ranging from 1 (never) to 5 (always). Notably, 5 out of the 10 items on the job burnout scale (items 1, 4, 15, 17, and 29) are inversely scored. A score below 22 on any subscale indicates lower compassion satisfaction, lower job burnout, or lower secondary traumatic stress. A score between 23 and 41 falls within the average range, whereas a score above 42 indicates higher compassion satisfaction, more job burnout, or more secondary traumatic stress. The reliability of the Pro-QOL was assessed via Cronbach’s alpha, which was reported as 0.88 for the compassion satisfaction subscale, 0.75 for job burnout, and 0.81 for secondary traumatic stress. Furthermore, the content validity index (CVI) of this tool has been reported to be 0.83 [24].
In the current study, the Persian version of this tool was utilized, and its validity and reliability were confirmed by Gorji et al. in 2017. The reliability was reported as 0.87 for the compassion satisfaction subscale, 0.87 for job burnout, and 0.74 for secondary traumatic stress, while the Cronbach’s alpha for the entire questionnaire was 0.73. The CVI was calculated as 0.91 [25].
Pittsburgh sleep quality index (PSQI)
The PSQI was developed by Backaus et al. [26] at the Pittsburgh Psychiatric Institute in 1989. The 19-item PSQI assesses sleep patterns during the past month and contains seven subscales of sleep quality: subjective sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disturbances, use of sleep medication, and daytime dysfunction. Each subscale is scored on a 4-point Likert scale from 0 to 3, and the total score ranges from 0 to 21. Higher scores indicate poorer sleep quality. A total score of ≥ 5 indicates poor sleep quality, with a diagnostic sensitivity of 90% and specificity of 87%. The validity and reliability of the PSQI have been established. In this study, the Persian version of the PSQI was used. Torabi et al. (2019) reported that the internal consistency of the entire tool was 0.89, and the CVI was 0.86 [27].
Data analysis
Data analysis was conducted using SPSS version 25, with a significance level set at P < 0.05. The mean of the scores the Pro QOL and the PSQI were not normally distributed (the Shapiro-Wilk test was used to test the distribution of data) (P < 0.05). Analysis was performed using non-parametric tests. Likewise, Kruskal-Wallis that, followed by Dunn- Bonferroni post-hoc test and Mann-Whitney were used to examine the statistical scores between the Pro QOL dimensions and demographic variables. Spearman’s correlation coefficient was used to examine the correlations between the Pro QOL and sleep quality. The correlation coefficient was defined as follows: Correlation coefficients between 0.9 and 1 indicate variables which can be considered very high correlation; 0.7 to 0.9: high correlation; 0.5 to 0.7: moderate correlation; 0.3 to 0.5 weak correlation; and 0.0 to 0.3 very weak [28]. Finally, linear regression analysis was used to assess the impact of the dimensions of the Pro QOL on the overall sleep quality.
Results
Out of the 273 distributed questionnaires, 253 were complete and were analyzed. Twenty questionnaires excluded from the study due to incomplete completion (high rate of missing data) or the decline of participates in returning the questionnaires. Table 1 shows the demographic characteristics of the ICU nurses. The average number of patients per nurse per shift was 2.21 ± 1.37 and an average work experience in the ICUwas 8.20 ± 5.26 years.
Table 1
Demographic characteristics of ICU nurses (n = 253)
Variables | Grouping | number | Percent |
|---|---|---|---|
Age | Under 25 | 10 | 4 |
25–29 | 102 | 40.3 | |
30–34 | 53 | 20.9 | |
35–39 | 53 | 20.9 | |
Over 40 | 35 | 13.8 | |
Gender | male | 56 | 22.1 |
female | 197 | 77.9 | |
Marital Status | Single | 104 | 41.1 |
Married | 125 | 49.4 | |
Others | 24 | 9.5 | |
Educational Level | Bachelor Degree | 216 | 85.4 |
Master Degree | 37 | 14.6 | |
ICU | General | 101 | 39.9 |
Internal | 81 | 32 | |
Neurosurgery | 14 | 5.5 | |
Others | 57 | 22.5 | |
Shift | Fixed | 21 | 8.3 |
Rotation | 232 | 91.7 | |
History of infection with coronavirus | Infected | 182 | 71.9 |
Not Infected | 71 | 28.1 |
The mean and standard deviation of the Pro QOL dimensions for ICU nurses were 33.49 ± 6.77, 32.28 ± 8.83 and 29.58 ± 11.67 for compassion satisfaction, burnout and secondary traumatic stress, respectively. The results indicated that the ICU nurses experienced moderate levels of Pro QOL in compassion satisfaction and compassion fatigue (burnout and secondary traumatic stress). Table 2 shows the demographic and clinical features of the ICU nurses and their associations with the Pro QOL dimensions.
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Table 2
Demographic and clinical features of ICU nurses and their association with pro QOL dimensions (n = 253)
Variable | Compassion Satisfaction Mean ± SD | Burnout Mean ± SD | Secondary Traumatic Stress Mean ± SD | |
|---|---|---|---|---|
Age | < 25 | 37.30 ± 6.34 | 30.10 ± 8.49 | 27.30 ± 11.08 |
25–29 | 33.40 ± 6.87 | 28.77 ± 8.18 | 28.11 ± 10.95 | |
30–34 | 32.71 ± 7.50 | 31.74 ± 9.61 | 30.03 ± 12.51 | |
35–39 | 33.41 ± 5.65 | 33.39 ± 9.10 | 33.83 ± 12.21 | |
> 40 | 34.00 ± 6.93 | 27.27 ± 7.72 | 27.34 ± 10.58 | |
Comparison of age groups | Test Statistics, df = 3.37,4 p = 0.49 | Test Statistics, df = 13.34,4 P = 0.01 | Test Statistics, df = 10.86,4 P = 0.02 | |
Marital Status | Married | 33.75 ± 6.59 | 30.80 ± 9.00 | 30.60 ± 11.7 |
Single | 33.75 ± 7.03 | 29.8 ± 8.50 | 34.27 ± 11.4 | |
Other | 34.03 ± 6.74 | 32.75 ± 8.90 | 33.90 ± 11.04 | |
Comparison of the marital status | Test Statistics, df = 0.65,2 P = 0.71 | Test Statistics, df = 4.36,2 P = 0.11 | Test Statistics, df = 8.19,2 P = 0.01 | |
Gender | male | 32.55 ± 6.25 | 31.32 ± 8.16 | 31.82 ± 11.85 |
female | 33.76 ± 6.90 | 29.70 ± 8.94 | 28.94 ± 11.57 | |
Mann-Whitney Test | Z= -0.88 P = 0.38 | Z=-1.93 P = 0.53 | Z=-1.39 P = 0.16 | |
Educational Level | Bachelor Degree | 33.54 ± 7.06 | 30.30 ± 8.79 | 29.37 ± 11.62 |
Master Degree | 33.19 ± 4.82 | 31.70 ± 8.98 | 30.78 ± 12.02 | |
Mann-Whitney Test | Z=-0.42 P = 0.67 | Z=-1.07 P = 0.28 | Z=-0.65 P = 0.51 | |
Shift | Fixed | 33.71 ± 6.90 | 26.57 ± 6.56 | 24.19 ± 9.62 |
Rotation | 33.47 ± 6.72 | 30.60 ± 8.93 | 30.09 ± 11.73 | |
Mann-Whitney Test | Z=-0.96 P = 0.33 | Z=-2.12 P = 0.03 | Z=-2.33 P = 0.01 | |
History of infection with coronavirus | Infected | 33.11 ± 7.18 | 29.74 ± 8.79 | 28.64 ± 11.59 |
Not Infected | 34.50 ± 5.48 | 31.67 ± 8.81 | 31.11 ± 11.62 | |
Mann-Whitney Test | Z=-1.23 P = 0.21 | Z=-1.58 P = 0.11 | Z=-1.91 P = 0.05 | |
The results of Kruskal-Wallis that followed by Dunn-Bonferroni post-hoc test, revealed that the mean scores of burnout and secondary traumatic stress in the 35–39 year age group were higher the other groups. In addition, Single nurses had significantly higher mean scores of secondary traumatic stress compared to their married peers (p < 0.05). According to this table, the results of the Mann-Whitney U test revealed that the mean score of compassion fatigue in nurses with fixed shifts was lower than that in nurses with rotating shifts (p = 0.01). The mean score of secondary traumatic stress was lower in nurses who had a positive history of infection with coronavirus (P = 0.05).
Table 3 shows the mean scores of sleep quality and the correlation between Pro QOL and sleep quality in ICU nurses. The overall sleep quality of the ICU nurses was poor (9.97 ± 4.55). The majority of the ICU nurses reported poor sleep quality 220 (87%), indicated by a PSQI ≥ 5 global score.
Table 3
Mean scores of the aspects of sleep quality and correlation between of Pro QOL and sleep quality in ICU nurses (n = 253)
Spearman’s correlation coefficient (p value) | ||||
|---|---|---|---|---|
Aspects of sleep quality | Mean ± SD | Compassion Satisfaction | Burnout | Secondary Traumatic Stress |
Subjective sleep quality | 1.75 ± 0.94 | -0.123 | 0.576** | 0.573** |
Sleep latency | 1.74 ± 0.90 | -0.082 | 0.256** | 0.219 ** |
Sleep duration | 1.14 ± 0.94 | -0.127* | 0.308** | 0.289** |
Habitual sleep efficiency | 0.93 ± 1.04 | -0.137* | 0.096 | 0.077 |
Sleep disturbance | 1.75 ± 0.84 | -0.206** | 0.723** | 0.710** |
Use of sleep medication | 0.92 ± 1.11 | -0.219** | 0.651** | 0.646** |
Daytime dysfunction | 1.75 ± 1.11 | -0.152* | 0.615** | 0.631 ** |
Overall sleep quality | 9.97 ± 4.55 | -0.230** | 0.700** | 0.683** |
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The correlation analysis revealed a negative correlation between overall sleep quality and compassion satisfaction (r=-0.23, p < 0.001). In contrast, burnout was positively correlated with overall sleep quality (r = 0.70, p < 0.001), and secondary traumatic stress (r = 0.68, p < 0.001). The results revealed that unfavorable Pro QOL were associated with poor sleep quality.
We found a very weak negative correlation between compassion satisfaction and sleep disturbance (r=-0.20, p < 0.001), as well as a high positive correlation between burnout and sleep disturbance (r = 0.72, p < 0.001) and between secondary traumatic stress and sleep disturbance (r = 0.71, p < 0.001). (Table 3).
Our results showed that the mean scores of sleep quality and its dimensions did not significantly differ according to sex, education level, or history of suffering from COVID-19 (p > 0.05). The results revealed that the mean scores of subjective sleep quality (p < 0.001), sleep disturbance (p = 0.038), daytime dysfunction (p < 0.001), and overall sleep quality (p = 0.013) were higher in nurses with rotating shifts than in those with fixed shifts.
Moreover, regression analysis revealed a significant relationship between compassion satisfaction, burnout, and secondary traumatic stress with sleep quality among ICU nurses, which can predict 0.45% of the variance in sleep quality (F = 7.11, p < 0.001, R2 = 0.46, adjusted R2 = 0.45). (Table 4).
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Table 4
Regression analysis of relationships between dimensions of Pro QOL and sleep quality in ICU nurses (n = 253)
Unstandardized Coefficients | Standardized Coefficients | |||||
|---|---|---|---|---|---|---|
Variables | Mean ± SD | B | Std. Error | β | t | p-value |
Compassion satisfaction | 33.49 ± 6.77 | − 0.067 | 0.032 | − 0.100 | -2.082 | 0.038 |
Burnout | 32.28 ± 8.83 | 0.114 | 0.048 | 0.221 | 2.347 | 0.02 |
Secondary traumatic stress | 29.58 ± 11.67 | 0.177 | 0.036 | 0.454 | 4.916 | 0.001 |
Discussion
This study assessed the relationships between ICU nurses’ Pro QOL in three dimensions and sleep quality during the COVID-19 outbreak. The results of this study indicated that nurses in COVID-19 ICUs experienced moderate levels of three dimensions of Pro QOL: compassion satisfaction, secondary traumatic stress and burnout, and they also reported poor sleep quality. Staff shortages, heavy workloads, increased patient turnover, inadequate medical supplies, and other challenges may be the reasons for the decrease in ICU nurses’ Pro QOL. Our findings are in line with those of the study of Cuartero-Castañer et al. (2021), which reported that ICU nurses experienced moderate levels of compassion satisfaction and burnout during the COVID-19 pandemic [29]. Hwang (2022) showed that nurses, in the context of the COVID-19 pandemic, had high levels of job stress and moderate QWL. Nurses’ QWL is negatively correlated with job stress and turnover intention [19]. Dixit et al. (2024) showed that the majority of nurses experience a moderate level of compassion satisfaction, burnout, and secondary traumatic stress after the second wave of the COVID-19 pandemic [16]. A previous study conducted in Northern Uganda (2021), reported that 49.11% of nurses experienced a high level of compassion satisfaction [30]. Another study in Malaysia (2021) reported a high level of burnout among 39.4% of nurses which was inconsistent with our results [14].
Our results revealed that the mean scores of compassion fatigue (burnout and secondary traumatic stress) in the 35–39 year age group were higher than those in the other groups. Niu et al. (2022) reported that the incidence of secondary traumatic stress in individuals under 30 years of age was greater than that in individuals aged 30–40 years [31]. The inconsistency in the age distribution of individuals experiencing secondary traumatic stress may be attributed to differences in work environments, or cultural factors. Jiang et al. (2021) reported that burnout in individuals over 46 years of age was greater than that in those under 46 years of age, which was inconsistent with our results [15]. This discrepancy could be due to a combination of career stage, family commitments, organizational influences, and individual variations.
In the present study, the mean score of secondary traumatic stress was higher in single nurses than in the other groups, and no significant difference was found between other dimensions of nurses’ Pro QOL and marital status. Saliya et al. (2024) found that marital status was a predictor variable for both compassion satisfaction and compassion fatigue [22]. According to the results of Jiang et al. (2021), there was no significant difference between marital status and nurses’ Pro QOL dimensions [15].This could be because of context differences between healthcare settings.
The present study indicated no significant difference between the Pro QOL dimensions and gender and educational level. A recent study showed a significant relationship between nurses’ educational level and secondary traumatic stress [28] which is not consistent with our results. Discrepancies in findings might be due to differences in study populations, and nurses’ work environments.
Our study revealed that the mean score of compassion fatigue in nurses with fixed shifts was lower than that in nurses with rotating shifts, which ultimately affected nurses’ Pro QOL. These results are in line with those of a previous study [32]. Nurses with fixed shifts may experience lower compassion fatigue due to consistent sleep, reduced stress, better work‒life balance, and a reduced risk of burnout. However, individual factors can also influence fatigue levels.
In our study, the majority of nurses (87%) experienced poor sleep quality during the COVID-19 pandemic. Similarly, the frequency of poor sleep quality in healthcare workers has increased, particularly among frontline nurses during the COVID-19 crisis [18, 20, 33, 34]. Poor sleep quality among ICU nurses was associated with heavy workloads, high psychological job demands, irregular shift work, and a high-stress practice environment. Gómez-Garlia et al. (2016) reported that nurses working night shifts experienced poorer overall sleep quality, daytime dysfunction, and sleep disturbance than those working day shifts. This may be due to disrupted circadian rhythms during night shifts, resulting in weaker and less regular activity patterns. Furthermore, nurses working in rotating shifts exhibited a decreased ability to provide patient care [35].
We found a positive correlation between compassion fatigue and sleep disturbance, and a negative correlation between compassion satisfaction and overall sleep quality, which was in line with the results of a previous study [36]. Healthcare workers’ health status can have a significant effect on providing continuous and comprehensive patient care and dealing with public health emergencies [21].
Nursing administrators should consider the results of this study to improve the nursing practice environment and nurses’ Pro QOL to reduce revealed work-related stressors during similar future emergencies. Experimental studies establishing the efficacy of practical interventions targeting nurses’ well-being are encouraged in the future. Furthermore, to develop theoretical models, determining the mediating effects of variables on the relationship between Pro QOL and sleep quality could be the subject of future research.
Limitations
This study has several limitations. First, the cross-sectional design (descriptive correlation) limited our ability to infer causal relationships between the variables. This type of study only assessed the Pro QOL and sleep quality of ICU nurses at the time of the study. It did not allow for an examination and comparison of these variables over time in the study population, such as before, during, and after the COVID-19 outbreak. Furthermore, the use of a self-report questionnaire might lead to reporting recall bias. Another limitation is that the research was limited to nurses working in COVID-19 ICUs. Nurses working in other departments, such as emergency, general, and outpatient departments (OPDs), which also provide COVID-19 patients with care, were not included in the study. This may limit the generalizability of the results to nurses in other wards or other the geographic regions.
Conclusion
The results of this study indicated that nurses in COVID-19 ICUs experienced moderate levels of compassion satisfaction, secondary traumatic stress, and job burnout. They also reported poor sleep quality. The results confirmed the link between the Pro QOL of ICU nurses during the COVID-19 pandemic and sleep quality. Burnout and secondary traumatic stress can negatively influence sleep quality by causing anxiety, stress, depression, and physical exhaustion. High workload, long working hours, and a stressful work environment in ICU can negatively affect nurses’ Pro QOL, leading to disrupted sleep-wake cycles and sleep disorders, which ultimately reduce their sleep quality. Our result revealed burnout and secondary traumatic stress had highly positive relationship with sleep disturbance dimension more than other dimensions. It is suggested that nursing managers and healthcare policymakers design and implement practical strategies, including the adequacy of resources and the recruitment of expert nurses, to improve the Pro QOL of nurses in the ICUS. This will subsequently lead to improved outcomes for nurses and ensure patient safety.
Acknowledgements
This manuscript is a part of Razie Soltani thesis for the Master of Science’s degree in Nursing. The researchers thank the Vice-Chancellor for Research and Technology at Shiraz University of Medical Sciences, Iran for their financial support. We also extend our thanks to the participating ICU nurses in this study.
Declarations
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Ethical approval and consent to participate
The study was approved by the Research Ethics Committee of Shiraz University of Medical Sciences (approval no.: IR.SUMS.REC. 1398.1172) and followed the Helsinki Declaration. All research participants gave their written informed consent and were fully informed about the aim of the study, as well as the anonymity and confidentiality of personal information. Moreover, they were assured of voluntary participation and that they would freely leave at any stage of the research.
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