DOI: https://doi.org/10.21203/rs.3.rs-2233005/v1
This study explored how coping styles mediate the relationship between sleep status and quality of life among night shift nurses.
A multistage stratified cluster sampling survey was conducted among staff at a general hospital from November 2019 to January 2020. A total of 1,170 night shift nurses completed the Pittsburgh Sleep Quality Index (PSQI), EuroQol five-dimensions (EQ-5D), and Simplified Coping Style Questionnaire (SCSQ). Respectively, these measures were used to assess sleep quality, the quality of life, and coping styles.
The total sleep status was positively correlated with the quality of life (r = 0.31, P < 0.05) and negative coping (r = 0.18, P < 0.05), negatively correlated with positive coping (r = -0.05, P < 0.05). Negative coping was positively correlated with the quality of life (r = 0.42, P < 0.05). According to the path analysis, sleep status had a positive effect on negative coping (β = 0.18, P < 0.05) and quality of life (β = 0.11, P < 0.05), negative effect on positive coping (β = -0.05, P < 0.05); positive coping had a negative effect on quality of life (β = -0.03, P < 0.05), while negative coping had a positive effect on quality of life (β = 0.02, P < 0.05).
Coping style partially mediated the relationship between sleep status and quality of life. This suggests that interventions targeting coping styles may benefit night shift nurses, as such an approach can ultimately enhance the quality of life by improving sleep.
The National Sleep Foundation defines shift work as that which is performed outside the traditional daily schedule of 9:00 to 17:00 [1]. Such an arrangement may influence sleep, which is an important physiological process that supports normal bodily functioning. In fact, sleep is closely related to physical and psychological well-being, with critical impacts on human health, the quality of life, and productivity. However, the special nature of nursing requires engagement in shift work. This is an important area of concern due to the increasing number of individuals entering the profession. According to the National Plan for the Development of Nursing and Health Care (2016–2020), the total number of registered nurses in China will reach 4.45 million by 2020, with 3.14 for every 1,000 persons and a national ratio of 1:1.25 [2]. Meanwhile, health needs continue to rise across the population. These factors make it vital to address issues that impact the nursing workforce, especially among nurses who work the night shift.
Due to the high-intensity and stressful nature of night shift work, nurses who work during that time are particularly prone to poor health outcomes. Chronic ill-health not only affects personal health for night shift caregivers, but also leads to a reduction in their ability to provide services [3]. This leads to coping. The main function of coping is to regulate the stress response, which includes changing the assessment of stressful events and regulating any associated somatic and emotional responses [4]. At the same time, many factors are known to influence the quality of life. In this context, previous studies have focused on the direct effects of either sleep status or coping style [5, 6], but the joint interaction between these two factors and the quality of life has not been explained. This study addressed this gap in the literature by assessing how both issues affected night shift nurses. First, we hypothesized that sleep status would not only directly affect the quality of life, but would indirectly affect the quality of life through the mediator of coping style. We believe that our findings will provide the basis for developing a health management system aimed at improving conditions for night shift caregivers, thus enhancing their quality of life and health.
The study sample consisted of 1,170 night shift nurses who were employed at general hospitals in Shandong Province. We applied a multistage stratified whole-group sampling method from November 2020 to January 2021. First, all prefecture-level cities in Shandong Province were ranked according to their 2018 GDP per capita levels and divided into three categories, including good, medium, and poor. Then, one prefecture-level city was selected from each category via simple random sampling (Qingdao City, Zaozhuang City, and Dezhou City). Second, a district city with only one municipal general hospital was surveyed for that general hospital. If more than one existed, then one general hospital was selected via simple random sampling. Again, in each prefecture-level city, three counties (districts/county-level cities) were randomly selected; in each county (district/county-level city), one (district/county-level city) general hospital was randomly selected via the same sampling method used for city-owned hospitals. As such, this study surveyed a total of 12 general hospitals, including three city-affiliated and nine county-affiliated. Among these, three wards were randomly selected for each discipline according to the discipline classification (all wards were surveyed in cases where fewer than three existed). Thus, surveyed night nursing staff were asked to complete the questionnaire.
The study was reviewed and approved by the Ethics Committee of the School of Public Health, Shandong University (approval number: 20181219). The fieldwork was only initiated after approval was obtained. All participants signed informed consent forms at the time of survey. Overall, this study collected a total of 1,170 valid samples from night shift nurses employed at general hospitals in Shandong Province.
As described in the following subsections, the participants provided their demographic characteristics and completed three scales to measure sleep status, the quality of life, and coping style.
The questionnaire asked for demographic data, including department, gender, age, education, title, administrative position, marital status, maternity status, years of work, night duty status, frequency of night duty, and the form of employment.
We measured sleep via the Pittsburgh Sleep Quality Index (PSQI), which consists of 18 items across seven dimensions, including subjective sleep quality (entry 6), sleep onset (entries 2 and 5a), sleep duration (entry 4), sleep efficiency [entry 4/(entry 3-entry 1)], sleep disturbance (entries 5b to 5j), hypnotic medication (entry 7), and daytime functioning (entries 8 and 9). Each is scored on a scale ranging from 0 to 3, with higher total scores indicating poorer sleep quality [7]. In this study, the PSQI received a Cronbach’s alpha coefficient of 0.9.
We measured the quality of life using the EuroQol five-dimensions (EQ-5D) scale [8]. Specifically, the five dimensions include Mobility, Self-Care, Usual Activities, Pain/Discomfort, and Anxiety/Depression. Each dimension consists of three levels, including no difficulty, some difficulty, and extreme difficulty.
We assessed coping styles via the Simplified Coping Style Questionnaire (SCSQ) [9], which consists of 20 items across two dimensions, including positive coping and negative coping. Each item is scored on the following multilevel scale: 0 (no adoption), 1 (occasional adoption), 2 (sometimes adoption), and 3 (frequent adoption). The main evaluation is the coping style adopted by the participant when they encounter problems. The positive coping dimension consists of items 1–12, and focuses on the characteristics of positive coping, while the negative coping dimension consists of items 13–20, and focuses on the characteristics of negative coping. The scale has received a Cronbach’s alpha coefficient of 0.87, which indicates good reliability [9].
In establishing statistical descriptions, we used means ± standard deviations for continuous data, and used frequencies and percentages for count data. We assessed correlations using the Pearson correlation analysis, and verified the mediating role of coping style in the relationship between sleep status and the quality of life using the Bootstrap procedure. In this study, all statistical tests were two-sided, with P < 0.05 considered statistically different. We conducted our analyses using IBM SPSS 25.0 (web version) and AMOS 24.0.
Table 1 lists basic demographics and professional characteristics across the study sample.
|
Variables |
Classification |
Sample |
Composition ratio |
|---|---|---|---|
|
Marital status |
Unmarried |
233 |
19.90 |
|
Married |
925 |
79.10 |
|
|
Other |
12 |
1.00 |
|
|
Age (years) |
20–29 |
475 |
40.60 |
|
30–39 |
556 |
47.50 |
|
|
40–49 |
120 |
10.30 |
|
|
≥ 50 |
19 |
1.60 |
|
|
Education level |
Master and above |
20 |
1.70 |
|
Undergraduate |
929 |
79.40 |
|
|
Below undergraduate |
221 |
18.90 |
|
|
Professional title |
Associate senior and above |
28 |
2.40 |
|
Intermediate |
290 |
24.80 |
|
|
Primary and other |
852 |
72.80 |
|
|
Post position |
Yes |
346 |
29.60 |
|
No |
824 |
70.40 |
|
|
Department |
Internal medicine |
141 |
12.10 |
|
Surgery |
561 |
47.90 |
|
|
Gynecology |
337 |
28.80 |
|
|
Obstetrics and gynecology |
103 |
8.80 |
|
|
Pediatrics |
22 |
1.90 |
|
|
Other |
6 |
5.00 |
|
|
Total |
1170 |
Table 2 shows scores for coping style, sleep status, and quality of life across the study sample.
|
Score |
Average score |
|
|---|---|---|
|
Positive coping |
0 to 3 |
1.83 ± 0.60 |
|
Negative coping |
0 to 3 |
1.14 ± 0.57 |
|
Sleep quality |
0 to 22 |
7.56 ± 4.29 |
|
Quality of life index |
-1 to 1 |
0.59 ± 0.10 |
Table 3 shows the correlations between coping style, sleep status, and quality of life across the study sample.
|
Sleep status |
Negative coping |
Positive coping |
Quality of life |
Anxiety or depression |
Pain or discomfort |
Daily activities |
Self-care |
Mobility |
|
|---|---|---|---|---|---|---|---|---|---|
|
Sleep status |
1.00 |
||||||||
|
Negative coping |
0.18* |
1.00 |
|||||||
|
Positive coping |
-0.05* |
-0.01 |
1.00 |
||||||
|
Quality of life |
0.31* |
0.42* |
-0.32* |
1.00 |
|||||
|
Anxiety or depression |
0.06* |
0.02 |
-0.11 |
0.55* |
1.00 |
||||
|
Pain or discomfort |
0.06* |
0.02* |
-0.11 |
0.54* |
0.29 |
1.00 |
|||
|
Daily activities |
0.07* |
0.03* |
-0.11* |
0.66* |
0.36* |
0.35* |
1.00 |
||
|
Self-care |
0.06* |
0.02* |
-0.11* |
0.53* |
0.29* |
0.28* |
0.35* |
1.00 |
|
|
Mobility |
0.05* |
0.02 |
-0.11 |
0.47* |
0.26 |
0.25 |
0.31* |
0.25* |
1.00 |
| * P < 0.05 | |||||||||
We used the structural equation model and Bootstrap method to test how coping style mediated the relationship between sleep status and the quality of life. This study required a multiple mediated structural equation model with one independent variable (consisting of seven observed variables, including subjective sleep quality, time to fall asleep, sleep duration, sleep efficiency, sleep disturbance, sleep medication and daytime dysfunction), two mediating variables (consisting of two observed variables, including positive coping and negative coping), and one dependent variable (consisting of five observed variables, including mobility, self-care, daily activities, pain or discomfort, and anxiety or depression). The fit indices showed the following: chi-squared value/free degree (minimum discrepancy divided by the degree of freedom; CMIN/DF) = 8.30; goodness of fit index (GFI) = 0.93; adjusted goodness of fit index (AGFI) = 0.90; gauge fit index (normative fit index; NFI) = 0.82; value-added fit index (incremental fit index; IFI) = 0.84; comparative fit index (CFI) = 0.84; asymptotic residuals mean square and root square (root mean square error of approximation; RMSEA) = 0.07 (< 0.08). These values indicate that the model is acceptable [10], thus providing a basis for further testing. After applying the Bootstrap method to test the model, the 95% confidence intervals (CIs) for the direct, indirect, and total effects of coping style in the relationship between sleep status and the quality of life did not contain 0, with a mean Z > 1.96. This indicated that direct and indirect effects were present. In sum, coping style partially mediated the relationship between sleep status and the quality of life.
This study found pairwise correlations between the scores of each dimension and the total score. For nursing staff in the study sample, sleep status was positively correlated with the quality of life; that is, higher sleep quality was associated with higher quality of life. This is important, as sleep quality directly impacts the quality of night care in the ward. Moreover, sleep is closely linked to mood, such that issues may contribute to mood disorders and impact emotional states, which can further affect sleep quality and the ability to fall asleep [11]. In this context, effective mood regulation strategies can help maintain good health [12]. Individuals with poor sleep quality are more likely to have negative moods and use negative coping strategies during stressful events, thus leading to unresolved problems; by contrast, individuals with good sleep quality are more likely to have positive moods and use positive coping strategies during stressful events, thus leading to happiness through problem solving [13]. For night shift nurses, better sleep quality may promote the initiative to understand and solve problems, which can then be handled in positive ways that are conducive to health. In turn, this can help maintain an optimistic outlook and improve the quality of life. However, poor sleepers are more likely to avoid or resign themselves to current health states and adopt negative coping styles to deal with problems, thus significantly reducing the quality of life.
This study further investigated mediators in the relationship between sleep status and the quality of life by constructing a structural equation model to explore the underlying mechanisms. As shown in Fig. 1, sleep status had a negative effect on positive coping styles, a positive effect on the quality of life, and a positive effect on negative coping styles. Moreover, negative coping styles had a positive effect on the quality of life, while positive coping styles had a negative effect on the quality of life. In sum, coping styles mediate the relationship between sleep status and the quality of life, and can therefore work as influencing factors on the quality of life. Here, positive coping styles are protective factors, while negative coping styles are risk factors; at the same time, sleep quality negatively affects positive coping styles and positively affects negative coping styles. This is consistent with Ruan Chengmei’s research [14]. Despite these implications, there is still no comprehensive policy or system to protect sleep health among nursing staff in China [15]. This is particularly needed to improve sleep status for night shift nurses, who are exposed to substantial stress and lack group support. These factors contribute to increased tension, even when compared to day shift nurses. Thus, night shift nurses many perpetually find themselves in a state of physical and mental stress during work tasks. Ultimately, failure to cope appropriately can lead to stress disorders, which are detrimental to physical and mental health. Positive coping facilitates problem solving and alleviates adverse emotions, while negative coping only temporarily relieves internal tension and is not conducive to problem solving [16]. These findings also support our research hypothesis, suggesting that night shift nurses who obtain better sleep will be more likely to adopt positive coping strategies to solve problems, thus creating a virtuous cycle that promotes a good quality of life and health.
For night shift nurses, the current results indicate that sleep status can not only directly affect the quality of life, but can indirectly affect the quality of life through coping styles. In this arrangement, coping styles partially mediate the relationship between sleep status and quality of life, such that improving sleep quality and/or changing coping styles may theoretically improve the quality of life for night shift caregivers.
This study also had some limitations. Although we adopted a multistage stratified whole group sampling method, the selection of primary hospitals was relatively large and the representativeness was biased. Therefore, the conclusions should be explored and tested continuously.
Adjusted goodness of fit index (AGFI)
minimum discrepancy divided by the degree of freedom (CMIN/DF)
comparative fit index (CFI)
confidence intervals (CIs)
EuroQol five-dimensions (EQ-5D)
goodness of fit index (GFI)
incremental fit index (IFI)
normed fit index (NFI)
Pittsburgh Sleep Quality Index (PSQI)
root mean square error of approximation (RMSEA)
Simplified Coping Style Questionnaire (SCSQ)
Ethics approval and consent to participate
All procedures performed in studies involving human participants were in accordance with the ethical standards of the Ethics Committee of the School of Public Health, Shandong University (approval number: 20181219).
Consent for publication
Not applicable.
Availability of data and materials
Data from this study will be shared with qualified investigators upon reasonable request for scientific purposes.
Competing interests
The authors declare that they have no competing interests in this section.
Funding
Education and Teaching Reform Research Project of Shandong University, No.2020Y236
Authors’ contributions
Yan Zhao: study design, analyzed the research material, statistical analysis, wrote the paper, performed the manuscript review
Bei Yang: analyzed the research material, statistical analysis, wrote the paper, performed the manuscript review
Cui Liu: wrote the paper, performed the manuscript review.
Benmiao Lin: data collection, analyzed the research material,
Xiaoyi Wu: data collection, prepared the manuscript.
Yuanyuan Sun: statistical analysis, interpreted the data, wrote the paper, and performed the manuscript review.
Jianying Chu: study design, analyzed the research material, wrote the paper, performed the manuscript review
Yan Zhao and Bei Yang contributed equally to this article, all authors read and approved the final manuscript.
Acknowledgements
We would like to express our deepest gratitude to the directors of the hospital that hosted the study and to all the nursing staff who agreed to participate.