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. 2022 Dec 20;10(4):2611–2620. doi: 10.1002/nop2.1521

Shift work disorder, mental health and burnout among nurses: A cross‐sectional study

Hui Cheng 1, Guangbi Liu 2, Junyi Yang 2, Qiaohong Wang 1, Hui Yang 1,✉
PMCID: PMC10006599  PMID: 36539975

Abstract

Aim

The aim of the study was to examine the relationships among nurses' shift work disorder, mental health and burnout to inform efforts to alleviate shift work disorder.

Design

This cross‐sectional study was conducted in China using a web‐based platform for questionnaire.

Methods

The study was comprised of a convenience sample of 1,268 Registered Nurses from 21 public hospitals in mainland China from June 2019–July 2019. Participants completed a web‐based survey designed to collect demographic and other self‐reported data. An independent sample t test and Pearson correlation were performed to analyse the relationship between shift work disorder, mental health and burnout.

Results

The vast majority (98.2%) of the participants were women between the ages of 20–59 years. The participants exhibited a higher incidence of mental health problems (58.1%) and burnout (65.5%) and those with shift work disorder exhibited a higher risk of mental health problems and burnout than those who did not have shift work disorder. Our research demonstrated that shift work disorder, combined with other variables, accounted for 40.5% of the variance in mental health (R 2 = .405, adjusted R 2 = .401, F = 107.214, p < .001) and 36.5% in burnout (R 2 = .365, adjusted R 2 = .361, F = 90.323, p < .001). Moreover, burnout negatively regulated the relationship between shift work disorder and mental health.

Conclusion

High‐risk nurses with shift work disorder were at a much higher risk of mental health problems and burnout.

Keywords: burnout, mental health, shift nurses, shift work disorder

1. INTRODUCTION

An estimated 15%–30% of the workforce in Europe and the United States is engaged in shift work. The utilization of shift work is increasingly important to sustain economic and social needs and is particularly common in hospitals (Cheng & Drake, 2019). Nurses are key in‐patient care. Shift nurses have proven particularly important because they provide 24‐hour care. Shift work disorder (SWD) among nurses is an important issue, as it is associated with adverse patient events (Patrician et al., 2011). According to the International Classification of Sleep Disorders, Second Edition (ICSD‐2) Criteria, the prevalence of the incidence of SWD ranges from 7.1%–33.5% among hospital personnel (Vanttola et al., 2020).

The American Academy of Sleep Medicine defines SWD as a circadian rhythm sleep disorder and a primary sleep disorder. Eight‐hour and 12‐hr shifts are two most common types of shift work. Sleep problems among shift nurses are increasingly recognized as an important issue at both an individual and organizational level. SWD may induce a variety of undesirable health outcomes, such as type 2 diabetes (Anothaisintawee et al., 2016), coronary artery disease (Vetter et al., 2016), abdominal obesity (Sun et al., 2018), breast cancer (Straif et al., 2007), nurses who work shifts and long hours are at risk of fatigue, job performance, quality of care and patient safety (Min et al., 2022; Sun et al., 2019).

Studies have shown that sleep disorders and mental health problems such as depression and anxiety are common consequences of shift work (Booker et al., 2019; Lee et al., 2016). Consistent night shifts also are associated with increased risks of burnout and mental disorders (Cheng & Cheng, 2017). However, there has been little research on the impacts of mental health problems and burnout on shift work disorders among nurses.

1.1. Background

A systematic review of 52 studies with a total of 31,749 participants showed that the prevalence of sleep disorders among medical staff in China was 39.2% (Qiu et al., 2020). A large multi‐country study of thousands of nurses in Europe and the United States has shown that 12‐hour shifts negatively affect patient care and nurse health and performance outcomes (Dall Ora et al., 2022). Nurses often report sleep problems due to non‐traditional shifts and long hours. Poor sleep quality is associated with poor cognitive function, poor patient care and may even endanger patient safety (Veal et al., 2021).

Previous studies also have shown that women that performed shift work reported much higher levels of mental distress than women who worked day shifts (Jaradat et al., 2018). A survey of Chinese nurses showed that poor sleep quality caused by night shifts was associated with a higher incidence of depression (40.8%) (Dai et al., 2019). Previous studies primarily explored the relationship between SWD and depressive symptoms and anxiety (Anbazhagan et al., 2016). However, mental health problems associated with SWD have not been fully addressed.

So far, studies indicated that nurses with poor health were 26%–71% more likely to have a medical malpractice suit brought against them than those with better health (Melnyk et al., 2018; Suzuki et al., 2004). Therefore, it is imperative to explore the causes of the increase in mental illness among shift workers in order to propose practical interventions.

Burnout is included as an occupational hazard in the 11th revised International Classification of Diseases (ICD‐11). ICD‐11 defined burnout as a syndrome that results from chronic workplace stress and has not been managed successfully (WHO, 2019). A meta‐analysis of burnout revealed that in a sample of 868 nurses, 25% suffered from emotional exhaustion, 15% experienced depersonalization, and 22% had a sense of low personal accomplishment (López‐López et al., 2019). A study of Indonesian nurses showed that the incidence of burnout was as high as 56% (Yestiana et al., 2019). A similar study showed that approximately 64.0% of Chinese nurses experienced job burnout that negatively impacted the quality of their work and lives (Wang et al., 2019). Burnout among Registered Nurses has been proven to be positively correlated with patient adverse events (Lewis et al., 2015). Greater amounts of shift work resulted in higher levels of burnout and patient dissatisfaction (Stimpfel et al., 2012). However, there has been little research on the relationship between shift work disorder and burnout, and the causes of burnout have not been adequately identified.

Although shift work disorders, mental health and job burnout have been studied intensively in recent years, little is known about their impacts on shift nurses. This study aims to assess the relationship between shift work disorder, mental health and burnout among shift nurses. Additionally, the study was designed to explore the factors that influence mental health and burnout, as well as how they are shaped by SWD.

2. METHODS

2.1. Design

From June 2019 to July 2019, a cross‐sectional self‐administered survey was conducted in China using a web‐based platform for questionnaires. The sample of shift nurses from 21 public hospitals in 18 provinces in large‐ and medium‐sized cities in China. Considering the number of places in each hospital, the nurses were selected via convenience sampling. The hospitals are all tertiary hospitals with more than 500 beds, located in all four regions (north, south, east and west) of mainland China. The sample was intentionally broad in geographical scope as a means to explain regional differences in GDP per capita and levels of healthcare development.

2.2. Participants

A total of 1,632 participants were included in this study; a total of 1,268 nurses (77.7%) completed questionnaires. Eligibility criteria included the following: (1) possession of a Chinese nursing certificate; (2) 18 years of age or older; (3) full‐time employment as a nurse; and (4) shift work experience of at least 3 months. Exclusion criteria were that the nurses who were currently on leave.

2.3. Data collection

Shift nurses were invited to anonymously and voluntarily complete web‐based questionnaires. Sampling procedure: A two‐step sample selection method was used. The author of this article contacted the nursing managers in each hospital and then the nurses' managers sent the nurses eligible to participate a questionnaire. The first question was whether the participant had performed shift work for more than 3 months. Participants who responded affirmatively to the question were selected as candidates, and the participants' oral informed consent was obtained by face‐to‐face communication. The time needed to complete the survey was approximately 25–30 min.

2.4. Ethical considerations

This study was approved by the ethics committee of Shanxi Medical University (Approval No. 2019011). Participation in the study was voluntary and respondents completed the questionnaire online. To protect confidentiality, participants' identities were not collected, and the responses were anonymous.

2.5. Data analysis

Statistical analysis was performed using IBM SPSS Statistics (v25.0, IBM Corp., USA, 2017) (Elbedewy et al., 2020). An independent sample t test and Pearson correlation were applied, according to the type of variable. A linear regression analysis was performed on the variables with significant univariate relationships for the outcome variables. The remaining variables served to explain the distribution. The significant factors were placed in a linear regression model. Finally, a mediation effect analysis was conducted using PROCESS macro of Hayes (Hayes, 2018).

2.6. Measurements

2.6.1. Shift work disorder (SWD)

Three questions that have appeared in previous studies were used to evaluate SWD (AASM, 2005; Eldevik et al., 2013; Flo et al., 2012). (1) Do you experience difficulties sleeping or excessive sleepiness? (2) Are the sleep or sleepiness problems that you experience related to a work schedule that interferes with your normal sleep schedule? And (3) Have you experienced sleep or sleepiness problems related to your work schedule for at least 1 month? Subjects who responded “yes” to all three questions were classified as suffering from SWD.

2.6.2. Mental health

Mental health was measured using the General Health Questionnaire (GHQ‐12) developed by Goldberg and Williams (1988). We used a validated Chinese version of the General Health Questionnaire GHQ (Yang et al., 2003). Each item was scored on a 4‐point Likert scale (0–3 points). There was a possible total score of 36 points. Scores greater than or equal to 27 points indicated the existence of a psychological problem. The reliability coefficient was .813.

2.6.3. Burnout

We used the Chinese Maslach Burnout Inventory's emotional exhaustion subscale to measure burnout (MBI; Christina Maslach & Jackson, 1981). The Chinese Maslach Burnout Scale is comprised of 15 items separated into three sub‐scales: (1) emotional exhaustion; (2) personalization; and (3) personal achievements (Li & Shi, 2003). The Chinese version included only five of the items from the emotional exhaustion scale, each of which was scored using a 7‐point Likert scale (0 = never–6 = always, every day). A higher score indicated more severe emotional exhaustion. The scale had a possible score of 30. Scores of more than 10 indicated burnout (Long‐Fei et al., 2013). Cronbach's alpha was .958.

2.6.4. Work environment

The Chinese version of the Nursing Work Index Practice Environment Scale (PES‐NWI) was used to assess the work environment (Lake, 2002; Chiang & Lin, 2008). The PES‐NWI scale included 31 items separated into five subscales and scored on a 4‐point Likert scale (1–4). Total possible scores were between 31–124. Higher scores indicated better working conditions. Cronbach's alpha was .962.

2.6.5. Work engagement

Work engagement was measured using the Utrecht Work Engagement Scale (UWES); (Fong & Ng, 2012; Schaufeli et al., 2006). The UWES included three dimensions: vigour, dedication and absorption. We used a validated Chinese version, and each item was scored on a 7‐point Likert scale (0–6). Higher scores indicated better conditions for participation. Cronbach's alpha was .894.

2.6.6. Job crafting

We used the Chinese version of the Job Crafting Scale (Liao, 2013), originally developed by Tims et al. (2012). There were 21 items separated into four subscales. Each item was scored using a 5‐point Likert scale (from 0–5). Higher scores indicated higher levels of job crafting. Cronbach's alpha was .920.

3. RESULTS

3.1. General characteristics of the participants

The online questionnaire was completed by 1,268 participants. Of the participants, 58.1% exhibited shift work disorder (SWD); these participants exhibited a higher incidence of mental health problems (58.1%) and burnout (65.5%). Participants were between 20–59 years of age. A total of 498 of these participants (39.2%) had been involved in shift work for 5–10 years. Approximately one‐third of the shift nurses were over‐ or under‐weight. However, two independent sample t tests determined that the weight of the participant did not represent a contributing factor to SWD. Descriptive statistics are shown in Table 1.

TABLE 1.

Demographics of the Chinese shift nurses' sample (n = 1,268)

Demographics Classification Frequency Percent Cumulative percent
Gender Female 1,245 98.20% 98.20%
Male 23 1.80% 100%
Age <25 y old 151 11.90% 11.9%
25–34 y 884 69.80% 81.7%
35–44 y old 216 17.0% 98.7%
>45 y old 16 1.3% 100%
Diet Yes 413 32.6% 32.6%
No 855 67.4% 100%
Exercise Never 581 45.8% 45.8%
Occasionally (3 times per week) 610 48.1% 93.9%
Frequently (6 times per week) 58 4.6% 98.5%
Every day 19 1.5% 100%
Smoking habit Never smoked 1,224 96.5% 96.5%
Smoked occasionally 32 2.5% 99.1%
Regularly smoked 12 0.9% 100.0%
Use of hypnotic medication Yes 193 15.2% 15.2%
No 1,075 84.8% 100.0%
Had a sick leave in the past 6 months Yes 171 13.5% 13.5%
No 1,097 86.5% 100.0%
BMI <18.5 kg/m2 (Underweight) 161 12.8% 12.8%
18.5–23.9 kg/m2 (Normal) 856 67.80% 80.6%
24.0–27.9 kg/m2 (Overweight) 197 15.60% 96.2%
>28.0 kg/m2 (Obesity) 48 3.8% 100%
Ward Internal medicine 446 35.2% 35.2%
Surgery and oncology 386 30.4% 65.6%
Emergency and ICU 187 14.7% 80.3%
Obstetrics and Gynaecology and Paediatrics 169 13.3% 93.6%
other 80 6.3% 100%
Shift work experience (years) ≤1 153 12.20% 12.2%
>1–≤2 115 9.10% 21.3%
>2–≤5 234 18.40% 39.7%
>5–≤10 498 39.10% 78.8%
>10 268 18.70% 100%
Shift schedule Shift (8 h) 704 55.5% 55.5%
Shift (12 h) 336 26.5% 82.0%
Shift (24 h) 39 3.1% 85.1%
Other 189 14.9% 100%
SWD Yes 737 58.1% 58.1%
No 531 41.9% 100%
Burnout Yes 830 65.5% 65.5%
No 438 34.5% 100%
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3.2. Correlation analyses

SWD was related to mental health problems and burnout. A number of other factors contributed to variations in the relationship between mental health and burnout: the use of hypnotic medications, exercise, shift work experience, the number of hours per shift, sick leave taken during the past 6 months, job crafting, work engagement and work environment. Participants with SWD scored higher on the mental health scale than those who did not suffer from the disorder (mean (SD) =18.03 (4.728) and mean (SD) = 14.33 (5.001), respectively; t (1266) = 13.425, p < .001). Participants with SWD also had higher burnout than those who did not have the disorder (mean (SD) = 17.82 (7.715) vs. mean (SD) = 11.84 (6.849); t (1266) = 14.266, p < .001) (Table 2).

TABLE 2.

Univariate analysis comparing mental health and burnout scores with possible predictors (n = 1,268)

Mental health Burnout
Mean (SD)/r Value p‐Value Mean ± SD/r value p‐Value
Shift work disorder
Yes 18.03 (4.728)a <.001 17.82 (7.715)a <.001
No 14.33 (5.001)a 11.84 (6.849)a
Gender
Female 16.48 (5.163)a .315 15.31 (7.928)a .699
Male 16.04 (5.920)a 15.96 (8.298)a
Age 0.033b .239 0.052b .062
BMI 0.058*b .038 −0.096**b .001
Exercise
No 17.65 (4.921)a <.001 16.87 (7.967)a <.001
Yes 15.48 (5.179)a 14.01 (7.668)a
Sick leave
Yes 18.47 (4.864)a <.001 19.00 (7.934)a <.001
No 16.16 (5.155)a 14.75 (7.780)a
Use of hypnotic medication
Yes 19.18 (4.997)a <.001 19.72 (7.799)a <.001
No 15.99 (5.509)a 14.53 (7.698)a
Internal medicine 16.54 (5.127)a <.001 15.24 (7.895)a <.001
Surgery and oncology 16.71 (5.219)a 15.63 (7.695)a
Emergency and ICU 15.40 (5.099)a 13.41 (7.553)a
Obstetrics and Gynaecology and Paediatrics 17.59 (5.069)a 17.36 (8.450)a
Other 14.64 (4.887)a 13.55 (7.657)a
Shift work experience
(years) ≤1 14.15 (5.333)a <.001 11.79 (7.487)a .007
>1–≤2 16.30 (5.763)a 14.85 (8.105)a
>2–≤5 16.73 (5.031)a 15.26 (7.620)a
>5–≤10 17.12 (5.004)a 16.38 (7.860)a
>10 16.46 (4.909)a 15.62 (7.971)a
Shift schedule
(8 h) 15.91 (5.063)a <.001 14.09 (7.513)a <.001
(12 h) 17.13 (5.363)a 17.32 (8.498)a
Other 17.24 (5.044)a 16.17 (7.650)a
Work engagement −0.500**b <.001 −0.418**b <.001
Job crafting scale −0.379**b <.001 −0.237**b <.001
Work environment −0.482**b <.001 −0.454**b <.001
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Note: a t test; bPearson's correlation.

Abbreviations: BMI, body mass index; SD, standard deviation; SWD, shift work disorder.

*p < .05 (two‐tailed); **p < .001 (two‐tailed).

3.3. Linear regression analysis

Separate backward linear regression models were conducted using mental health and burnout as the dependent variables. Only variables that demonstrated significant relationships from the univariate analysis were included. SWD alone explained 8.1% of the variance in mental health (R 2 = .081, F = 153.748, p < .001). SWD together with hypnotic medication use, exercise, years of shift work experience, the number of hours per shift or sick leave taken in the past 6 months, accounted for 40.5% of the variance in mental health scores (R 2 = .405, adjusted R 2 = .401, F = 107.214, p < .001).

SWD alone explained 8.4% of the variance in burnout (R 2 = .084, F = 149.919, p < .001). SWD, together with hypnotic medication use, exercise, shift work experience and the number of hours per shift, accounted for 36.5% of the variance in burnout scores (R 2 = .365, adjusted R 2 = .361, F = 90.323, p < .001). Regression coefficients and the confidence intervals (CI) for each step in the model that predicted mental health problems (GHQ‐12) and burnout are illustrated in Tables 3 and 4.

TABLE 3.

Unstandardized (B) and standardized (β) regression coefficients for each step in the model predicting mental health (General Health Questionnaire‐12)

Unstandardized Coefficients Standardized Coefficients 95% confidence interval for B
B SE β t p‐Value R 2 F Lower bound Upper bound
(Constant) 35.187 1.153 30.522 <.001 0.405 107.214 32.925 37.449
Work engagement −.175 .014 −.317 −12.299 <.001 −.202 −.147
SWD −2.213 .245 −.211 −9.048 <.001 −2.693 −1.733
Work environment −.082 .009 −.235 −9.011 <.001 −.099 −.064
Use of hypnotic medication −1.268 .327 −.088 −3.876 <.001 −1.910 −.626
Exercise −.833 .232 −.080 −3.586 <.001 −1.288 −.377
Shift experience .291 .090 .071 3.223 .001 .114 .469
Shift schedule .384 .147 .057 2.608 .009 .095 .673
Absences −.731 .337 −.048 −2.172 .030 −1.391 −.071
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TABLE 4.

Unstandardized (B) and standardized (β) regression coefficients for each step in the model predicting burnout (Maslach burnout inventory)

Unstandardized Coefficients Standardized Coefficients 95% confidence interval for B
B SE β t p‐Value R 2 F Lower bound Upper bound
(Constant) 39.673 1.973 20.108 <.001 .376 84.175 35.802 43.544
Work environment −.152 .015 −.285 −10.260 <.001 −.181 −.123
SWD −3.664 .385 −.228 −9.522 <.001 −4.419 −2.909
Work engagement −.249 .026 −.295 −9.699 <.001 −.300 −.199
Use of hypnotic medication −2.177 .514 −.099 −4.237 <.001 −3.185 −1.169
Job crafting .097 .020 .144 4.754 <.001 .057 .137
Shift time .894 .232 .087 3.860 <.001 .440 1.348
Shift experience .542 .142 .086 3.815 <.001 .263 .821
Absences −1.706 .529 −.074 −3.224 .001 −2.745 −.668
Exercise −1.021 .367 −.064 −2.783 .005 −1.741 −.301
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3.4. Moderated mediation analyses

Additionally, SWD and MBI significantly predicted mental health problems (β = −.282, .575, respectively, p < .001). When MBI was included in the model, there was a 57.5% increase in GHQ scores (β = .575, p < .001; Table 5).

TABLE 5.

Process program analysing how burnout mediates the relationship between SWD and mental health (n = 1,268)

Model Model 1 Model 2 Model 3
Independent variable Y = Mental health M = Burnout Y = Mental health
B SE B SE B SE
X = SWD −.715*** .053 −.754*** .053 −.282*** .047
M = Burnout − ‐ ‐ ‐ .575*** .023
F 180.217*** 203.530*** 438.510***
R 2 .125 .139 .409
Sobel test Indirect effect = −0.434 Z = −12.346***
Bootstrap Indirect effect Boot LLCI Boot ULCI
−0.434 −0.509 −0.366
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***p < .001.

4. DISCUSSION

A total of 58.1% of the participants suffered from SWD. Previous studies have shown that the incidence of SWD among shift nurses varied in different countries. For example, the incidence of SWD was 24.4% in Japan (Asaoka et al., 2013), 43.1% in South India (Anbazhagan et al., 2016), and 44.2% in Norway (Flo et al., 2012). The reason for these differences cannot be attributed solely to the intensity of shifts. Rather, the differences depended upon the specific conditions of shift work, such as opportunities for naps, night hours, circadian rhythm delays, rotation schedules and the average number of night shifts per month during the past year (Asaoka et al., 2013; Haile et al., 2019).

SWD explained approximately 8% of the variance in mental health, compared with 18.8% of the variance among Australian shift nurses (Booker et al., 2019). The reason for this difference between the two countries could be due to the different scales used to assess mental health. The GHQ‐12 questionnaire used to measure mental health was used in this study, whereas depression assessment tools typically had been used in previous studies. An additional reason for this difference between the two countries could be attributed to different sample selection ranges. This Chinese study used a large national sample of 1,268 nurses, whereas the Australian study used a local sample of only 179 nurses. Mental health and burnout both were related to SWD as well as to work engagement, and work environment and job crafting could help to prevent burnout and mental health problems. These findings support past work that showed an association between job crafting and burnout (Hakanen et al., 2017). The relationship between shift work disorders and mental health may be due to pathophysiological mechanisms, such as HPA Axis hyperactivity (Fernandez‐Mendoza & Vgontzas, 2013; Khan et al., 2020). The interactions among work engagement, work environment and burnout were obtained using a path analysis of job demands and job resources found in the Job Demands‐Resources model (Möckli et al., 2020). The relationship between job crafting and mental health may be due to the fact that job crafting may mediate the effect of a proactive personality on mental health (Zhang et al., 2018).

One surprising finding was that shift nurses who had worked for 5–10 years exhibited worse mental problems and burnout compared to other groups at statistically significant levels. This could be explained by the fact that nurses were responsible for the bulk of the department's functions or that their family responsibilities were particularly demanding during the hours shift work was needed. The need for nurses to invest a good amount of energy to meet the demands of both work and family could provoke more psychological problems and burnout. Consequently, it would be important for healthcare managers to pay greater attention to shift nurses who have worked for 5–10 years. For example, they could provide those nurses organizational support, such as access to assistants or better working environments.

Burnout mediated the relationship between SWD and mental health. Therefore, it is possible to improve mental health outcomes among nurses with initiatives designed to ameliorate burnout. The Luxembourg Declaration on Workplace Health Promotion (WHP) in the European Union also stipulates the need to include ergonomic scheduling, individual‐oriented measures and the adjustment of sleep–wake rhythms in order to reduce the threat that shift work poses to the physical and mental health of nurses (D'Ettorre & Pellicani, 2020). What needs to be emphasized here was the two‐way nature of this relationship: insufficient sleep may also lead to the evolution and lasting impact of burnout, especially among healthcare workers (Sørengaard & Saksvik‐Lehouillier, 2022). One systematic review on this topic demonstrated that poor health and moderate to high levels of burnout were linked to poor patient safety, such as medical errors (Hall et al., 2016).

4.1. Limitations

The study has several limitations. First, this was a cross‐sectional study; causal relationships among the variables could not be proven. One direction for future research would be a longitudinal study. Second, there could have been a more comprehensive review of the literature to identify the factors that impact mental health and burnout, such as work overload, work‐related stress, professional qualifications and/or hostile work environments; these factors could be included in the independent variables in order to increase the explanatory value of the dependent variable (López‐López et al., 2019). Third, the questionnaire used in this study was a subjective questionnaire based on self‐reporting. Objective indicators, such as circadian biomarkers and genes, could be included in future research. Finally, this study only conducted a sample survey of Chinese nurses working in hospitals. Therefore, caution should be exercised in extending the implications of these findings to other types of institutions, countries and cultural or professional groups.

5. CONCLUSION

Our study revealed that high‐risk nurses with shift work disorder are at a much higher risk for mental health problems and burnout. Furthermore, burnout negatively regulated the relationship between SWD and mental health. This study emphasized the importance of assessments and management of shift work disorder. The findings also evidenced a need to develop interventions designed to improve shift nurses' sleep patterns. Such initiatives could begin at the institutional level to improve the system of shift employment, provide amenable work environments and encourage workers to job craft. On a personal level, these workers could improve their situation through regular exercise. Collectively, these efforts could create improved working conditions and assure quality nursing services for patients.

AUTHOR CONTRIBUTIONS

Hui Cheng made substantial contributions to conception and design, or acquisition of data, or analysis and interpretation of data. Hui Cheng and Junyi Yang involved in drafting the manuscript or revising it critically for important intellectual content. Guangbi Liu given final approval of the version to be published. Qiaohong Wang and Hui Yang agreed to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. Each author should have participated sufficiently in the work to take public responsibility for appropriate portions of the content.

All authors have agreed on the final version and meet at least one of the following criteria [recommended by the ICMJE (http://www.icmje.org/recommendations/)]:

  • substantial contributions to conception and design, acquisition of data or analysis and interpretation of data.

  • drafting the article or revising it critically for important intellectual content

FUNDING INFORMATION

Excellent graduate student innovation project of Shanxi Province in China, No.2019BY083.

CONFLICT OF INTEREST

The authors declare that there was no conflict of interest.

ETHICAL APPROVAL

Our study was approved by the ethical committee of Shanxi Medical University (Approval No. 2019011). Participation in the study was voluntary, and consent was assumed when the participants responded to the online survey.

ACKNOWLEDGEMENTS

We thank LetPub (www.letpub.com) for its linguistic assistance and scientific consultation during the preparation of this manuscript. We would like to thank our team, managers and nurses from the Hospital.

Cheng, H. , Liu, G. , Yang, J. , Wang, Q. , & Yang, H. (2023). Shift work disorder, mental health and burnout among nurses: A cross‐sectional study. Nursing Open, 10, 2611–2620. 10.1002/nop2.1521

DATA AVAILABILITY STATEMENT

Author elects to not share data (Research data are not shared).

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