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. 2024 Mar 4;11(3):e2118. doi: 10.1002/nop2.2118

Alterations of functional brain activity and connectivity in female nurses working on long‐term shift

Yujie Dong 1, Xiaohong Wu 2, Yuqin Dong 1, Yuwei Li 1, Ke Qiu 1,✉
PMCID: PMC10910870  PMID: 38436535

Abstract

Aim

To investigate the alterations of functional brain activity and connectivity in female nurses working on long‐term shifts and explore their correlations with work‐related psychological traits.

Design

An exploratory cross‐sectional study.

Methods

Thirty‐five female nurses working on long‐term shifts (shift nurses) and 35 female nurses working on fixed days (fixed nurses) were enrolled. After assessing the work‐related psychological traits, including burnout, perceived stress, anxiety, and depression of nurses, the fractional amplitude of low‐frequency fluctuations (fALFF) and region of interest (ROI)‐based functional connectivity (FC) analyses were performed to investigate the differences of brain spontaneous activity and functional connectivity between these two groups of nurses. Thereafter, correlations between the functional brain parameters (fALFF and FC) and clinical metrics were investigated among the shift nurses.

Results

Compared to fixed nurses, shift nurses had higher burnout, perceived stress and depression scores, lower fALFF in the right dorsolateral prefrontal cortex (dlPFC), left and right superior parietal lobule (SPL), bilateral anterior cingulate cortex (ACC), and higher fALFF in the right superior/middle temporal gyrus, as well as decreased FC between the right dlPFC (the selected ROI) and bilateral ACC, left and right inferior frontal/orbitofrontal gyrus (IFG/IOFG), right SPL, and left middle occipital gyrus (voxel‐level p < 0.001, cluster level p < 0.05, GRF correction). Correlation analyses demonstrated that the fALFF value of the right dlPFC was significantly correlated with the burnout and anxiety scores, the FC value of the right dlPFC‐right SPL was correlated with the perceived stress and burnout scores, the FC value of the right dlPFC‐right IFG/IOFG was correlated with the burnout score in shift nurses (p < 0.05).

Conclusion

Shift nurses had work‐related altered functional activity and connectivity in the right frontoparietal network, which provided objective and visualised evidence to clarify the hazards of long‐term shift work on female nurses.

Patient or Public Contribution

Seventy nurses participated deeply as subjects in this study. These findings are expected to draw managers' attention to the harmful influences of shift work on nurses.

Keywords: burnout, functional neuroimaging, neuroimaging, nurses, shift work

1. INTRODUCTION

Shift work is an employment practice that encompasses a broad range of schedules, such as regular or irregular shifts between day and night, as well as between weekdays and weekends (Rivera et al., 2020). Given the expectation for healthcare staff to provide 24‐h service for hospitalised patients, shift work is inevitably an occupational characteristic necessary in the medical field, especially for nurses (Razavi et al., 2019). The prevalent shift work pattern of nurses is day, evening, and night rotation (Cao et al., 2020; d'Ettorre, 2017; Stimpfel et al., 2015), which means that three groups of nurses take turns to provide healthcare services for patients at day, evening, and night through shift handovers (Min et al., 2021b). Shift work offers numerous benefits for hospitals and patients. The regular and stable shift work pattern proves to be an effective method for ensuring uninterrupted medical services, relieving manpower shortages, and improving nursing quality (Cheng & Drake, 2019). However, the impacts of shift work on nurses themselves are usually negative. The long‐term irregular work pattern tends to disrupt the physiological rhythm of individuals, leading to burnout, emotional disorders, and even various physical and mental illnesses (Imes et al., 2023; Matheson et al., 2014). A recent cross‐sectional study from China demonstrated that about 60% of shift nurses exhibited work‐related disorders, manifesting as a higher incidence of mental health problems, sleep disorders, and burnout (Cheng et al., 2023). Moreover, long‐term shift work was identified to be a significant risk factor for various serious disorders, such as mental disorders (Booker et al., 2020), dementia (Ling et al., 2023), endocrine disorders (Hansen et al., 2016), and cardiovascular diseases (Vetter et al., 2016), especially for the females.

Neuroimaging serves as a noninvasive tool for investigating human brain structure and function. The application of neuroimaging techniques has provided visualised evidence to understand the impact of shift work on the physical and mental health of workers. For example, a recent neuroimaging study (Park et al., 2020) demonstrated that long‐term shift work contributed to the plasticity of grey matter morphology of the bilateral postcentral gyrus, right paracentral lobule, and left superior temporal gyrus of nurses. Moreover, grey matter alterations in the left postcentral gyrus mediated the influence of sleep disturbance on the depressive symptoms of the subjects. Another study (Lee et al., 2022) compared the differences in white matter structure of shift workers and non‐shift workers, finding that the shift workers exhibited higher fractional anisotropy in the bilateral anterior cingulum, and that the increased fractional anisotropy in the right anterior cingulum was correlated with the poor sleep quality of shift workers. These studies provided preliminary knowledge of shift work affecting the brain structural plasticity of workers, which was generally attributed to the shift work‐induced sleep deprivation and the resulting disruption of the internal environment. However, it is unclear whether and how long‐term shift work affects functional brain activity and connectivity patterns, and how abnormalities in functional brain activity are associated with the work‐related psychological traits of nurses.

Therefore, the current study enrolled a group of nurses working on long‐term shifts (shift nurses) and another group of nurses working on fixed days (fixed nurses) and evaluated their burnout, psychological stress, anxiety, and depression conditions. Then, we acquired the Magnetic Resonance Imaging (MRI) data of nurses and compared the functional brain activity and connectivity patterns between these two groups of nurses using the fractional amplitude of low‐frequency fluctuations (fALFF) (Zou et al., 2008) and region of interest (ROI)‐based functional connectivity (FC) (Briley et al., 2022) methods. fALFF is an advancement of traditional spectrum analysis, which has good sensitivity and specificity regarding the spontaneous neural activity of the human brain (Shu et al., 2020). FC is the classic approach for cross‐regional connections analysis, which reflects the consistency of functional activity of two distant regions (Fingelkurts et al., 2005). The results of this study were expected to provide objective and visualised evidence to elucidate the hazards of long‐term shift work on female nurses and further offer a potential quantitative indicator for monitoring and mitigating the physical and psychological hazards of shift work in the future.

2. MATERIALS AND METHODS

2.1. Research design

This was an exploratory cross‐sectional study comparing between‐group differences in work‐related psychological traits, as well as functional brain activity and connectivity patterns, in female shift nurses and female fixed nurses.

2.2. Participants

Thirty‐five shift nurses and 35 fixed nurses shift were recruited as volunteers from three hospitals in Leshan, Sichuan, China. Specifically, fixed nurses were recruited from the outpatient department and physical examination center, while shift nurses were recruited from the internal medicine wards of the hospital. The included nurses had to meet the following inclusion criteria: (1) junior nurses; (2) 20–35 years old; (3) female; (4) right‐handed (Gur et al., 1982); (5) unmarried or married but not in pregnancy; (6) free from the endocrine, neurological or psychiatric diseases, or other serious illnesses; (7) had no contraindications for MRI scan. In addition, shift nurses should fulfil the following criteria: worked alternating day (8:00–16:00), evening (16:00–23:00), and night (23:00–8:00) shifts for more than one year. Fixed nurses should have no experience in working shifts or have remained fixed work (8:00–18:00) for nearly one year.

2.3. Clinical measures

The Chinese version of the Maslach Burnout Inventory Human Service Survey (MBI‐HSS) (Schaufeli et al., 1993) was introduced to assess the occupational burnout of nurses. The MBI‐HSS is a self‐assessed scale consisting of 17 items and adopts a Likert scale of 0–6. The higher MBI‐HSS scores indicated greater burnout of nurses. The Chinese version of the Perceived Stress Scale (PSS) (Zang et al., 2022) was used to assess nurses' subjective perceptions of work‐related stress. PSS is a self‐assessed questionnaire that contains 14 items and is scored on a Likert 0–4 scale. The higher the score, the greater the psychological stress of the nurses.

In addition, the Zung Self‐Rating Anxiety Scale (SAS) (Zung, 1971) and the Zung Self‐Rating Depression Scale (SDS) (Zung, 1965) were utilised to evaluate the emotional states of the nurses. The SAS and SDS are the classic scales for evaluating the anxiety and depression conditions of subjects. Both the SAS and SDS contain 20 questions and are scored on a Likert 1–4 scale. Standardised scores greater than 50 on the SAS and SDS indicated that the nurses may be suffering from anxiety and depression.

2.4. Clinical data collection

After the enrolled nurses signed informed consent, we collected demographic information from them through an interview and obtained their MBI‐HSS, PSS, SAS, and SDS scores through scale self‐scoring.

2.5. Clinical data analysis

Statistical analysis of clinical data was performed using SPSS 24.0. The continuous variables were reported with mean ± standard deviation. Between‐group comparisons of demographic characteristics and psychological traits of shift nurses and fixed nurses were conducted with independent samples t‐tests. The statistical significance threshold was set to p < 0.05.

2.6. MRI data acquisition

The MRI data, including high‐resolution T1 images and blood‐oxygen‐level‐dependent (BOLD) images, was acquired with a 3.0 T Philips MRI scanner. The T1 image scanning parameters were as follows: repetition time/echo time: 9.1 ms/3.0 ms, slice thickness: 1 mm, matrix size: 256 × 256, field of view: 240 × 240, flip angle: 12°. The BOLD images scanning parameters were as follows: repetition time/echo time: 2000 ms/30 ms, slice thickness: 3.5 mm, number of slices: 37, matrix size: 64 × 64, field of view: 240 × 240, flip angle: 90°. Considering the effects of chronotype on brain activity, all the MRI data was acquired in the afternoon.

2.7. MRI data preprocessing

MRI data preprocessing, as well as fALFF and FC analysis, were performed with DPABI 4.1 (http://rfmri.org/DPARSF) (Yan et al., 2016) by X.W. (one of the authors who did not know the details of study design).

The preprocessing steps were as follows: (1) removing the first 10 time points of the scanning sequence; (2) slice timing correction; (3) motion correction and excluding participants with mean frame‐wise displacement more than 0.2 (Power et al., 2012); (4) spatial normalisation, registering individual images to the standard space template and resampling to 3 × 3 × 3 mm3 voxels; (5) spatial smoothing with a 6 mm kernel.

2.8. fALFF analysis

After data preprocessing, the fast Fourier transform was used to transform the time series of each voxel to the frequency domain to obtain the power spectrum. Then, the square root was calculated at each frequency of the power spectrum, and the mean square root was obtained across the 0.01–0.08 Hz band for each voxel. Finally, the fALFF in each voxel was divided by the mean fALFF of the global brain within a brain mask to standardize for voxels in the entire brain. In order to make the fALFF values of the voxels maintain a normal distribution, the calculated fALFF values were transformed into z‐scores to obtain the final fALFF maps for statistical analysis. Independent t‐tests were utilised for intergroup comparisons of fALFF, with statistical significance threshold set at voxel‐level p < 0.001, cluster‐level p < 0.05, and Gaussian Random Field (GRF) correction.

2.9. FC analysis

The first step of ROI‐based FC analysis was to determine the ROI. In this study, we identified the ROI based on the results of the fALFF analysis. The regions with the most pronounced difference between shift nurses and fixed nurses were selected as ROI. The mean time series of the ROI were extracted based on the Utilities Toolbox of DPABI and the ROI‐voxel FC analysis was conducted with the Pearson correlation analysis. Independent t‐tests were applied for between‐group comparisons of FC in shift nurses and fixed nurses. The significance threshold was the same as the fALFF analysis (voxel‐level p < 0.001, cluster‐level p < 0.05, GRF correction).

2.10. Correlation analysis

In addition, partial correlation analyses were conducted to explore the correlations between the fALFF and FC metrics and MBI‐HSS, PSS, SAS, and SDS scores in shift nurses. Age, working years, and mean frame‐wise displacement were taken as covariates in the correlation analyses.

3. RESULTS

3.1. Demographic characteristics

Two nurses in the shift group were excluded because of excessive head movement. Consequently, the clinical data and MRI data analysis included 33 shift nurses and 35 fixed nurses. No statistically significant difference was observed between these two groups of nurses in age, years of work, and SAS score (p > 0.05). While compared to fixed nurses, shift nurses had significantly higher MBI‐HSS, PSS, and SDS scores (p < 0.05), indicating that shift nurses experienced more severe burnout, psychological stress, and depression than fixed nurses (Table 1).

TABLE 1.

Demographic characteristics and psychological traits of the two groups of nurses.

Age Working years MBI‐HSS PSS SAS SDS
Shift nurses (n = 33) 27 ± 3.66 4.3 ± 1.89 63.55 ± 6.24 31.18 ± 6.68 52.75 ± 13.97 51.32 ± 10.39
Fixed nurses (n = 35) 26.6 ± 3.96 3.97 ± 2.01 47.34 ± 10.99 24.69 ± 6.07 46.64 ± 11.34 44.45 ± 11.79
T 0.371 0.699 7.415 4.199 1.986 2.542
p 0.712 0.487 <0.001** <0.001** 0.051 0.013*
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Abbreviations: MBI‐HSS, The Chinese version of the Maslach Burnout Inventory Human Service Survey; PSS, The Chinese version of the Perceived Stress Scale; SAS, the Zung Self‐Rating Anxiety Scale; SDS, the Zung Self‐Rating Depression Scale.

**

p < 0.001;

*

p < 0.05.

3.2. fALFF analysis

The fALFF analysis results demonstrated that compared to fixed nurses, shift nurses had significantly decreased spontaneous functional activity in the right dorsolateral prefrontal cortex (dlPFC), left and right superior parietal lobule (SPL), and bilateral anterior cingulate cortex (ACC), and significantly increased functional activity in the right superior/middle temporal gyrus (STG/MTG) (voxel‐level p < 0.001, cluster‐level p < 0.05, GRF correction) (Table 2, Figure 1).

TABLE 2.

Alterations of fALFF in shift nurses compared to fixed nurses.

Cluster Cluster size MNI coordinates (x, y, z) T Contrast
dlPFC.R 261 50 19 21 −5.34 ↓
SPL.L 34 −9 −39 66 −5.06 ↓
SPL.R 106 25 −62 65 −4.66 ↓
ACC.Bi 53 2 35 17 −4.07 ↓
STG/MTG.R 197 57 −47 5 5.31 ↑
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Abbreviations: ACC, anterior cingulate cortex; Bi, bilateral hemisphere; dlPFC, dorsolateral prefrontal cortex; L, left hemisphere; MNI, Montreal Neurological Institute; R, right hemisphere; SPL, superior parietal lobule; STG/MTG, superior/middle temporal gyrus.

FIGURE 1.

FIGURE 1

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Brain regions with altered fALFF in shift nurses. ACC, anterior cingulate cortex; Bi, bilateral hemisphere; dlPFC, dorsolateral prefrontal cortex; L, left hemisphere; R, right hemisphere; SPL, superior parietal lobule; STG/MTG, superior/middle temporal gyrus.

3.3. FC analysis

Since the dlPFC was the region with the most pronounced difference in functional brain activity between the two groups of nurses, it was selected as the ROI in the following FC analysis. The results of ROI‐based FC analysis showed that compared to fixed nurses, shift nurses had significantly decreased FC between the right dlPFC and bilateral ACC, left and right inferior frontal/orbitofrontal gyrus (IFG/IOFG), right SPL, and left middle occipital gyrus (MOG) (voxel‐level p < 0.001, cluster‐level p < 0.05, GRF correction) (Table 3, Figure 2).

TABLE 3.

Alterations of right dlPFC‐voxel FC in shift nurses compared to fixed nurses.

Cluster Cluster size MNI coordinates (x, y, z) T Contrast
ACC.Bi 280 −3 27 −25 −5.70 ↓
IFG/IOFG.R 261 36 39 0 −5.58 ↓
MOG.L 254 −27 −90 17 −5.06 ↓
IFG/IOFG.L 175 −36 36 −3 −4.85 ↓
SPL.R 93 39 −24 54 −4.73 ↓
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Abbreviations: ACC, anterior cingulate cortex; Bi, bilateral hemisphere; IFG/IOFG, inferior frontal/orbitofrontal gyrus; L, left hemisphere; MNI, Montreal Neurological Institute; MOG, middle occipital gyrus; R, right hemisphere; SPL, superior parietal lobule.

FIGURE 2.

FIGURE 2

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Brain regions with altered FC of dlPFC in shift nurses. ACC, anterior cingulate cortex; Bi, bilateral hemisphere; IFG/IOFG, inferior frontal/orbitofrontal gyrus; L, left hemisphere; MOG, middle occipital gyrus; R, right hemisphere; SPL, superior parietal lobule.

3.4. Correlation analysis

The results of partial correlation analysis showed that the fALFF value of the right dlPFC was negatively correlated with their MBI‐HSS score (R = 0.418, p = 0.022) and SAS score (R = 0.439, p = 0.015) in shift nurses. Moreover, the FC value of right dlPFC‐right SPL was negatively correlated with both PSS score (R = 0.497, p = 0.005) and MBI‐HSS score (R = 0.367, p = 0.046), the FC value of right dlPFC‐right IFG/IOFG was negatively correlated with MBI‐HSS score (R = 0.369, p = 0.042) in shift nurses (p < 0.05) (Figure 3).

FIGURE 3.

FIGURE 3

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Correlations between the altered brain functional parameters and clinical metrics in shift nurses. dlPFC, dorsolateral prefrontal cortex; fALFF, fractional amplitude of low‐frequency fluctuations; FC, functional connectivity; IFG/IOFG, inferior frontal/orbitofrontal gyrus; MBI‐HSS, The Chinese version of the Maslach Burnout Inventory Human Service Survey; PSS, The Chinese version of the Perceived Stress Scale; R, the right hemisphere; SAS, the Zung Self‐Rating Anxiety Scale; SPL, superior parietal lobule.

4. DISCUSSION

This study investigated where there were differences in burnout, perceived stress, anxiety, and depression, as well as brain functional activity and connectivity, between female nurses who worked on long‐term shifts and fixed day. The results demonstrated that shift nurses had higher MBI‐HSS, PSS, and SDS scores than fixed nurses. These results were consistent with the previous findings that shift work could induce alterations in the sleep patterns of nurses, which in turn led to restlessness, depression, anxiety, and nervousness (Karatsoreos, 2012). Shift work disorder was strongly associated with depression and anxiety in nurses (Booker et al., 2020). As shift work continues, the negative emotions and work‐related stress of nurses accumulate, leading to increased symptoms of depression and anxiety, and ultimately reduced work efficiency (Li et al., 2021). Moreover, as detected in a prospective study, after one year of shift work, workers experienced a decline in their mental health and an increase in clinical symptoms of depression and anxiety, which were modulated by sleep disorders and burnout (Kalmbach et al., 2015). The theory of chronobiology provides a plausible explanation for these phenomena: irregular or reduced sleep duration leads to reduced sensitivity of peripheral cortisol receptors (Kino & Chrousos, 2011) and decreased melatonin secretion (Rahman et al., 2010), which consequently affects homeostasis of the human body and induces emotional and psychological disorders.

In addition to experiencing higher levels of burnout and significant psychological stress, shift nurses also exhibited suppressed spontaneous activity and reduced functional connectivity in the right dlPFC, SPL, and IFG/IOFG, which had been identified as the critical nodes of the right frontoparietal network (Cao et al., 2021; Vendetti & Bunge, 2014). These findings supported the disruption of functional activity and connectivity patterns in the right frontoparietal network in nurses working on long‐term shift. The frontoparietal network is the key region responsible for higher cognitive processing in the human brain. According to the lateralisation of their corresponding functions, the frontoparietal network is divided into left and right subnetworks. The right frontoparietal network is mainly responsible for working memory, endogenous perception and emotion perception, and inhibitory control. In contrast, the left frontoparietal network mainly involves speech, semantic recognition, and cognition (Marek & Dosenbach, 2018; Vendetti & Bunge, 2014). Numerous neuroimaging studies have shown that abnormal right frontoparietal network activity might be closely related to impaired working memory and attention deficits (Becker et al., 2022; Chen et al., 2023; Letkiewicz et al., 2022; May & Kana, 2020; Tan et al., 2021; Yuk et al., 2020; Zhou et al., 2023). A previous neuroimaging meta‐analysis also dedicated that clinical patients with emotional regulation disorders exhibited reduced activity in the right frontoparietal network and compensatory activation of emotion‐related brain areas, such as the insula and temporal gyrus (Pico‐Perez et al., 2017).

Furthermore, some studies on sleeping disorders provided further evidence for understanding the right frontoparietal network and psychological abnormalities in shift nurses. The previous studies detected that long‐term sleep deprivation could seriously affect emotional regulation, cognitive attention, and working memory capacity (Gerhardsson, Akerstedt, et al., 2019; Gerhardsson, Fischer, et al., 2019). Under conditions of sleep deprivation, subjects exhibited suppressed right frontoparietal network activity and unstable mutual inhibition between the frontoparietal network and the default mode network when performing attention control tasks (Krause et al., 2017). Long‐term working shift, especially irregular rotation, are highly likely to result in a mismatch between actual and biological sleep and wake times, resulting in excessive sleepiness. With mistimed sleep and excessive sleepiness, both the working memory and emotional regulation of nurses are impaired (Esmaily et al., 2022). Therefore, the plasticity of the right frontoparietal network activity and increased burnout found in shift nurses in this study may be attributed to long‐term chronic sleep disorders.

In addition to the right frontoparietal network, this study also identified decreased function activity in the bilateral ACC and decreased FC between bilateral ACC and right dlPFC in nurses who worked on long‐term shift. The ACC is an essential component of the limbic system and a key node for emotion perception and stress control (Qiu et al., 2022; Rolls et al., 2022). Previous studies have shown that patients with emotional disorders, such as anxiety and depression, generally exhibited abnormal functional activity and structure in ACC (Cheng et al., 2021; Gasquoine, 2013; Wlad et al., 2023). Results from animal experiments have also demonstrated that the content of ACC‐derived neurotrophic factors and chronic stress in mice were closely related to negative emotions and behaviours(Wen et al., 2022; Yang et al., 2017). The current study observed a significant increase in psychological stress and depression scores, as well as a decrease in spontaneous functional activity in ACC in shift nurses, which reverified the correlations between ACC and stress and emotional regulation. In addition to emotional regulation, as part of the old cortex, the ACC is closely related to human vigilance (Leehr et al., 2019). A previous study found that acute sleep deprivation impaired subjects' vigilance and task performance (Piantoni et al., 2013). Shift nurses generally face chronic sleep deprivation and resulting vigilance and reaction decrease (Duran‐Gomez et al., 2021; Min et al., 2021a). Therefore, the reduced functional activity and connectivity in ACC might also relate to the vigilance impairment of nurses.

In addition, the results of correlation analysis indicated that the abnormal fALFF of the right dlPFC, FC of right dlPFC‐right SPL, and FC of right dlPFC‐right IFG/IOFG of shift nurses were significantly associated with their burnout and psychological stress condition. The negative correlation coefficients implied that shift nurses with lower spontaneous activity and synchrony in the right dlPFC suffered from more severe clinical symptoms. These results explained the reasons behind nurse burnout and abnormal psychological states in the context of long‐term shift work from the perspective of brain functional plasticity. Moreover, it also provided a potentially quantifiable indicator for diagnosing and monitoring the severity and hazards of long‐term shift work.

There were several limitations in this study. First, this was a cross‐sectional survey that identified differences in the functional activity patterns of shift nurses versus fixed nurses. The progressive effects of long‐term shift work on the functional brain activity and connectivity patterns of nurses need to be further revealed in a longitudinal study. Second, because of the limitations of the sample source, only female nurses were included in this study. It has been suggested that shift work and sleep deprivation affected males and females to different degrees (Anderson et al., 2023). Therefore, future study needs to focus on the differences in the impact of shift work on male and female nurses. Third, this was a resting‐state fMRI study, and the findings do not provide a strong indication of a causal relationship between functional brain activity and alterations in work‐related psychological traits. The follow‐up studies could use a task design to further investigate the correlations between shift work‐induced abnormal brain activity patterns and impairments of cognition and working memory in nurses. Fourthly, the inclusion criteria for fixed nurses were the absence of experience in shift work for nearly one year. However, a recent study suggested that former night shift workers might also manifest structural and functional neural plasticity (Bittner et al., 2022). Therefore, further validation of the current findings in nurses who have not experienced shift work is needed.

5. CONCLUSION

In conclusion, this current study indicated with the fALFF and FC approaches that female nurses working on long‐term shift had decreased brain functional activity and connectivity in the right frontoparietal network, which were associated with their burnout, stress, and depression conditions. The results provided new insights into the impacts of long‐term shift work on female nurses' physical and mental health from a functional neuroimaging perspective and offered a potential and quantifiable indicator for future research on how to monitor and further mitigate the hazards of shift work.

AUTHOR CONTRIBUTIONS

Ke Qiu and Yuqin Dong contributed to the conception and design of the study. Yujie Dong, Xiaohong Wu, and Yuwei Li performed data collection and analysis. Yujie Dong wrote the first draft of the manuscript. Ke Qiu revised the manuscript. All authors read and approved the submitted version.

FUNDING INFORMATION

This work was supported by the Sichuan Science and Technology Project (No. 19RKX0261) and the Key Science and Technology Innovation Project of Leshan Vocational and Technical College (No. 2019020).

CONFLICT OF INTEREST STATEMENT

The authors declare that the research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest.

ETHICS STATEMENT

The study protocol was approved by the ethics committee of Leshan Hospital of Traditional Chinese Medicine (No. 2019‐10‐003).

PATIENT CONSENT STATEMENT

All participants signed an informed consent before entering the study.

ACKNOWLEDGEMENTS

The authors thank all those participants, as well as the MRI operators, for their help in MRI data collection.

Dong, Y. , Wu, X. , Dong, Y. , Li, Y. , & Qiu, K. (2024). Alterations of functional brain activity and connectivity in female nurses working on long‐term shift. Nursing Open, 11, e2118. 10.1002/nop2.2118

Yujie Dong and Xiaohong Wu contributed equally and shared the first authorship.

DATA AVAILABILITY STATEMENT

The main data supporting our findings can be found within the manuscript. The raw data can be requested from the corresponding author.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

The main data supporting our findings can be found within the manuscript. The raw data can be requested from the corresponding author.

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