Fatigue and coping strategies among Chinese night-shift nurses: a cross-sectional study

Abstract

Background

Night-shift work is a crucial component of nursing but is associated with significant fatigue, which may impact both nurse well-being and patient safety. Understanding the levels of fatigue and the coping strategies employed by nurses can help develop effective interventions. This study aimed to assess the fatigue levels of Chinese night-shift nurses and explore commonly used anti-fatigue strategies.

Methods

A cross-sectional study was conducted in Zhejiang Province, China, using the Occupational Fatigue Exhaustion/Recovery Scale (OFER) questionnaire. The survey assessed acute and chronic fatigue levels, fatigue recovery, and anti-fatigue strategies among nurses. Statistical analysis was performed using SPSS 26.0.

Results

Among the 371 valid responses, chronic fatigue levels (66.41 ± 24.17) were higher than acute fatigue levels (57.31 ± 15.61). Nurses with higher education levels reported lower acute fatigue, while older, more experienced nurses and those working in higher-grade hospitals had lower chronic fatigue. Common coping strategies included naps (63.88%) and stimulant consumption (54.72%), with coffee (45.37%) and milk tea (23.28%) being the most popular drinks.

Conclusion

Our findings indicate that Chinese night-shift nurses experience substantial fatigue, especially chronic fatigue, which is influenced by factors including education, age, clinical experience, exercise frequency, and hospital grade. Although personal coping strategies are common, they fall short in mitigating fatigue, underscoring the need for comprehensive interventions that combine individual and organizational measures.

Clinical trial number

not applicable.

Background

Shift work, defined as employment outside the conventional 9 a.m. to 5 p.m. schedule [1], affects a significant portion of the global workforce. It is estimated that approximately 20–29% of workers worldwide are engaged in shift-based roles [2], which are common in sectors such as healthcare, security, transportation, and manufacturing. Among these, healthcare professionals represent a particularly vulnerable group. Night-shifts are an essential component of nursing practice, playing a critical role in maintaining the continuity and quality of patient care. However, nurses working night shifts are frequently exposed to excessive workloads, which can lead to both mental and physical exhaustion, fatigue, and sleep deprivation [3, 4]. Evidence suggests that night-shift work significantly impairs cognitive function and increases the risk of medical errors among nurses [5, 6]. In addition to performance-related issues, night-shift work has been associated with a range of long-term health risks, including metabolic syndrome, type 2 diabetes, obesity, dyslipidemia, coronary artery disease, hypertension, and even certain cancers [7,8,9,10,11,12].

Fatigue is a critical issue for nurses, particularly those working night shifts. Studies have consistently shown that night-shift nurses experience higher levels of fatigue and poorer sleep quality compared to day-shift nurses [13, 14]. Nurses working consecutive night shifts face significant sleep deprivation, with shorter sleep durations and less time spent in bed compared to off-duty days [15]. Night shift nurses who experience poor sleep are more likely to report higher levels of chronic fatigue [16]. The impact of fatigue on nurses is substantial, potentially leading to medical errors, decreased performance, and social problems [17]. These findings underscore the urgent need for effective fatigue management strategies in clinical settings. Despite the growing awareness of shift-related fatigue, there remains a lack of empirical studies focusing specifically on the relationship between fatigue, coping strategies, and night-shift work among Chinese surgical nurses. Addressing this gap is essential for developing targeted interventions to improve nurse well-being and patient safety.

Various tools have been developed to assess fatigue in healthcare settings, including both single-dimensional scales (e.g., Fatigue Severity Scale, Chinese version of the Li Fatigue Scale) and multidimensional instruments (e.g., Fatigue Scale-14, Fatigue Assessment Scale, Multidimensional Fatigue Scale) [18]. Among them, the Occupational Fatigue Exhaustion/Recovery Scale (OFER) has demonstrated strong reliability and validity across different cultural contexts, particularly for assessing fatigue in nurses [19, 20]. The OFER differentiates between acute and chronic fatigue and also measures inter-shift recovery, making it especially useful for informing targeted interventions. Its content validity index of 0.92 supports its suitability for use among Chinese nurses [21]. By offering a comprehensive view of work-related fatigue, the OFER can aid nursing administrators in identifying contributing factors and developing strategies to enhance both staff well-being and patient safety.

This article presents the findings of a study conducted in Zhejiang Province, aimed at assessing the fatigue levels of surgical nurses on night shifts and exploring effective anti-fatigue strategies. The study seeks to offer practical recommendations to alleviate night shift fatigue, minimize medical errors, and foster a more efficient and harmonious healthcare environment.

Methods

Study design and setting

A cross-sectional study was conducted between October and December 2022 in Zhejiang Province, China, covering 18 hospitals of various tiers and grades (primary, secondary, tertiary; Grades A, B, and C). Tertiary Grade A is the highest level, offering the most advanced medical care and research. The participating institutions were distributed across six cities within the province, representing a mix of urban and suburban healthcare settings. The study was approved by the institutional review board of the Second Affiliated Hospital, Zhejiang University School of Medicine (No. 20221131), and permission was obtained from both the hospital nursing department directors and the participating nurses.

Participants and recruitment

Nurses were recruited from the departments of orthopedics, general surgery, thoracic surgery, and urology, which are all within the surgical system. Stratified sampling was employed to ensure diversity across geographic areas within Zhejiang Province. Eligible participants were: (1) registered nurses with at least two years of clinical experience; (2) working in one of the targeted surgical departments; (3) performing night shifts at least third a month. Nurses who did not meet these criteria or who failed to complete the questionnaire in full were excluded.

Recruitment was facilitated through departmental nursing managers, who distributed the online questionnaire via WeChat, a commonly used communication platform in China. The recruitment and exposure period took place from October 1 to December 1, 2022.

Exposure, outcomes, and variables

Primary exposure: night-shift work (defined as working between 9 p.m. and 8 a.m. at least two times per month).

Primary outcomes: acute fatigue, chronic fatigue, and intershift recovery, measured using the OFER Scale [19].

Predictor variables included: demographics (age, gender, marital status, education), professional background (years of experience, department, hospital grade), lifestyle (sleep duration, exercise frequency, night shift frequency).

Potential confounders: age, education level, years of experience, hospital grade, and sleep habits — all known to influence fatigue levels.

Effect modifiers: exercise frequency and hospital grade were analyzed for potential modifying effects on fatigue outcomes, as previous research suggests these may buffer fatigue.

Data collection tool

A researcher-made online questionnaire was developed, consisting of three sections: (1) demographic and professional information; (2) fatigue measurement using the OFER scale, which includes three subscales (acute fatigue, chronic fatigue, recovery); (3) self-reported coping strategies, including naps, beverage choices (e.g., coffee, tea, milk tea), and other fatigue mitigation behaviors.

The OFER assesses acute and chronic fatigue, as well as the ability to recover from work-related exhaustion. The OFER consists of three subscales: the Chronic Fatigue Subscale, the Acute Fatigue Subscale, and the Intershift Recovery Subscale, each containing five items. Responses are recorded on a 7-point Likert scale (0 = strongly disagree to 6 = strongly agree). The final score for each subscale is calculated using the formula: sum (subscale item scores) / 30 × 100, with possible values ranging from 0 to 100. Based on Winwood et al. (2006), scores are categorized as follows: 1–25 (low level), 26–50 (low–moderate level), 51–75 (moderate–high level), and 76–100 (high level) [22].

Efforts to minimize bias

To reduce selection bias, a stratified sampling method was applied across hospitals of different geographic regions in Zhejiang Province. Inclusion criteria were clearly defined to ensure consistency in participant selection. The survey was anonymous and self-administered to minimize social desirability bias and allow participants to respond honestly. Furthermore, all participants were assured of data confidentiality and informed that their responses would have no impact on their employment evaluations.

To reduce information bias, a standardized and validated fatigue scale (OFER) was used, with clear instructions provided to participants. The questionnaire was pilot tested among a small group of nurses (not included in the final analysis) to ensure clarity and comprehensibility.

Study size

Sample size estimation was based on a 95% confidence level, a 5% margin of error, and an assumed moderate effect size for fatigue variation across different demographics. Using these parameters and a conservative response distribution (50%), a minimum required sample size of approximately 370 nurses was calculated using standard sample size formulas for cross-sectional studies. To account for possible incomplete responses, the questionnaire was distributed to over 400 nurses, resulting in 371 valid responses included in the final analysis.

Statistical analysis

Data analysis was performed using SPSS 26.0. Continuous variables were reported as mean ± standard deviation, while categorical variables were summarized using counts and percentages. Pearson correlation analysis was used to assess the relationships between continuous variables and levels of acute and chronic fatigue, while Spearman correlation analysis was applied for ordinal or categorical variables. P values of < 0.05 were interpreted as statistically significant.

Potential confounding factors were considered and partially controlled through study design. A stratified sampling approach was used to ensure balanced representation across regions. Only fully completed questionnaires were included in the analysis. Responses with missing key variables (e.g., fatigue scale scores or demographic data) were excluded during the initial data screening process. This complete-case analysis approach was used to maintain data integrity and reduce bias from imputation.

Results

Demographic characteristics of surveyed nurses

A total of 443 nurses were invited to participate. Among these, 13 nurses either declined to participate and 59 nurses submitted incomplete questionnaires and were therefore excluded. Ultimately, 371 fully completed and valid questionnaires were included in the analysis. The majority of participants were female (96.23%), with an average age of 30.46 ± 5.64 years. Most were married (64.42%) and held a bachelor’s degree (70.62%). The average nursing experience was 8.83 ± 5.69 years. Regarding hospital classification, 59.73% of respondents worked in tertiary grade A hospitals, and 62.02% held the title of primary nurse practitioner. The nurses reported an average of 6.04 ± 2.51 night shifts per month and 6.49 ± 0.78 h of sleep per day (Table 1).

Table 1 Characteristics of the nurses surveyed (n = 371)

Fatigue levels among night shift nurses

The mean chronic fatigue score (66.41 ± 24.17) was higher than the acute fatigue score (57.31 ± 15.61), indicating a prevalent issue of prolonged fatigue among nurses. The mean fatigue recovery score was 40.98 ± 13.20, suggesting low–moderate recovery ability. A detailed breakdown of fatigue levels shows that 61.46% of nurses experienced moderate to high levels of acute fatigue, while 42.05% reported high levels of chronic fatigue. Nearly 65% of participants exhibited low-to-moderate recovery ability, and only 0.81% achieved a high recovery level (Table 2).

Table 2 Fatigue levels and recovery scores among night shift nurses

Correlation between sociodemographic factors and fatigue

Correlation analysis revealed that acute fatigue was significantly and negatively associated with education level (r = -0.119, p = 0.021), suggesting that nurses with higher academic qualifications tended to report lower levels of acute fatigue. Chronic fatigue showed significant negative correlations with age (r = -0.116, p = 0.026), years of nursing experience (r = -0.121, p = 0.019), exercise frequency (r = -0.125, p = 0.016), and hospital grade (r = -0.109, p = 0.037), indicating that more experienced, physically active nurses working in higher-grade hospitals had lower levels of long-term fatigue (Table 3).

Table 3 Correlation between sociological factors and fatigue of nurses

Relationship between fatigue and recovery

Further correlation analysis revealed a moderate, negative relationship between chronic fatigue and fatigue recovery (r = -0.478, p < 0.001), suggesting that poor recovery ability is closely linked to higher levels of chronic fatigue. A weaker but still statistically significant negative correlation was also found between acute fatigue and fatigue recovery (r = -0.158, p = 0.002), indicating that recovery capacity also influences short-term fatigue, albeit to a lesser extent (Table 4).

Table 4 Correlation between fatigue recovery, chronic, and acute fatigue

Coping strategies for fatigue

A range of personal strategies was employed by nurses to mitigate fatigue during night shifts. Napping was the most common (63.88%), followed by the consumption of refreshing beverages (54.72%). Among drinks, coffee (45.37%) was the most frequently consumed, followed by milk tea (23.28%) and tea (20.70%). Other reported strategies included mental concentration techniques (17.25%), exposure to bright lighting (15.63%), and regular exercise (13.48%). Interestingly, 16.17% of participants reported not using any coping methods, while a small percentage (2.96%) reported using other unspecified strategies (Table 5).

Table 5 Measures to reduce night shift fatigue (n = 371)

Discussion

This study provides a comprehensive overview of fatigue among Chinese night-shift nurses, with several key findings. First, chronic fatigue levels were higher than acute fatigue levels, indicating a widespread issue of prolonged fatigue. Second, nurses with higher education levels reported lower acute fatigue, while chronic fatigue was significantly lower among older, more experienced nurses, those with higher exercise frequency, and those working in higher-grade hospitals. Third, although nearly all nurses reported experiencing fatigue, more than half frequently employed coping strategies such as taking naps and consuming stimulant beverages. These findings highlight the need for targeted interventions to address both physical fatigue and lifestyle-related risk factors in the nursing population.

Occupational fatigue is a common concern among nurses globally, with varying patterns observed across different countries and healthcare systems. For instance, a meta-analysis involving 1,137 nurses in the United States reported higher levels of acute fatigue (67.3 ± 20.5) compared to chronic fatigue (41.4 ± 23.7) [23]. Similarly, Sharifah et al. [24] found that Saudi nurses experienced more acute fatigue (57.01 ± 17.12) than chronic fatigue (52.27 ± 23.19). In Istanbul, both chronic (59.87 ± 26.81) and acute fatigue (64.31 ± 22.98) levels were relatively high, with acute fatigue again being more prominent [20]. In contrast, our findings revealed a reversed trend among Chinese night-shift nurses, with chronic fatigue (66.41 ± 24.17) surpassing acute fatigue (57.31 ± 15.61), suggesting that persistent, long-term exhaustion is a more pressing issue in this population. Notably, a significant negative correlation was observed between inter-shift recovery and both chronic and acute fatigue, reinforcing the importance of adequate recovery—a result consistent with previous research [24]. In South Korea, nurses working rotating shifts also reported high levels of fatigue, with acute fatigue (70.40) and chronic fatigue (73.39) both elevated and relatively balanced [25]. These cross-national differences may stem from diverse factors such as healthcare system structure, nurse-to-patient ratios, shift scheduling practices, rest opportunities during shifts, and the availability of institutional support for fatigue management. Therefore, localized and context-specific strategies are essential for effectively addressing occupational fatigue among nurses.

Work-related fatigue among nurses is influenced by multiple factors. Prior studies have shown that educational level plays a significant role, with lower education levels associated with increased fatigue and reduced work ability [26]. Consistent with these findings, our study revealed a negative correlation between education level and acute fatigue scores. This may be explained by the tendency of nurses with higher educational attainment to hold more senior or administrative positions, which involve less physical strain and lower shift-related stress. In addition, chronic fatigue was negatively associated with age, years of nursing experience, hospital grade, and exercise frequency. These findings suggest that older, more experienced nurses, those who regularly exercise, and those working in higher-grade hospitals may demonstrate greater resilience to chronic fatigue—possibly due to greater job familiarity, access to more institutional resources, and supportive working environments. This is supported by the study of Gabrielle Jones et al. [27], which reported that increased social support from supervisors and colleagues can reduce stress and fatigue among healthcare workers. The observed positive impact of regular physical activity on reducing fatigue aligns with previous research indicating that exercise can enhance energy levels and alleviate work-related exhaustion [28]. However, conflicting evidence exists. For example, Safiye Ozvurmaz et al. [29] found that older nurses experienced higher work-related fatigue. This discrepancy may be due to differences in the fatigue assessment tools used across studies. Furthermore, other studies have identified additional contributing factors to nurse fatigue. In Saudi Arabia, poor sleep quality and unhealthy eating habits were significantly associated with chronic fatigue among nurses [24], while in South Korea, fatigue levels were influenced by work schedule characteristics such as overtime hours and the number of night shifts [25]. These findings highlight the multifactorial nature of nurse fatigue and the need for context-specific interventions tailored to both individual and systemic factors.

Fatigue management in nursing should be addressed through a multi-level framework. This study focused primarily on individual coping strategies employed by nursing staff, including naps (64%), consumption of refreshing drinks (55%), concentration techniques (17%), exposure to bright lighting (16%), and regular exercise (13%). Notably, within the category of refreshing beverages, a culturally specific preference was observed: 23% of Chinese nurses reported consuming milk tea as a fatigue management strategy. While milk tea contains caffeine and tea polyphenols, its high sugar and trans fat content raises concerns regarding potential long-term health risks, such as obesity and cardiovascular disease [30, 31]. However, such personal strategies are often reactive and limited in their capacity to address the underlying causes of chronic fatigue. At the organizational level, systemic interventions—such as optimizing shift scheduling, ensuring adequate nurse staffing, providing appropriate rest facilities, and fostering a supportive and ethical work environment—are essential to achieving sustainable fatigue mitigation [32, 33]. Therefore, future research should investigate comprehensive fatigue management programs that integrate organizational-level interventions to effectively enhance nurse well-being.

Limitation

Despite its valuable insights, this study has several limitations. It relied solely on the OFER questionnaire, which, although validated, may not fully capture the complexity of nurse fatigue. Future research should include objective measures (e.g., sleep tracking, physiological indicators) and workplace factors (e.g., shift length, lighting) to provide a more comprehensive understanding. Second, as the study relies solely on self-reported data, there is a potential for response bias, with participants possibly underreporting fatigue or overestimating their recovery due to professional expectations. Future research should consider incorporating objective measures (e.g., sleep monitoring) or qualitative methods (e.g., interviews) to enhance data accuracy and depth. Third, our study was conducted in a specific cultural and professional context—among surgical nurses in Zhejiang Province, China, where workplace norms, rest practices, and professional culture may differ substantially from those in other countries. Future research should consider these contextual and institutional variables to better understand fatigue across diverse healthcare systems and cultural environments. Another limitation is the absence of formal adjustment for confounding variables, which may influence the observed associations. Future studies should apply multivariable analysis to better isolate independent predictors of fatigue.

Conclusion

Chinese night-shift nurses exhibit considerable fatigue, with chronic fatigue predominating over acute fatigue. Our analysis revealed that while acute fatigue was negatively correlated with education level, chronic fatigue was inversely associated with age, clinical experience, exercise frequency, and hospital grade. Although nurses commonly adopt personal strategies such as napping and consuming stimulant beverages to alleviate fatigue, these measures do not fully mitigate the prolonged impact of night shifts. Consequently, future research should prioritize comprehensive fatigue management programs that integrate both individual-level interventions and organizational-level strategies.