The study employed a cross-sectional study design. It is descriptive research that involves analyzing the information about a population at a specific point in time and also can be used to determine relationships between variables (Wang and Cheng, 2020). This method may limit generalizability due to potential sampling bias, as participants were not randomly selected from the broader population of nursing students on night shift internships.

In our study, convenience sampling method was used to recruit student nurses. The inclusion criteria were student nurses who have undergone a 40-week clinical practice from June 2023 to March 2024 in three university-affiliated Grade A general hospitals located in Shiyan City, Hubei Province, China. Grade A hospitals are classified as the highest hospital grade in China. The exclusion criteria are student nurses are those suffering from anxiety, depression, obsessive-compulsive disorder, and other mental disorders before clinical practice. Pre-existing mental disorders were medically confirmed by the mental health teacher in our research team. Student nurses who are suspended from clinical practice for over one month due to medical or personal reasons were also excluded. Initially, 210 students met the inclusion criteria and consented to participate in the study. Later, four students withdrew from the study due to illness or personal leave, and three students failed to complete the questionnaire. The final sample was 203 (96.7%). To assess potential bias, we compared the key demographic characteristics (e.g., age, gender, duration of clinical practice) of participants and non-participants. No significant differences were found between the two groups (p > 0.05), suggesting that sample was broadly representative and no response bias. Furthermore, the study’s aims and the voluntary nature of participation were clearly stated in the consent process to mitigate this concern.

We collected demographic information on participants’ age, gender, duration of clinical practice, and the frequency of their night shifts. Participants completed the tool independently without researcher supervision. We used the Chinese version of the Symptom Check-list 90 (SCL-90). The original SCL-90 was developed by Leonard Derogatis in mid-1970s, also known as Self-Reporting Inventory, and is considered one of the world’s most famous mental health test scales. SCL-90 consists of nine symptom dimensions including somatization, obsessive-compulsive, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation, and sychoticism, all of which reflect mental health conditions (Lanyon, 2007; Derogatis et al., 1973). The scale utilizes a 5-point Likert scale to assess the nine symptom factors from 1 (absent) to 5 (severe). A higher score for a symptom factor suggests a more pronounced issue related to the corresponding psychological symptoms. The higher the total score, the lower the overall level of mental health. Since the 1990s, Chinese researchers have utilized the SCL-90 to investigate and analyze the mental health of nurses. We also used the SCL-90 to compare the mental health status of our sample with the Chinese national norms obtained from a large-scale testing of the SCL-90 in the normal population in China (Wang, 1984).

In our study, the SCL-90 demonstrated good internal consistency in our study, with a total scale Cronbach’s alpha of 0.83. Subscale Cronbach’s alphas were as follows: Somatization (0.82), Obsessive-Compulsive (0.85), Interpersonal Sensitivity (0.84), Depression (0.88), Anxiety (0.83), Hostility (0.79), Phobic Anxiety (0.77), Paranoid Ideation (0.78), and Psychoticism (0.76). These values are consistent with the tool’s established reliability in Chinese populations (Song et al., 2020), further confirming its suitability for our sample.

Data collection was carried out over a four-week period beginning in March 2024 using the Symptom Checklist-90 (SCL-90) administered through an online questionnaire platform. The SCL-90 is a widely used self-report tool designed to assess psychological distress across nine symptom dimensions. Ethical approval for the study was obtained from the Science and Technology Ethics Committee of Hubei University of Medicine (Reference Number: 2024-RE-019). Participants received a written information sheet outlining the study purpose, procedures, and their rights, including voluntary participation and the option to withdraw at any time without penalty. Informed consent was implied upon the submission of the completed online questionnaire, which was distributed via an anonymized mobile survey link. To ensure confidentiality, no personal identifiers or IP addresses were collected, and all data were stored in a password-protected repository accessible only to the research team. Data were reviewed for completeness before analysis, and security measures were implemented to maintain anonymity, integrity, and secure handling of all responses.

Survey data were entered into Statistical Package for Social Science (SPSS) version 26.0. Descriptive statistics (mean, standard deviation) were calculated. Independent t-test was used to examine difference in mental health status between our sample and Chinese mental health national norms. The normality of the data was assessed prior to the independent t-test. The results indicated that all key variables (night shift frequency and SCL-90 total/subscale scores) followed a normal distribution (Shapiro–Wilk W = 0.97–0.99, p > 0.05), supporting the use of parametric statistical methods. Spearman correlation was used to determine the association between SCL-90 and frequency of night shifts.

A total of 210 undergraduate nursing students consented to participate in this study but only 203 (96.7%) questionnaires were valid for final data analysis. The mean age was 22 ± 1.54 years, the duration of their clinical practice was 8.25 ± 1.15 months, and the frequency of night shift was 1–2 nights a week. Demographic characteristics (e.g., age, gender, duration of clinical practice) of nursing students showed no statistically significant differences (p > 0.05). The results indicated that while male students had slightly lower scores than females on the obsessive-compulsive, depression, anxiety, and psychoticism factors, but no statistically significant differences.

Nursing students who work night shifts exhibited elevated SCL-90 scores across all dimensions, surpassing the national average for China, reporting moderate symptom distress. The results of the t-test showed statistically significant differences in the symptomatology factor scores of somatization, obsessive-compulsive symptoms, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation and psychoticism (p < 0.05). The levels of somatization, obsessive-compulsive symptoms, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation, and psychoticism among nursing students working night shifts showed significant severity compared to the national average of Chinese mental health national norms. The details are shown in Table 1.

The correlation between night shift frequency and SCL-90 total scores was positively correlated [r = 0.335, p < 0.01, 95% CI (0.16, 0.46)]. Correlation analysis demonstrated significant positive correlations (p < 0.01) of night shift frequency with somatization (0.281), obsessive––compulsive symptoms, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation and psychoticism (p < 0.05). The levels of somatization, obsessive-compulsive symptoms, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation, and psychoticism among nursing students working night shifts showed significant severity compared to the national average of Chinese mental health national norms. The details are shown in Table 2.

This is the first study that assessed the impact of working night shifts on mental health of undergraduate nursing students as part of the clinical placement experiences. However, our study have some limitations. First, the study employed a cross-sectional study and convenience sampling in one geographic region of China. This method may limit generalizability due to regional sample and also cannot establish a true cause-and-effect relationship. Second, when using self-report data, nursing students may have underreported psychological distress due to social desirability bias or over-reported symptoms to seek support, which could introduce inaccuracies in the data. Third, athough the study provided us some understanding of the mental health status of nursing students, more research with increased sample size and additional survey questionnaires (e.g., resilience) are needed to better correlate with the SCL-90. A mixed-methods design can be used in future research to explore the strategies to support nursing students’ psychological wellbeing on shift duties.

The correlation between night shift frequency and the decline in psychological well-being among Chinese nursing students underscores the need for changes in clinical practice. Hospitals and healthcare institutions should implement structured scheduling policies that prioritize the mental health of student nurses. This includes adhering to a recommended minimum interval of 3–4 days between night shifts and limiting weekly night shift duration to no more than 8 h, as supported by evidence indicating that such measures help preserve sleep quality and reduce circadian rhythm disruption (Wyse et al., 2017). In addition, clinical supervisors and hospital staff should receive training to recognize signs of mental fatigue and emotional distress among nursing students (Postma et al., 2017). Continuous, on-site psychological support services should also be made accessible to help students process stress and avoid emotional burnout (Segura, 2024).

Further research is necessary to explore mediating and moderating factors. Of nights shifts among nursing students. Future studies to investigate how individual differences—such as coping style, resilience, or social support—affect how nursing students respond to night shift demands. Longitudinal research tracking students from the academic setting into early career stages could also provide insights into the long-term psychological effects of night shifts during training. Additionally, intervention-based studies are needed to test the efficacy of various support mechanisms—such as peer mentoring programs, mindfulness training, or flexible scheduling—in reducing negative mental health outcomes. Such research will help establish evidence-based guidelines that are specifically tailored to the Chinese nursing education context.

Nursing education programs should proactively equip students with skills to manage the psychological demands of night shifts. Integrating mental health literacy and self-regulation strategies into the curriculum, training in positive psychological techniques can empower students to recognize, accept, and adapt to emotional challenges (Dobrowolska et al., 2020). Educators and clinical teachers should also maintain open, consistent communication with students throughout their clinical placements, offering timely guidance and emotional support can help students navigate difficulties encountered during night shifts, in line with recommendations from the World Health Organization (2022). Ultimately, a well-rounded education that emphasizes both clinical competence and psychological preparedness is essential for sustaining the mental well-being of future nurses.