Introduction
As a unique group of college students, nursing students shoulder the duty of saving lives and healing the wounded. They face the pressure of learning theoretical knowledge and professional skills. In addition, students suffer from the pressure of clinical training experiences, which often produce psychological problems, among which depression and anxiety are the most important manifestations [1]. Previous studies have confirmed the high rate of depression and anxiety among nursing students [2‐4]. As one example, in Los Angeles, the rates of depression and anxiety reached 30% and 38%, respectively [5]. The incidence among Chinese nursing students were as high as 28.7% and 41.7%, respectively [6].
Past results have shown that nursing students have significantly higher rates of depression and anxiety compared to other general students of the same age group [7]. Depression and anxiety in nursing students can contribute to poor health. This can have an impact on healthcare recipients, for example, it can contribute to poor communication and treatment engagement, resulting in poor quality patient care [4]. In published studies anxiety has been studied less than depression among nursing students. Anxiety, though as common as depression, is often overlooked. Furthermore, apart from the overwhelming sensations of fright or distress, anxiety has the capacity to diminish the ability to focus on objectives, sustain mental effort, and coordinate bodily movements [8], these are all crucial for nursing students to deliver secure and efficient healthcare to individuals. Consequently, it becomes imperative to recognize the variables that impact manifestations of melancholy as well as anxious tendencies and investigate the plausible mechanisms behind these factors of depression and anxiety.
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Negative life events (NLEs) can add to the chances of developing mental health problems such as depression and anxiety [9]. Research has found that nursing students often suffer from depression, and other psychological problems after experiencing family trauma, academic pressure, and other negative life events [10]. A longitudinal study of anxiety treatment found that the more NLEs a person encountered, the worse their anxiety outcomes [11]. Another study established that the more NLEs a person experienced, the more prone they were to depression and anxiety [12]. Several studies have explored the potential mechanisms connecting NLEs with depression and anxiety [13, 14]. Some results suggest that resilience plays a partial mediating role [15], but this work mainly focuses on adolescents or general college students, and nursing students have rarely been studied.
Resilience is a protective factor, and individuals with high resilience can typically bounce back from significant challenges or health issues and return to their normal functioning. In other words, individuals with greater resilience possess a stronger capacity for recovery and face a reduced risk of illness [16]. Cultivating resilience is considered an effective way to thwarting the occurrence of mental health disorders and enhancing overall mental well-being [17]. A study of Chinese adolescents found that resilience as a mediating variable in the impact of NLEs on depression [15]. However, there are no empirical studies to confirm the mediation effect of resilience in the influence of NLEs on anxiety. Furthermore, most previous studies focused on adolescents, lacking a focus on the unique characteristics of nursing students. At the same time, we also consider gender as an important factor in our study. Male nursing students, as a minority group in nursing training and the profession, often face negative impacts that female nursing students have not experienced, including low self-esteem, anxiety, and depression [18].
There are significant differences in depression and anxiety between males and females [19]. In most reports, females have higher rates of major depression and anxiety disorders than males. On average, the ratio is 2:1 [20]. Studies have shown that the hormone levels of females fluctuate periodically on a larger scale than those of males, and repeated estrogen discontinuation interferes with glucocorticoid release, making females more susceptible to feel stress, which increases the chances of anxiety and depression [21]. Research has demonstrated that the path of loneliness predicting depression was moderated by gender [22]. In addition, another study has explored the impact of gender in terms of its moderation on the relationships between paternal authoritative parenting and self-efficacy in adolescents [23]. However, there is very little literature that has investigated the moderation effect of gender in the path of NLEs predicting depression and anxiety among nursing students.
College students often have sleep problems, with about half of them not sleeping well [24]. Among nursing students, the situation is even worse, with 71% not sleeping well [25]. Research has confirmed that sleep quality is related to mental health [26]. Zhang et al. found that sleep quality was an important factor leading to depression and anxiety [27]. Additionally, there was a strong correlation of sleep quality with NLEs and resilience [28, 29]. To eliminate sleep quality from interfering with the results, we used sleep quality as a control variable in all analyses.
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Present study
In summary, NLEs, resilience, gender, and sleep quality were all significantly associated with depression and anxiety. However, prior research has not explored the intricate connection between these variables and their potential roles as mediators and moderators. Thus, this investigation examines the mediation effect of resilience and the moderation effect of gender through a moderated mediation model. We propose a hypothesis: Resilience might act as a mediating variable in the path of NLEs predicting depression and anxiety among nursing students. In addition, gender may act as a moderating variable in the direct and mediated paths.
Methods
Sample
We studied a sample of nursing students enrolled in traditional nursing programs. The discipline-based curriculum system dominates nursing education in China. The curriculum mainly includes public foundation courses, basic medical courses, and nursing and clinical practices [30].
The sample size was calculated using G*Power [31]. The parameters were : effect size f2 = 0.15; α = 0.05; power (1 − β) = 0.95; number of tested predictors = 10; and total number of predictors = 10. Based on this power analysis, a sample size of 172 participants was determined to be required. The inclusion criteria include full-time nursing students from year 1 to year 4 (including students with anxiety and depression diagnoses), as well as web access. The exclusion criteria include part-time undergraduate students. A total of 568 participants were recruited by convenience sampling. The questionnaire link was distributed to nursing undergraduate students via WeChat. The detailed recruitment process can be found in this article [32]. The consent form is attached at the beginning of each questionnaire. Participants’ privacy and voluntary participation were ensured.
Measurements
Socio-demographics information
Data on age, gender, and year of training were collected in this study. Age was categorized as ≤ 20 and > 20. Grade was classified as year 1, year 2, year 3, and year 4.
Depression symptoms
The Patient Health Questionnaire-9 (PHQ-9) developed by Kroenke et al. [33] was used to assess depression symptoms. Specifically, the revised Chinese version was used in this study. Nine items are responded to on Likert-type scales, ranging from 0 to 3, with 0 representing “not at all” and 3 representing “nearly every day”. Higher scores represent higher levels of depression symptoms. Cronbach’s alpha was 0.933 in the present study. In a confirmatory factor analysis (CFA), we found that our scale model exhibited good fit: X2/df = 3.01, RMSEA = 0.06, NFI = 0.98, CFI = 0.99, and TLI = 098.
Anxiety symptoms
This study adpoted the Chinese version of the Generalized Anxiety Disorder Scale (GAD-7) revised by He Xiaoyan [34]. The GAD-7 has a total of 7 items, ranging from 0 to 3, with 0 representing “not at all” and 3 representing " nearly every day”. With higher scores indicating higher anxiety symptoms. Cronbach’s alpha was 0.949, and CFA revealed an acceptable fit of the scale model: X2/df = 1.69, RMSEA = 0.03, NFI = 0.99, CFI = 0.99, and TLI = 0.99.
Resilience
The Chinese version of the10-item Connor-Davidson Resilience Scale (10-item CD-RISC), which was revised by Ye Zengjie [35], was used in this study. The scale has 10 items with a 4-point range from 1 representing “never” to 4 representing “always”. Higher scores indicate higher resilience. Cronbach’s alpha was 0.948. CFA showed an acceptable fit of the scale model: X2/df = 1.89, RMSEA = 0.04, NFI = 0.98, CFI = 0.99, and TLI = 0.99.
Negative life events
Sawyer et al. defined adolescence as ages 10–24 [36]. This study adopted the Chinese version of the Adolescent Life Events Self-Rating Scale (ASLEC) revised by Liu Xianchen et al. [37]. This scale has 27 items with a 5-point range from 1 indicating “no influence” to 5 indicating “extremely severe influence”. The total score reflects the magnitude of impact caused by these negative events, with higher scores meaning higher impact. Cronbach’s alpha was 0.967. CFA showed that the scale model exhibited good fit: X2/df = 5.37, RMSEA = 0.08, NFI = 0.90, CFI = 0.92, and TLI = 0.89.
Sleep quality
The Chinese version of the Pittsburgh Sleep Quality Index (PSQI) revised by Liu Xianchen et al. [38] was used in this study. There are 18 items, each item was responded to on a 4-point scale where 0 indicates “not during the past month” and 3 indicates “three or more times week”. The total PSQI score was equal to the sum of all items, and higher scores indicate worse sleep quality. Cronbach’s alpha was 0.742. CFA revealed an acceptable fit of the scale model: X2/df = 2.41, RMSEA = 0.05, NFI = 0.98, CFI = 0.99, and TLI = 0.97.
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Control variables
As Pearson correlation results showed that sleep quality was related with other variables (see Table 1), we decided to eliminate sleep quality from interfering with the results and we used it as a control variable in all analyses.
Table 1
Descriptive statistics and bivariate correlations among depression, anxiety, resilience, and NLEs (N = 568)
M ± SD | 1 | 2 | 3 | 4 | 5 | |
|---|---|---|---|---|---|---|
1.Depression | 8.16 ± 5.458 | - | ||||
2.Anxiety | 5.06 ± 4.290 | 0.590** | - | |||
3.NLEs | 35.31 ± 25.741 | 0.376** | 0.454** | - | ||
4.Resilience | 25.74 ± 6.221 | -0.268** | -0.289** | -0.191** | - | |
5.Sleep quality | 4.68 ± 2.898 | 0.396** | 0.479** | 0.351** | -0.231** | - |
Statistical analysis
Age was missing for eight participants, and the expectation-maximization method was used to estimate the 8 missing values. Descriptive analyses, independent t-test and one-way analysis of variance (ANOVA) were calculated for describing sociodemographic characteristics and comparing the distribution of depressive and anxiety symptoms. The correlations of study variables (depression, anxiety, resilience, and NLEs) were analyzed by Pearson correlation analyses. The SPSS PROCESS macro was used for mediation and moderated mediation analysis. In addition, 95% confidence intervals were calculated using the bias-corrected bootstrapping method with 5000 samples.
Ethics approval and consent to participate
The Ethics Committee of Nantong University approved the investigation (2019017/202021). The informed consent for the survey was obtained from all participants.
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Result
Descriptive statistics and correlation for all variables
A collection of 568 survey responses was analyzed in the current study, and socio-demographics of sample are shown in Table 2. Mean age was 20.59 years (SD = 1.33) and the gender distribution was 70 males (12.3%) and 498 females (87.7%). First-year students had the smallest number, accounting for 19.2% of the participants; Second-year students had the largest number of students, accounting for 33.8% of the participants. The average scores of PHQ-9 and GAD-7 in females were 8 (SD = 5.28) and 4.94 (SD = 4.20), lower than that of males were 9.30 (SD = 6.49) and 5.90 (SD = 4.83). No statistically significant age, gender, or year of school differences were observed in depression or anxiety symptoms.
Table 2
Descriptive statistics for sociodemographic characteristics (N = 568)
n(%) | Depression | Anxiety | |
|---|---|---|---|
(M ± SD) | (M ± SD) | ||
Gender | |||
Male | 70(12.3%) | 9.30 ± 6.49 | 5.90 ± 4.83 |
Female | 498(87.7%) | 8.00 ± 5.28 | 4.94 ± 4.20 |
t | 1.873 | 1.757 | |
p | 0.062 | 0.079 | |
Age (mean 20.59, SD 1.33 ) | |||
≤ 20 | 287(50.5%) | 8.42 ± 5.41 | 5.23 ± 4.37 |
> 20 | 281(49.5%) | 7.89 ± 5.50 | 4.88 ± 4.21 |
t | 1.162 | 0.965 | |
p | 0.246 | 0.335 | |
Grade | |||
1st year | 109(19.2%) | 8.96 ± 5.87 | 5.41 ± 4.44 |
2nd year | 192(33.8%) | 8.11 ± 5.08 | 4.69 ± 4.16 |
3rd year | 152(26.8%) | 8.02 ± 5.53 | 5.19 ± 4.49 |
4th year | 115(20.2%) | 7.66 ± 5.59 | 5.17 ± 4.10 |
F | 1.148 | 0.798 | |
p | 0.329 | 0.495 |
The average value, standard deviations, and Pearson correlation coefficient among the variables can be seen in Table 1. The results indicated that NLEs positively related to depression (r = 0.376, p < 0.01), anxiety (r = 0.454, p < 0.01), and poor sleep quality (r = 0.351, p < 0.01). NLEs were significantly negatively associated with resilience (r = -0.191, p < 0.01). Resilience was negatively associated with depression symptoms (r = -0.268, p < 0.01), anxiety symptoms (r = -0.289, p < 0.01), NLEs (r = -0.191, p < 0.01), and poor sleep quality (r = -0.231, p < 0.01). In addition, poor sleep quality significantly positively related to depression (r = 0.396, p < 0.01) and anxiety (r = 0.479, p < 0.01) symptoms.
Mediating role of resilience
The analysis of the mediation model, as depicted in Fig. 1, was completed using SPSS PROCESS Model 4. Table 3 displays the significance and respective path coefficients for each relationship. In this regression analysis, depression was the dependent variable. The findings revealed that NLEs significantly predicted depression (B = 0.270, p < 0.001). Upon introducing resilience as a mediating variable, the positive prediction of NLEs on depression continued to maintain its significance (B = 0.251, p < 0.001). NLEs demonstrated a significantly inverse prediction of resilience (B = -0.125, p < 0.001). Resilience significantly negatively predicted depression (B = -0.158, p < 0.001). It was established that the partial mediation effect of resilience, NLEs significantly predicted depression symptoms through the indirect path of resilience (B = 0.02, 95% CI [0.004, 0.041]).
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Table 3
Mediation analysis (N = 568)
Outcome | Variable | Path c | Path c’and b | Path a | Path a*b | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
B | SE | B | SE | B | SE | B | SE | LLCL | ULCL | ||
Depression | NLEs | 0.270*** | 0.040 | 0.251*** | 0.039 | - | - | 0.020 | 0.009 | 0.004 | 0.041 |
Resilience | - | - | -0.158*** | 0.038 | -0.125*** | 0.043 | |||||
R² | 0.221 | 0.244 | 0.067 | ||||||||
F | 80.066 | 60.671 | 20.347 | ||||||||
Anxiety | NLEs | 0.326*** | 0.037 | 0.307*** | 0.037 | - | - | 0.019 | 0.009 | 0.004 | 0.040 |
Resilience | - | - | -0.153*** | 0.035 | -0.125*** | 0.043 | |||||
R² | 0.323 | 0.344 | 0.067 | ||||||||
F | 134.664 | 98.859 | 20.347 | ||||||||
Fig. 1
Conceptual mediation models of NLEs, resilience, and depression and anxiety symptoms
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Another regression analysis was conducted where anxiety was the dependent variable. NLEs significantly predicted anxiety (B = 0.326, p < 0.001). Upon introducing resilience as a mediating variable, the positive prediction of NLEs on anxiety continued to maintain its significance (B = 0.307, p < 0.001). Notably, NLEs exhibited a significantly inverse prediction of resilience (B = -0.125, p < 0.001). Moreover, resilience significantly negatively predicted anxiety (B = -0.153, p < 0.001). These findings supported that NLEs significantly positively predicted anxiety through the indirect path of resilience(B = 0.019, 95% CI [0.004, 0.040]).
Moderating role of gender
The analysis of the moderated mediation model, as depicted in Fig. 2, was performed using SPSS PROCESS Model 59. Table 4 displays the significance and respective path coefficients for each relationship. In this regression analysis, depression was the dependent variable. Moderated mediation analyses displayed that gender did not moderate the direct (NLEs * gender: B = -0.020; 95%CI: -0.060, 0.020) and indirect paths within the moderated mediation model (NLEs→ resilience: B = -0.025, 95% CI: -0.074, 0.024; resilience→ depression: B = -0.129, 95% CI: -0.312, 0.054 ).
Table 4
Moderated mediation analysis (N = 568)
Outcome | Variable | B | SE | t | LLCI | ULCI |
|---|---|---|---|---|---|---|
Depression | NLEs | 0.051 | 0.009 | 5.957*** | 0.034 | 0.068 |
Resilience | -0.145 | 0.034 | -4.315*** | -0.211 | -0.079 | |
Gender | -0.070 | 0.658 | -0.106 | -1.362 | 1.222 | |
NLEs*Gender | -0.020 | 0.020 | -0.983 | -0.060 | 0.020 | |
Resilience*Gender | -0.129 | 0.093 | -1.384 | -0.312 | 0.054 | |
Anxiety | NLEs | 0.049 | 0.006 | 7.827*** | 0.037 | 0.061 |
Resilience | -0.108 | 0.025 | -4.400*** | -0.157 | -0.060 | |
Gender | 0.272 | 0.481 | 0.566 | -0.672 | 1.217 | |
NLEs*Gender | -0.031 | 0.015 | -2.120* | -0.060 | -0.002 | |
Resilience*Gender | -0.021 | 0.068 | -0.311 | -0.155 | 0.113 |
Fig. 2
Conceptual moderated mediation model of gender, NLEs, resilience, and depression and anxiety symptoms
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Another regression analysis examined anxiety was the dependent variable. Gender did not moderate in the indirect path of the mediation model (NLEs→resilience: B = -0.025, 95% CI: -0.074, 0.024; resilience →anxiety: B = -0.021, 95% CI: -0.155, 0.113). The significant predictors of anxiety were the interaction terms between gender and NLEs (NLEs * gender: B = -0.031, 95% CI: -0.060, -0.002), showing that the impact of NLEs on anxiety was moderated by gender among the students. Figure 3 illustrates the final model of moderated mediation.
Fig. 3
The final moderated mediation model. (* p < 0.05; *** p < 0.001). All path coefficients are unstandardized B
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By analyzing the direct effects of NLEs on anxiety for each gender, we further examined the significant moderated mediation model. As shown in Fig. 4; Table 5, the point estimate for males between NLEs and anxiety was 0.076 (95%CI: 0.050, 0.103), and the point estimate for females was 0.045 (95%CI: 0.032, 0.058). Thus, the relationship between NLEs and anxiety was stronger for males than females.
Table 5
Conditional direct effects of NLEs on anxiety for males and females
B | SE | LLCI | ULCI | |
|---|---|---|---|---|
Male | 0.076 | 0.013 | 0.050 | 0.103 |
Female | 0.045 | 0.007 | 0.032 | 0.058 |
Fig. 4
Simple slope analysis for testing the moderating effect of gender on the relationship between NLEs and anxiety
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Discussion
This study explored the relationship among NLEs, resilience, and symptoms of depression and anxiety in nursing students from China. Our findings indicated that resilience has a mediating role in the impact of NLEs on depression and anxiety. A moderation effect of gender was observed regarding the direct link between NLEs and anxiety, such that, males showed a stronger relationship.
Our results revealed that NLEs had strong positive correlations with depression and anxiety symptoms among nursing students from China. The discovery aligns with prior investigations [12]. In our study, compared with students of other majors, nursing students are at a higher likelihood of encountering adverse life occurrences, including academic pressure and encounters with mortality in work settings. These negative events serve as crucial elements that increase the susceptibility to psychological well-being concerns, like distress, depression, and anxiety [9]. In addition, resilience has the potential to help individuals cope with depression and anxiety [39, 40]. The lower the resilience, the more likely you are to have mental health problems, and this has been widely confirmed in different populations, such as children, adolescents, adults, and the elderly [41‐43].
This current survey showed that resilience partially mediated associations between NLEs, depression, and anxiety among nursing students, which may reveal a potential mechanism for how NLEs might indirectly influence depression and anxiety symptoms. A recent integrative review confirmed resilience as an important mediating variable in the mental health of nursing students, amidst various other influencing factors [44]. As one example, researchers observed a mediation effect of resilience in the connection between clinically relevant stress, anxiety and depression symptoms in nursing students [45]. Liu et al. also provided strong evidence that resilience can serve as a mediating variable in the impact of NLEs on depression in Chinese middle and high school adolescents [15]. In our study, we have revealed that resilience is a key part of the mechanism by which NLEs contribute to poor mental health. Hence, further studies are necessary to explore effective methods to facilitate resilience. For example, facilitating attachment security through cultivating trait mindfulness may help to enhance resilience [46].
There is currently limited literature on the moderation effect of gender in research exploring the effect of NLEs on psychological health. We found that the impact of NLEs on anxiety was moderated by gender. The study of gender differences in mental health issues has been a longstanding research focus. Generally speaking, females are often more prone to psychological problems than males for two main reasons. Among the psychosocial factors analyzed, traits of masculinity (i.e., confidence, standing up for one’s beliefs, and individualism) may be reduce the occurrence of anxiety, while traits of femininity (i.e., being affectionate, compassionate, and sensitive to the needs of others) can be a risk factor [47]. In studies that consider biological factors, the influence of brain structure, genetic factors, and sex hormone fluctuation factors enhance female anxiety tendency [48]. In our moderated mediation model, gender was found to have a moderating effect on the direct impact of NLEs on anxiety, with males experiencing a greater impact. Gender differences in NLEs have been frequently reported in previous studies. Specifically, prior studies have consistently indicated that females are more likely to experience psychological well-being problems caused by negative events [49].
Our results may be different for two reasons. According to statistics, male nursing majors in Chinese universities account for only 13.7% of nursing students [50]. Also in our study, the number of male nursing students surveyed was 70, accounting for 12.3% of the study sample. As a minority group in the nursing profession, male nursing students may be psychologically sensitive to the opinions of others. In addition, under the traditional nursing concept, the general public has the stereotype that nursing is a profession dominated by females and that males should not pursue nursing [51]. The experience of male nursing students in the process of education is overwhelmingly negative, their professional choice may be laughed at and looked down on by relatives and friends, and told that pursuing a career in nursing is shameful for a man, and female patients may refuse to accept their care and nursing in future clinical work [52]. These biases and negative events can make male nursing students particularly susceptible to mental health problems as compared to female nursing students [53].
A recent study by Holden and O’Connell demonstrated that implementing an online mindfulness meditation intervention can improve depression and anxiety in nursing students [54]. In addition, a Turkish study showed that group psychoeducation can control anxiety and depression levels [55].Therefore, schools can set up mental health education courses, especially for male nursing students’ psychological health, counseling needs, and behavior training. Colleges and universities and the state need to strengthen social publicity and affirm males in the nursing profession [56].
Limitations and implications
Future studies should aim to address several limitations. First, longitudinal studies should be conducted to confirm the causal relationships among variables, as the current study was only a cross-sectional survey. Second, the study included a limited number of male nursing students, which may result in a lack of representativeness. To ensure accuracy, future research should consider including a larger sample size of males. Lastly, the present findings are limited to samples from three educational institutes in China. These samples cannot represent nursing students in the whole of China or even the world, future studies should aim to broaden the scope of this research.
Nevertheless, the results still have important practical significance. First of all, this study deviates from the norm by specifically targeting a unique subset of nursing students. Second, we identified resilience as a mediating variable in the relationship between NLEs and symptoms of depression and anxiety. It is therefore essential that health care providers develop interventions that promote resilience to reduce depression and anxiety in nursing students. Third, contrary to the view that women are more prone to psychological problems, male nursing students are more prone to anxiety in this research. It is important for parents and teachers to identify and intervene early in male nursing students’ mental health.
Conclusions
This study explored the relationship of NLEs, resilience, and gender with depression and anxiety among nursing students in China. The results indicated that resilience acted a mediator in the connection between NLEs with depression and anxiety symptoms. Additionally, gender was found to have a moderating effect on the direct impact of NLEs on anxiety, with males experiencing a greater impact. The findings suggest that interventions aimed at enhancing resilience could potentially alleviate depression and anxiety symptoms in nursing students, particularly among male individuals, who undergo adverse life events.
Acknowledgements
All the authors acknowledge each participant for their participation to the research.
Declarations
Ethics approval and consent to participate
The Ethics Committee of Nantong University approved the investigation (2019017/202021). The informed consent for the survey was obtained from all participants.
Consent for publication
Not Applicable.
Competing interests
The authors declare no competing interests.
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