The sample size calculator can be freely accessed at www.raosoft.com/samplesize.html. A total of 282 subjects from three secondary vocational schools in Anhui Province of China were selected as the objects of investigation by using the cluster sampling method. After obtaining informed consent from the subjects, or their guadians the participants were tested in a group using unified guidance language, and the questionnaires were uniformly collected. A total of 281 (99.65%) valid questionnaires were collected. After eliminating unusable ones (such as answers with a missing rate of over 50%, incomplete information or regular answers), 267 valid questionnaires were retained, with a valid rate of 94.68%. The students’ average age was 16.35 years (SD = 1.58), ranging from 14 to 20 years. Among them, 128 were male students, accounting for 47.94%; 157 students were from the rural area, accounting for 58.80%; and 124 students had good family relationship, accounting for 46.44% of the total.

The socio-demographic information collected in this study included age, gender, grade, birthplace (urban vs. rural), and family relation (good vs. bad).

The structured questionnaire consisted of three separate scales developed or modified by local researchers in China and were suitable for assessing the subjects of this study.

The general self-efficacy scale (GSES) was developed by Ralf Schwarzer, and it was later revised and adopted to Chinese culture by Wang (28). It was used to check the overall self-evaluation of secondary vocational students (29). The scale contains 10 items, such as “I can always solve problems if I try my best. ” It uses Likert’s four-point scoring method, with “1” denoting “not at all true,” “2” denoting “somewhat incorrect,” “3” denoting “mostly true,” and “4” denoting “exactly true.” A higher score implied higher self-efficacy. The value of Cronbach’s α of this scale was.88. The prediction validity of GSES was tested by using anxiety as criterion. There was a significant negative correlation between GSES and trait anxiety, state anxiety and test anxiety (TAS), and the correlation coefficients were -.301,.422 and.253, respectively.

The emotional intelligence scale (EIS) was developed by Schutte et al. in 1988 and later translated and revised by Liu (30). This scale has been widely used in China (31, 32) and consists of 21 items, such as “I can always solve problems if I try my best,” and four dimensions, namely regulation of perceived emotions, self-emotion management, others’ emotion management, and emotion application. Likert’s five-point scoring method was adopted, with “1” representing “strongly disagree” and “5” representing “strongly agree.” A higher score implied a higher level of emotional intelligence. The value of Cronbach’s α coefficient of this scale was.92. The pairwise correlation among the factors was significant, and the correlation coefficient was between .294 and .462, which was a low to moderate positive correlation. The correlation coefficient between the factors and the total score was ranging from .616 to .800, which denote strong positive correlation, indicating that each factor was consistent with the overall concept.

The Resilience Scale of Adolescents (RS) developed by Hu and Gan (33) was used in this study (33). This scale has been widely used in China (34) and comprises a total of 27 items, such as “My life has a clear purpose, “ and 5 dimensions, including goal concentration, emotional control, positive cognition, family support, and interpersonal assistance (34). It uses Likert’s five-point scoring method, with 1 indicating completely inconsistent, 2 indicating inconsistent, 3 indicating not sure, 4 indicating consistent, and 5 indicating completely consistent. A higher score implied a higher level of resilience. The internal consistency coefficient of the scale was .88, and the internal consistency coefficient of the subscale was ranging from.69 -.83. The pairwise correlation among the factors was significant, and the correlation coefficient was between.12 and.56, which was a low to moderate positive correlation. The correlation coefficient between the factors and the total score was ranging from.54 to.73, which was medium to high positive correlation, indicating that each factor was consistent with the overall concept.

SPSS26.0 and macro PROCESS were used for data processing and analysis. Descriptive statistical analysis, independent sample t test, Pearson correlation analysis, regression analysis, and mediation effect tests were the statistical methods used in this study.

Before the analysis, all data were tested for normality and were found to fulfill the criteria. The skewness coefficient method was used to test whether the scores obtained show normal distribution (35). The skewness values obtained for different scales used in this study were -.445 for the “General Self-efficacy Scale”, “-.728” for the “Emotional Intelligence Scale,” and “.365” for the “Resilience Scale of Adolescents.” The normally distributed data are expressed as the mean ± standard deviation, and the numerical data are expressed as n.

Following the recommendations of Williams and McGonagle (36), Harman’s single-factor test was used for determining the common method variance bias. Variance was found to be less than the threshold of <25%, indicating that common method variance was not present (36).

The scores of self-efficacy, emotional intelligence, and resilience of Chinese secondary vocational students were above the average level. The total score of resilience and emotional intelligence did not differ between the male and female students. The self-efficacy score of boys was significantly higher than that of girls (t = 2.77, p < 0.01). The scores of self-efficacy (t = -2.80, p < 0.01) and resilience (t = -3.48, p < 0.01) of urban students were significantly higher than those of students from rural areas. In addition, the total scores of resilience (t = 3.12, p < 0.01) and self-efficacy (t = 4.38, p < 0.001) of secondary vocational students with different family relationships differed significantly ( Table 1 ).

As shown in Table 2 , Pearson’s product difference analysis was conducted between self-efficacy, emotional intelligence, and resilience of secondary vocational students. The result confirmed hypothesis 1 and revealed an obvious correlation among the three variables (p < 0.01).

Regression analysis was used to test whether emotional intelligence has a mediating effect. Three models were used to analyze the mediating effect: Model 1, regression analysis of the independent variable (X) and the dependent variable (Y); Model 2, regression analysis of the independent variable (X) and the mediating variable (M); Model 3, regression analysis of the independent variable (X), mediating variable (M), and dependent variable (Y). It was assumed that if X affects Y by affecting M, then M is the mediating variable. Self-efficacy was considered as the independent variable (X), level of resilience was the dependent variable (Y), and emotional intelligence ability was assumed to be the intermediary variable (M). The regression analysis was performed, and the results are shown in Table 3 .

Self-efficacy had a significant predictive effect on resilience and confirmed hypothesis 2 (β = .932, t = 7.168, p < 0.001), and this result was true even after addition of the intermediary variable emotional intelligence (β = .602, t = 4.035, p < 0.001). Self-efficacy was a significant predictor of emotional intelligence (β = .426, t = 7.250, p < 0.001), and emotional intelligence was a significant predictor of resilience (β =. 281, t = 4.162, p < 0.001). The confidence intervals were estimated then by Bootstrap method with deviation correction. The results showed that 95% confidence intervals did not contain 0, indicating that the mediating effect was significant, which validated Hypothesis 3. Self-efficacy of secondary vocational students can directly predict resilience. Resilience can also be affected through the mediating effect of emotional intelligence, and the proportion of intermediary effect was 16.59 %. According to the test results, the intermediary role model was constructed in this study, as shown in Figure 1 .

The self-efficacy of secondary vocational students was above the medium level, which is consistent with the findings of previous studies (12, 29). Compared with junior high school students, learning pressure among secondary vocational students is significantly low. Practical ability and employment-oriented learning content can mobilize students' learning enthusiasm, and therefore, secondary vocational students' learning interest was found to be significantly improved. All these factors contribute to the improvement of secondary vocational students' sense of self-efficacy.

The emotional intelligence of secondary vocational students was above the medium level. This result is in close agreement with that of a previous study conducted by Liu (29). Studies have shown that a variety of internal protective factors (such as emotional control ability and self-efficacy) and external environmental factors (such as relatives and peers) may affect the level of resilience of individuals (37). Moreover, the resilience of secondary vocational students was above the medium level, which is consistent with previous research (29, 38). Secondary vocational students are shunted to vocational schools after graduation from junior high school, and they may face more challenges in life (39). Having faced examinations such as the senior high school entrance examination and various setbacks in life, along with the accumulated personal experience and improved environmental adaptability, secondary vocational students tend to exhibit significantly higher levels of resilience

We also found that the level of resilience of secondary vocational students with good family relationships was significantly higher than that of secondary vocational students with bad family relationships, which is consistent with some previous research results (6). Family is the first and most important place for individuals’ growth, and therefore, family environment and atmosphere play a crucial role in cultivating an individual’s resilience. A good family relationship can enable secondary vocational students to obtain safety and love.

This study provides evidence that higher levels of general self-efficacy predict higher levels of resilience, which is consistent with previous research findings (40, 41). Specifically, based on the results of previous studies and this study on secondary vocational school students, we determined that self-efficacy has a positive impact on the resilience of secondary vocational school students. Students with high levels of self-efficacy tend to be confident about their abilities and resources for overcoming challenges (23) and tend to develop different resilient behavioral responses to cope with stress and other negative experiences (40).

Research suggests that self-efficacy was positively correlated with emotional intelligence of secondary vocational school students, indicating its role as an important internal driving factor for promoting emotional intelligence of secondary vocational school students. This is in accordance with the results of previous studies (29, 40), which verified that a high level of self-efficacy could enhance students’ ability to manage emotions and deal with stress. Higher levels of self-efficacy implied higher levels of emotional intelligence of secondary vocational school students. Strengthening self-efficacy and emotional intelligence can improve the learning outcomes of vocational education students (40).

We also determined the impact of emotional intelligence on the resilience of secondary vocational students. Secondary vocational students with high emotional intelligence tend to be confident and adopt a positive coping style when dealing with stressful life events, implying that they tend to be more resilient in life (40).

Interestingly, this study revealed that emotional intelligence serves as a partial mediating factor for the influence of self-efficacy on secondary vocational students’ resilience. These results confirm that self-efficacy influences secondary vocational school students’ resilience not only directly but also indirectly through emotional intelligence. Therefore, interventions that improve emotional intelligence as a strategy to enhance self-efficacy for promoting resilience are needed. The present study results also indicate that emotional intelligence plays an important role in enhancing secondary vocational students’ resilience, in agreement with the results of previous studies. Liu (2019) conducted a study on emotional intelligence and resilience of secondary vocational students and determined that there was a significant correlation between the two variables (29). Armstrong et al. studied the relationship between emotional intelligence and resilience and observed a strong correlation between them (21). Therefore, promoting the level of psychological resilience of secondary vocational students by improving their self-efficacy can be a promising strategy. Improving self-efficacy can also promote individuals’ emotional perception and positive regulation ability, thereby contributing to a positive change and enhancing resilience among secondary vocational students.

The results of this study highlight the necessity to design and implement intervention programs and active measures focused on self-efficacy and emotional intelligence, aiming to help secondary vocational school students to develop high resilience levels. In addition to daily learning activities, secondary vocational students should be encouraged to participate actively in outdoor activities, such as physical exercise, which can help them improve their self-confidence and self-efficacy, and further strengthen their psychological well-being (42). Administrators and teachers in secondary vocational schools should pay attention to cultivating the students' abilities, guide them to focus on their strengths, and strive to create a platform to display their talents. Finally, warm and friendly family atmosphere is a protective factor for the psychological development of adolescents. Family members should pay attention to the shaping of a good family environment in their daily life, which is conducive to the healthy development of secondary vocational school students.

Several limitations of this study should be noted. First, the number of participants in the study is small. Secondly, the cross-sectional method was used for data collection from participants at a single point in time. In future studies, we can consider using longitudinal research methods to explore the continuous relationship between these different variables. In addition, the formation of resilience is not only affected by individual factors, but also by external factors such as family and school. In the follow-up research, other external variables can be included to achieve a deeper understanding of the development of psychological resilience of secondary vocational students.