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Article

School Climate and Self-Efficacy Relating to University Lecturers’ Positive Mental Health: A Mediator Model

by
Qin Lai
,
Bity Salwana Alias
* and
Aida Hanim A. Hamid
Faculty of Education, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia
*
Author to whom correspondence should be addressed.
Educ. Sci. 2025, 15(7), 852; https://doi.org/10.3390/educsci15070852
Submission received: 24 March 2025 / Revised: 14 June 2025 / Accepted: 23 June 2025 / Published: 3 July 2025
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Abstract

Rising workloads and institutional pressures in higher education threaten lecturers’ mental health, yet few studies explore how university climate and self-efficacy contribute to their positive mental health (PMH). This study employed a cross-sectional survey to investigate the mediating role of lecturers’ self-efficacy in the relationship between university climate and lecturers’ PMH. A total of 357 responses were collected from English major lecturers in Chinese higher education institutions through an online survey with convenience sampling. Data were collected via an online questionnaire using validated scales: the School Climate Inventory (SCI-5) for school climate, the General Self-Efficacy Scale (GSES) for self-efficacy, and the Positive Mental Health Scale (PMH) for mental health. The results indicated that all five dimensions of university climate—Collaboration (β = 0.122, p < 0.05), Student Relations (β = 0.163, p < 0.01), School Resources (β = 0.12, p < 0.05), Decision-Making (β = 0.11, p < 0.05), and Instructional Innovation (β = 0.325, p < 0.001)—positively influenced lecturers’ self-efficacy, with instructional innovation having the most significant impact. Moreover, self-efficacy significantly enhanced lecturers’ PMH (β = 0.27, p < 0.001) and partially mediated the relationship between university climate and lectures’ PMH (VAF = 20–80%). The findings highlighted the importance of fostering an innovative and supportive university climate while enhancing self-efficacy to promote faculty well-being. Future studies can further extend the results of this study through institutional and individual development strategies.

1. Introduction

To foster a more effective learning and development environment, educational policymakers should prioritize the mental well-being of both students and educators (Germain, 2024; Martin, 2010). Individuals with positive mental health (PMH), whether students or educators, manage challenges more effectively and demonstrate greater motivation and efficiency in learning (Bardach et al., 2022). However, the education system prioritizes student achievement over instructors’ well-being (Raju, 2024). In higher education, lecturers are often seen as facilitators of student success rather than individuals needing support (W. B. Johnson, 2015), leading to role standardization that hinders institutional growth. Faculty well-being significantly impacts higher education as mentally healthy lecturers deliver better instruction, adopt innovative teaching methods, and enhance student engagement while aligning with institutional goals. Lecturers at Chinese universities face strict professional standards as they are expected to meet teaching requirements while also contributing to scientific research efforts, taking on a dual set of responsibilities (Hammoudi Halat et al., 2023). A survey conducted by Renmin University of China revealed that over 80% of the university faculties had significant stress, with almost 30% suffering from severe job burnout (Li, 2005). Additionally, almost 90% of the instructors experienced some kind of job burnout, while close to 40% reported poor mental health (Li, 2005). Enhancing the PMH of Chinese college instructors has emerged as an urgent concern for institutions and society in this context.
A number of variables can influence university lecturers’ PMH, including personal factors, professional growth possibilities, work environment, workload and stress management, school culture, and leadership style (Aldridge & Fraser, 2016; Buskila & Chen-Levi, 2021; Collie et al., 2012). Among these factors, the school climate holds significant influence (Collie et al., 2012; Fathi & Derakhshan, 2019). Universities can improve lecturers’ mental health, motivation, and teaching effectiveness by fostering a positive school climate (Collie et al., 2012; Fathi & Derakhshan, 2019). Support from administrators enhances faculty self-esteem and belonging, while effective leadership boosts academic achievement and faculty value (Sila, 2023). Principals can promote well-being by managing relationships, creating a supportive environment, and showing genuine care (Buskila & Chen-Levi, 2021). Additionally, recognition from colleagues and students further enhances lecturers’ mental health (Garg et al., 2022). In addition, university faculties’ personal factors may also affect their PMH. One of the key factors is their self-efficacy (Kaqinari et al., 2022). Current research indicates that lecturers’ self-efficacy in higher education can be beneficial to their PMH (Chan et al., 2020; Kaqinari et al., 2022; Nabavi et al., 2017). High self-efficacy levels contribute to increased job satisfaction, reduced stress, and greater psychological resilience among educators (Kaqinari et al., 2022; Reilly et al., 2014). Additionally, self-efficacy is associated with lower levels of burnout, promoting overall well-being and effective teaching practices in the academic environment. Fathi and Derakhshan (2019) found that teacher self-efficacy had a stronger impact on teaching stress among Iranian EFL teachers, explaining 22.1% of the variance compared to emotional regulation’s 14.2%. In another study, Xiyun et al. (2022) tested a model of PMH among 276 Iranian EFL teachers, confirming self-efficacy as the strongest predictor of well-being. Similarly, Matos et al. (2022a) examined Brazilian lecturers and found that self-efficacy positively influenced quality of life and personal accomplishment while reducing burnout, further highlighting its role in faculty well-being.
It is worth mentioning that prior research has largely ignored the mediating role of lecturers’ self-efficacy in the relationship between school climate and lecturers’ PMH in higher education, limiting a comprehensive understanding of faculty well-being. This study aims to fill this gap by empirically examining whether self-efficacy mediates the relationship between school climate and PMH among English major lecturers in Chinese higher education institutions.

2. Literature Review

2.1. University-Level School Climate

The term “school climate” describes the general climate and personality of the school, including the relationships amongst students, teachers, administrators, and parents as well as the school’s culture, management style, academic climate, safety, and level of learning and personal growth promotion (Konishi et al., 2022). This definition highlights the influence of the institution’s internal environment on both students and staff, encompassing emotional and security aspects.
B. Johnson et al. (2007) claimed that school climate has five components, namely, collaboration, student relations, school resources, decision-making, and instructional innovation. Theirs is a commonly recognized definition, which is what this study uses. Collaboration involves the joint efforts by educators and the interaction between students and educators. It can promote the exchange of educational materials, establishes a supportive and cooperative environment, and improves classroom interaction and student engagement. Regarding student relationships, Lavy and Naama-Ghanayim (2020) emphasized the interconnectedness between student relationships and other aspects of the school climate, including the teacher–student relationship, school spirit, and sense of security. Establishing positive student relationships helps foster a supportive school culture, while poor student relationships tend to undermine the school climate. About school resources, Ahmadi et al. (2020) claimed that school participation is a student’s acceptance and identification of the school’s objectives and ideals as well as their sense of identity and belonging to school life.
Instructional innovation encourages the sharing of novel ideas and practices among instructors, fostering professional discussion and collaboration. It also contributes to the creation of a pleasant school environment. Additionally, it enhances teachers’ self-efficacy by encouraging them to study and experiment with new strategies. Ultimately, the implementation of a fair decision-making method enhances the overall satisfaction of the school and increases operational efficiency while also fostering a pleasant campus environment. Previous studies suggested that school climate greatly can enhance lecturers’ sense of belonging, efficacy, and pleasure by fostering lecturers’ collaboration, maximizing student relationships, assuring resource availability, promoting creativity in teaching, and adopting equitable decision-making (Ruiz, 2024; Thompson, 2018). In higher education, school climate has the ability to influence teaching faculties’ self-efficacy. The support provided by colleagues and administrators is vital for building the lecturers self-confidence (Dallı & Sezgin, 2022).
It should be noted that various aspects of the school climate might have varying impacts on lecturers’ self-efficacy. The innovative school climate promotes the use of inventive instructional approaches and may enhance the confidence and proficiency of university lecturers. An optimistic school climate characterized by support and collaboration can offer emotional support and improve their confidence in teaching (Azila-Gbettor & Abiemo, 2021). Prior research has examined the impact of several elements of the school climate on lecturers’ self-efficacy. For example, Aldridge and Fraser (2016) conducted a survey in 29 schools in western Australia, examining the correlation between school environment, teachers’ self-efficacy, and job happiness. They discovered that enhancing school climate can positively impact teachers’ self-efficacy and work satisfaction. Currently, there is a lack of empirical studies in the field of university-level school climate. Thus, to investigate the impact of the five elements of school climate on the self-efficacy among university lecturers, this study proposed the following:
H1. 
Collaboration has a positive effect on lecturers’ self-efficacy.
H2. 
Student Relations has a positive effect on lecturers’ self-efficacy.
H3. 
School Resources has a positive effect on lecturers’ self-efficacy.
H4. 
Decision-Making has a positive effect on lecturers’ self-efficacy.
H5. 
Instructional Innovation has a positive effect on lecturers’ self-efficacy.

2.2. Positive Mental Health

Positive mental health includes more than just the absence of mental diseases. It includes feelings of enjoyment, contentment, and a sense of purpose, as well as the capacity to bounce back from challenges, effectively handle stress, and adjust to changes. It is crucial for the educational process, regardless of whether it pertains to students, educators, or staff in administration. Previous research on positive mental health in education primarily explores the relationship between students’ mental health and academic achievement, focusing mainly on the students’ perspectives (Kaya & Erdem, 2021; Kiuru et al., 2020; Rand et al., 2020). These studies frequently investigate the impact of positive psychological characteristics, such as self-esteem, self-efficacy, and well-being, on students’ motivation, academic performance, and overall educational experience. For example, Atkins et al. (2010) conducted a survey in a school’s basic mental health service, specifically examining the integration of education and mental health in the school setting.
It Is worth noticing that the amount of research conducted on lecturers’ positive mental health in higher education is significantly lower compared to that of students. Prior research on the positive mental health of lecturers primarily concentrates on the topics of job burnout and job satisfaction (Castro et al., 2023; Matos et al., 2022a). These studies have examined the correlation between their job stress, emotional support, professional identity, mental health, teaching quality, and student success. For example, Castro et al. (2023) investigated burnout among lecturers in Portugal during the COVID-19 pandemic, finding that lower resilience, higher levels of depression and stress, and disrupted sleep patterns significantly contributed to personal and work-related burnout, highlighting the need for higher education institutions to implement support strategies to improve lecturers’ mental health and overall well-being. University lecturers’ positive mental health is shaped by various aspects, such as the work environment, relationships with colleagues, feedback from students, and possibilities for professional advancement (Matos et al., 2022a). It is important to note that the self-efficacy of instructors might impact their PMH. Prior research has suggested that the self-efficacy of university lecturers can serve as an indicator of their positive mental health and job burnout (Matos et al., 2022a). A strong sense of self-efficacy can not only boost teachers’ job happiness and resilience but also successfully reduce job burnout and enhance overall PMH.
Thus, this study proposed the following:
H6. 
Lecturers’ self-efficacy has a positive effect on their Positive Mental Health.

2.3. Lecturers’ Self-Efficacy

Self-efficacy, proposed from social cognitive theory by Bandura and Walters (1977), refers to an individual’s belief in their own skills and has a significant impact on various aspects of behavior (Bandura et al., 1999; Wood & Bandura, 1989). It can influence the setting of goals, the selection of surroundings that facilitate success, the level of effort exerted to attain goals, and even the physiological response to stressful events (Bandura et al., 1999). University lecturers‘ self-efficacy refers to a lecturer’s personal assessment of their competence in teaching, conducting research, fulfilling extension assignments, and managing activities at a level that meets the requirements of their institution (Matos et al., 2022b). Lecturers who possess a strong sense of self-efficacy are able to have confidence in themselves and exert a positive influence on their students’ performance. Furthermore, lecturers who have a strong sense of self-efficacy are more inclined to sustain a positive mental health. This positive emotion increases their educational passion and capacity for innovation, hence enhancing the quality of instruction and the learning experience of students.
Prior research has determined that the self-confidence and belief in their abilities of university lecturers are influenced by several aspects, such as the overall atmosphere of the institution, possibilities for professional growth, support from colleagues, and feedback from students (Hosford & O’Sullivan, 2016; Malinen & Savolainen, 2016). For instance, Fathan (2022) conducted a study in Pamulang University and found that the university academic climate could positively affect lecturers’ self-efficacy. Research from other educational stages (e.g., K12) also indicates the importance of school climate. Hosford and O’Sullivan (2016) conducted a study on teachers in conventional primary schools in Ireland and discovered that a supportive school environment can greatly enhance teachers’ efficacy in teaching, particularly when it comes to addressing behavioral issues among children in inclusive education. Malinen and Savolainen (2016) conducted a survey among junior middle school teachers in Finland, specifically examining variables such as school atmosphere, self-efficacy, and job satisfaction. The study revealed that a positive school atmosphere had a significant impact on teachers’ job satisfaction by enhancing their self-efficacy in behavior management.
In addition, previous research has demonstrated that the self-efficacy of university lecturers can impact various psychological processes, such as motivation (Saienko et al., 2020), positive and negative emotions (Burić et al., 2020), self-esteem (Ward, 2024), and mental health (Bandura et al., 1999; Wood & Bandura, 1989). Sezgin and Erdogan (2015) conducted a survey among primary school teachers to examine the influence of academic optimism, hope, and work enthusiasm on teachers’ self-efficacy. The study revealed a strong and positive correlation between academic optimism, hope, and work enthusiasm and lecturer’ self-efficacy. Burić et al. (2020) conducted a survey on 3010 teachers in Croatia, examining the correlation between teacher self-efficacy and teacher emotion. The study revealed that teachers with high self-efficacy had more positive emotions, whereas negative emotions were found to diminish teachers’ self-efficacy.
Although prior research has explored the influence of school climate on self-efficacy and the effect of self-efficacy on instructors’ PMH in the context of K12 stage education, such as elementary school education, there is a notable gap when it comes to the university level. Specifically, the empirical research focusing on this aspect at the university level is rather scarce. Additionally, the role that self-efficacy plays in the relationship between the university-level school climate and lecturers’ PMH remains largely unexamined. Thus, this study proposed the following hypothesizes:
H7. 
Lecturers’ self-efficacy has a mediating effect on the relationship between Collaboration and lecturers’ Positive Mental Health.
H8. 
Lecturers’ self-efficacy has a mediating effect on the relationship between Student Relations and lecturers’ Positive Mental Health.
H9. 
Lecturers’ self-efficacy has a mediating effect on the relationship between School Resources and lecturers’ Positive Mental Health.
H10. 
Lecturers’ self-efficacy has a mediating effect on the relationship between Decision-Making and lecturers’ Positive Mental Health.
H11. 
Lecturers’ self-efficacy has a mediating effect on the relationship between Instructional Innovation and lecturers’ Positive Mental Health.
Figure 1 shows the conceptual framework of this study.

3. Methods

3.1. Study Design

This study employs a cross-sectional survey design to examine the mediating role of self-efficacy in the relationship between university-level school climate and lecturers’ positive mental health. Quantitative data were collected through validated scales distributed via online questionnaire platforms.

3.2. Participants and Recruitment

The targeted population is the full-time English lecturers in Chinese higher education institutions, excluding administrative staff. There are three inclusion criteria: (1) current lecturer/professor position, (2) English teaching major, and (3) full-time employment. Convenient sampling was adopted for the study since the 2022 Statistical Bulletin on the Development of National Education, released by the Chinese Ministry of Education (Ministry of Education of the People’s Republic of China, 2022), reports that there are 1,977,800 full-time lecturers in higher education, which made probability sampling unable to be used. A power analysis conducted using G*Power 3.1 revealed that the minimum sample size (effect size = 0.15, α = 0.05, power = 0.80) should be 270 (Cohen, 2013).

3.3. Procedure

An online questionnaire-based survey was administered over a two-month period, conducted from 26 July to 30 September 2024. The questionnaire was distributed via various social media platforms (i.e., WeChat groups, QQ groups, and Weibo). Prior to distribution, consent was obtained from group administrators, after which the questionnaire hyperlink was provided. A total of 47 WeChat groups for college faculty of Language College in University (400–500 members each), 15 QQ groups for college faculty communication (over 800 members each), and 2 Weibo account with 1000 followers received the questionnaire links. Accompanying the links was a notification specifying that university-level English language lecturers were invited to complete the questionnaire.

3.4. Instruments

This questionnaire consists of three key sections. Section 1 contains a brief introduction to the research, along with a Data Confidentiality Statement and informed consent forms. Section 2 presents the items for collecting demographic information, and Section 3 includes the main survey items.
In Section 1, within the brief study introduction, we stated that the survey is intended for full-time lecturers of English majors in higher education. The Chinese version of the informed consent form is also provided here to clarify that the questionnaire is solely intended for academic use and to assure participants that their responses will be treated with the utmost confidentiality. We also informed the participants that there was no definitive or incorrect response. Respondents who agree to participate in the survey need to sign the informed consent form in person. If they do not sign, they will not be able to access the second part of the questionnaire.
In Section 2 regarding demographic information, it covers gender, age, highest degree, and institution type. Moreover, two specific questions are also asked to determine whether the respondents are the targeted population: (1) occupation and major in the field of higher education. The first question was “What is your job position within higher education?” Participants were required to choose “lecturer or professor” instead of “Administrative staff” in order to proceed to the following question. (2) What is your area of expertise in teaching? Only individuals who have selected English as their major are eligible to participate in the survey.
Section 3 is the main questionnaire. The items for each variable have been obtained from previous studies and have undergone thorough verification to ensure their reliability. The questions of the questionnaire were all from mature scales. Moreover, the respondents were all English teachers with good reading skills in both Chinese and English. Considering these factors, the items of the questionnaire were translated by the author, who passed the College English Test Band 8 in China. The items of the questionnaire are in both Chinese and English versions. A survey employing a 7-point Likert scale was used to assess the variables. Participants were asked to indicate the degree to which they agreed with the provided statement (1 = completely disagree, 4 = neutral, and 7 = completely agree) (Appendix A). The questionnaire uses a mature scale that has been verified in previous studies. In particular, the self-efficacy of the lecturers was evaluated using the General Self-efficacy Scale (GSES), which consists of 12 items (Klassen et al., 2009). Regarding school climate, it was previously assessed from several viewpoints. This study has utilized the School Climate Inventory (SCI-5), which consists of a total of 21 items proposed by B. Johnson et al. (2007) since it evaluates the school climate from the teaching faculty’s perspective. The SCI-5 consists of 5 sub-constructs, specifically Collaboration, Student Relations, School Resources, Decision-Making, and Instructional Innovation. The assessment of the lecturer’s positive mental health was conducted using the Positive Mental Health Scale (PMHS), which consists of 9 items and was derived from Lukat et al. (2016).

3.5. Data Analysis

Descriptive analysis of the data was conducted using SPSS 27. After confirming that the collected data passed the normality distribution check, this study used AMOS 23.0 to conduct confirmatory factor analysis (CFA), analyzing indicators such as the reliability, validity, and model fit. The threshold criteria adopted were from Hair et al. (2023). Subsequently, this study conducted a structural equation analysis on the data to verify the hypotheses.

4. Results

4.1. Basic Information of the Sample

A total of 357 valid responses were received. The basic information of the samples is shown in Table 1. The responses cover different ages, genders, education background, and types of college (public or private). The study used SPSS 27 to conduct descriptive analysis on each variable. The results (Table 2) show that the scores of the samples on all variables exceed the mean of 4, indicating that the overall scoring of the sample for all variables presents a positive situation. The kurtosis coefficient and skewness coefficient of each variable are all less than 10, indicating that the data conform to the normal distribution.

4.2. Measurement Model

This study employed the Maximum Likelihood Estimation (MLE) method to assess the measurement model as the data conformed to a normal distribution. To enhance the structural validity of the measurement model, confirmatory factor analysis (CFA) was conducted using AMOS 23.0. The analysis indicated an acceptable model fit (χ2 = 912.030, df = 798, χ2/df = 1.14, less than 3, RMSEA = 0.020, less than 0.08, IFI = 0.993, TLI = 0.992, and CFI = 0.993 all greater than 0.9), which all exceeded the recommended thresholds set by Hair et al. (2023).
To ensure the reliability and validity of the measurement instrument, composite reliability (CR) and average variance extracted (AVE) were computed. As presented in Table 3, CR values ranged from 0.918 to 0.976, surpassing the minimum threshold recommended by Hair et al. (2023), thereby reinforcing the internal consistency of the constructs. Moreover, AVE values exceeded the benchmark of 0.50, satisfying Fornell and Larcker (1981) criterion for convergent validity, which indicates that each latent construct is well-represented by its indicators. In addition, discriminant validity was assessed by comparing the square root of AVE for each construct with its highest correlation with other constructs. As illustrated in Table 4, the square root of AVE for each construct was greater than its corresponding inter-construct correlations, conforming to Fornell and Larcker (1981) criteria and substantiating the distinctiveness of the latent variables. These findings collectively affirm the reliability, convergent validity, and discriminant validity of the measurement model, establishing its suitability for further structural analysis.

4.3. Structural Model

Structural model was further analyzed through AMOS 23.0. The results of the model indicated a good fit (χ2 = 944.351, df = 803, χ2/df = 1.173, less than 3, RMSEA = 0.022, less than 0.08, GFI = 0.894, greater than 0.8, RFI = 0.939, CFI = 0.991, NFI = 0.943, TLI = 0.990, IFI = 0.991, all greater than 0.9). The results demonstrated that collaboration had a significant and positive effect on the self-efficacy of lecturers (β = 0.122, t = 2.401, p < 0.05). Therefore, hypothesis H1 was supported. The impact of Student Relations on lecturers’ self-efficacy was shown to be statistically significant and positive (β = 0.163, t = 3.076, p < 0.01), hence supporting hypothesis H2. The presence of School Resources had a notable and positive impact on the lecturers’ self-efficacy (β = 0.12, t = 2.19, p < 0.05), confirming the validity of Hypothesis 3 (H3). The study found that Decision-Making had a highly significant and positive effect on lecturers’ self-efficacy (β = 0.11, t = 2.157, p < 0.05), hence supporting hypothesis H4. The implementation of Instructional Innovation had a significant and positive impact on the lecturers’ self-efficacy (β = 0.325, t = 5.726, p < 0.001), hence confirming the support for hypothesis H5. The self-efficacy of the lecturers had a significant and positive effect on their positive mental health (β = 0.27, t = 5.027, p < 0.001), confirming the support for hypothesis H6. The results can be found in Table 5 and Figure 2.

4.4. Mediating Effects

This research employed the product of coefficients approach to examine indirect effects and determined their significance using the 5000 bootstrapping procedure (Hayes & Scharkow, 2013). In mediation analysis, partial mediation frequently occurs and is valuable for computing the ratio of indirect to total effects, commonly referred to as the variance accounted for (VAF) value. This value quantifies how much of the dependent variable’s variance is explained through mediation, where a VAF below 20% indicates minimal mediation, a range of 20% to 80% signifies partial mediation (Hair et al., 2023), and a VAF exceeding 80% suggests full mediation. This study specifically explored how lecturers’ self-efficacy mediates the relationships between Collaboration, Student Relations, School Resources, Decision-Making, Instructional Innovation, and Positive Mental Health. The findings, presented in Table 6, confirmed the hypotheses H7, H8, H9, H10, and H11.

5. Discussion

This study discussed the impact of school climate and lecturers’ self-efficacy on their positive mental health in Chinese high education. In particular, the study has focused on the mediating role of lecturers’ self-efficacy. The major findings are summarized below.
The most important finding of the results is that all five sub-variables of the school climate positively influence lecturers’ self-efficacy, suggesting that university-level school climate plays a crucial role in shaping lecturers’ self-efficacy. This finding aligned with previous studies conducted in K12 stage education (Dahlkamp et al., 2017; Hosford & O’Sullivan, 2016; Mansor et al., 2021), indicating that lecturers’ satisfaction with the university-level school climate influenced their decision to remain in the profession, considering factors like self-efficacy, working conditions, and job satisfaction. For example, Hosford and O’Sullivan (2016) found that a supportive school climate enhanced teacher efficacy and confidence in managing challenging behaviors in Irish primary schools. Similarly, Mansor et al. (2021) examined 695 sixth-form teachers in Malaysia and reported a strong positive relationship between school climate and self-efficacy. Moreover, this study found differences in the impact of five independent variables of school climate on lecturers’ self-efficacy compared to previous studies. Instructional innovation has the greatest impact on lecturers’ self-efficacy, while decision-making has the least impact. This finding is similar to the results of other studies; for example, many previous studies have shown that instructional innovation can improve higher education productivity, suggesting it is a crucial factor for teaching practice (Smith, 2012). Zainal and Mohd Matore (2021)’s study indicated that lecturers’ self-efficacy and their capability for instructional innovation are positively related.
However, our findings also contradict previous studies. Decision-making has been recognized as a crucial factor for improving teaching faculty’s self-efficacy. However, our study found that, although important, it ranks below other factors. Sukirno and Siengthai (2011) emphasized the importance of university lecturers’ participation in decision-making. They empirically examined the impact of participation in decision-making on lecturer performance in higher education in Indonesia. Their findings indicate that participative decision-making and academic rank significantly affect lecturer performance. Posselt et al. (2020)’s study also suggested that university faculty should participate in decisions such as admission of graduate students, hiring, peer review, and curriculum and instruction.
Furthermore, this study discovered a direct relationship between lecturers’ self-efficacy and their PMH. This implies that as lecturers’ self-efficacy increases, their ability to achieve PMH in their college work becomes stronger. The discovery aligns with prior studies, which demonstrated that self-efficacy has the potential to enhance mental well-being (Muenchhausen et al., 2021; Nabavi et al., 2017). Similar results can also be found among K12 stages. For instance, Capone and Petrillo (2020) reported that among 285 high school teachers, those with higher self-efficacy experienced less burnout and depression, emphasizing the need for interventions, especially for temporary teachers.
The study confirms that self-efficacy serves as a significant partial mediator between school climate and lecturers’ PMH (VAF = 20–80%), aligning with Bandura (1977)’s social cognitive theory. While prior research established direct links between climate factors and teacher‘s PMH (Gray et al., 2017), our findings extend this by demonstrating that 20–80% of school climate’s influence operates through self-efficacy. Specifically, instructional innovation was found to be the strongest factor for enhancing lecturers’ self-efficacy (e.g., successful adoption of new teaching methods). The partial mediation suggests climate also impacts lecturers’ PMH through unmeasured pathways, possibly via reduced job stress (Zoer et al., 2011) or social support (Harandi et al., 2017). Notably, self-efficacy’s direct effect on lecturers’ PMH highlighted its role as a psychological resource, which has been observed in K-12 stages (Burić et al., 2020) but previously untested in higher education.

5.1. Theoretical Implications

Our results have two main theoretical contributions for fostering positive mental health among university lecturers in higher education. Firstly, this study establishes a theoretical basis for understanding both institutional and individual-level determinants of university lecturers’ positive mental health, with a particular emphasis on the role of self-efficacy. While previous research has extensively examined the influence of self-efficacy on job satisfaction and burnout among university lecturers (Capone & Petrillo, 2020; Huang et al., 2019; Nabavi et al., 2017), its role in shaping school climate and fostering positive mental health has been largely overlooked. This study addresses this gap by demonstrating that self-efficacy mediates the relationship between school climate and faculty well-being, thereby shifting the research focus from macro-level institutional policies to individual psychological resources. By highlighting the interplay between institutional support structures and psychological resilience, our findings offer a more comprehensive perspective on the mechanisms underlying lecturers’ positive mental health. Secondly, this study advances the understanding of school climate by dissecting it into five distinct dimensions for further analysis and discussion. This approach deepens insights into how different aspects of school climate influence university lecturers’ self-efficacy and positive mental health. Unlike prior studies, which often treated school climate as a singular variable without exploring its specific components or their subsequent impacts, our research provides a more nuanced theoretical framework (Collie et al., 2012; Dahlkamp et al., 2017; Kang, 2023; Zakariya, 2020). By doing so, we offer a more comprehensive understanding of how to cultivate a psychologically supportive school climate in higher education.

5.2. Implications for Policy

Given the verified mediating role of self-efficacy between university-level school climate and lecturers’ PMH, the empirical findings of this study provide evidence to inform policy development in Chinese higher education institutions. Accordingly, we propose the following two policy recommendations.
First, universities should strengthen institutional support for instructional innovation. In most Chinese universities, academic research projects tend to receive more financial support and faculty engagement compared to instructional innovation initiatives. Therefore, this study recommends that universities enhance funding programs for instructional innovation projects to encourage faculty participation. Additionally, developing teaching–research integration initiatives that recognize pedagogical innovation in research performance evaluations is also advised. Second, this study suggests that universities establish structured mentorship systems to better promote lecturers’ self-efficacy. For example, implementing mandatory mentorship programs with a 1:2 pairing ratio (senior to junior faculty) could focus on key efficacy-building areas such as classroom management, research productivity, and work–life balance.

5.3. Limitations and Future Research

There are three primary limitations to this study. Firstly, in terms of the study design and sampling technic, this study employed a cross-sectional design, which limits the ability to establish causal relationships between school climate, lecturers’ self-efficacy, and their PMH. Although we proposed self-efficacy as a mediator, longitudinal or experimental designs would be necessary to confirm the directionality of these effects. Moreover, convenience sampling via social media platforms (e.g., WeChat and QQ groups) is adopted by the study to recruit participants, which may introduce selection bias. This method relies on voluntary participation, potentially overrepresenting lecturers who are more active online or motivated to engage in research while underrepresenting those with limited digital access or low participation willingness.
Secondly, the research focuses mainly on English major lecturers in Chinese higher education institutions, limiting the generalizability of our findings to this specific group. It is important to note that English major lecturers may differ from lecturers of other disciplines in various aspects, such as teaching content and methods. English major lecturers emphasize language skills and intercultural communication, whereas teachers in other disciplines might prioritize the transmission of specialized knowledge and technical application. Additionally, English major lecturers are often assigned with more public courses in Chinese higher education, which could influence their self-efficacy and perception of school climate differently from lecturers of other disciplines. Future research could expand to include a broader range of disciplines, particularly those in the literature (which focus on developing students’ communication and literary skills) and engineering (which emphasize hands-on and problem-solving skills), to compare whether there are differences in self-efficacy among lecturers in various fields.
Thirdly, while school climate has been extensively studied from both empirical and theoretical perspectives, there is a lack of conceptual agreement across this body of literature, resulting in inconsistent guidance for research into this important topic. This study is based on the definition and measurement of school climate as proposed by B. Johnson et al. (2007). It is recognized that the definition of school climate varies depending on the research subjects. For example, there are differences in the perceived school climate between students and teachers, and the definitions and measurement methods of school climate differ across primary, secondary, and higher education. Therefore, future research could further explore the differences in definitions of school climate to seek the generalizability of this study’s findings.

6. Conclusions

This study explores the impact of university-level school climate and self-efficacy on English lecturers’ PMH in China, with a focus on the mediating role of self-efficacy. Data from 357 English lecturers show that all five school climate dimensions—Collaboration, Student Relations, School Resources, Decision-Making, and Instructional Innovation—positively affect self-efficacy, with Instructional Innovation having the strongest effect. Self-efficacy significantly enhances PMH and partially mediates the relationship between school climate and PMH (VAF = 20–80%). The findings highlight the importance of fostering an innovative school climate and enhancing self-efficacy to promote faculty well-being. The study extends prior research by establishing a mediational model in higher education, showing school climate influences PMH primarily through self-efficacy. Recommendations include supporting instructional innovation and implementing mentorship programs to boost self-efficacy and faculty mental health.

Author Contributions

Conceptualization, Q.L.; methodology, Q.L. and B.S.A.; formal analysis, Q.L.; investigation, Q.L.; writing—original draft preparation, Q.L.; writing—review and editing, B.S.A. and A.H.A.H.; project administration, B.S.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and approved by the academic committee of the School of Language and Culture of City University of Dongguan, NO. DGC-2024-011, 2024-07-01 for studies involving humans.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
LSELecturers’ self-efficacy
COLCollaboration
STRStudent Relations
SCRSchool Resources
DEMDecision-Making
INIInstructional Innovation
PMHPositive Mental Health

Appendix A

Table A1. Measurements.
Table A1. Measurements.
VariableNumItems
Positive Mental Health Scale1I am often carefree and in good spirits.
2I enjoy my life.
3All in all, I am satisfied with my life.
4In general, I am confident.
5I manage well to fulfill my needs.
6I am in good physical and emotional condition.
7I feel that I am actually well equipped to deal with life and its difficulties.
8Much of what I do brings me joy.
9I am a calm, balanced human being.
Lecturers’ self-efficacy10How much can you do to craft good questions for students?
11How much can you do to implement a variety of assessment strategies?
12How much can you do to provide an alternate explanation when students are confused?
13How much can you do to implement alternative strategies in your classroom?
14How much can you do to motivate students who show low interest in school work?
15How much can you do to get students to believe they can do well in school work?
16How much can you do to help students value learning?
17How much can you do to assist families in helping their children do well in school?
18How much can you do to control disruptive behavior in the classroom?
19How much can you do to get children to follow classroom rules?
20How much can you do to calm a student who is disruptive of noisy?
21How much can you do to establish a classroom management system with each group of students?
School climateCollaboration22Classroom instruction is rarely coordinated across teachers.
23I have regular opportunities to work with other teachers.
24There is good communication among teachers.
25Good teamwork is not emphasized enough at my school.
26I seldom discuss the needs of individual students with other teachers.
27Teachers design instructional programs together
Student
Relations		28Most students are well mannered or respectful of the school staff.
29Students in this school are well behaved.
30Most students are helpful and cooperative with teachers.
31Most students are motivated to learn.
School
Resources		32The supply of equipment and resources is not adequate.
33Instructional equipment is not consistently accessible.
34Video equipment, tapes, and films are readily available.
35The school library has sufficient resources and materials
Decision-Making36Teachers are frequently asked to participate in decisions.
37I have very little to say in the running of the school.
38Decisions about the school are made by the principal.
Instructional
Innovation		39We are willing to try new teaching approaches in my school.
40New and different ideas are always being tried out.
41Teachers in this school are innovative.
42New courses or curriculum materials are seldom implemented.

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Education 15 00852 g001
Figure 1. Conceptual framework.
Figure 1. Conceptual framework.
Education 15 00852 g001
Education 15 00852 g002
Figure 2. SEM results. Note: LSE: lecturers’ self-efficacy; COL: Collaboration; STR: Student Relations; SCR: School Resources; DEM: Decision-Making; INI: Instructional Innovation; PMH: Positive Mental Health.
Figure 2. SEM results. Note: LSE: lecturers’ self-efficacy; COL: Collaboration; STR: Student Relations; SCR: School Resources; DEM: Decision-Making; INI: Instructional Innovation; PMH: Positive Mental Health.
Education 15 00852 g002
Table 1. Basic information of the samples.
Table 1. Basic information of the samples.
ItemsNumPercentage (%)
GenderMale8122.689
Female27677.311
Age≥613610.084
51–605014.006
18–306919.328
31–408022.409
41–5012234.174
Highest degreePh.D.298.123
Master32891.877
Institution type (Job)Private Education9827.451
Public Education25972.549
Table 2. Descriptive statistical results of the variable.
Table 2. Descriptive statistical results of the variable.
VariablesMinMaxMeanSDSkewnessKurtosis
LSE1.836.585.051.55−1.03−0.82
COL1.336.674.941.60−0.89−0.99
STR1.507.005.161.56−1.15−0.30
SCR1.257.004.791.74−0.63−1.37
DEM1.007.005.151.64−1.15−0.20
INI1.007.004.941.66−0.78−1.11
PMH1.676.675.091.57−1.08−0.65
Note: LSE: lecturers’ self-efficacy; Collaboration: COL; STR: Student Relations; SCR: School Resources; DEM: Decision-Making; INI: Instructional Innovation; PMH: Positive Mental Health.
Table 3. Cronbach’s alpha coefficient, composite reliability, and AVE.
Table 3. Cronbach’s alpha coefficient, composite reliability, and AVE.
FactorItemsFactor LoadingAVECR
LSELSE10.8790.7710.976
LSE20.868
LSE30.883
LSE40.877
LSE50.887
LSE60.876
LSE70.885
LSE80.878
LSE90.877
LSE100.87
LSE110.875
LSE120.88
COLCOL10.890.7820.956
COL20.884
COL30.884
COL40.885
COL50.881
COL60.882
STRSTR10.8660.7750.933
STR20.88
STR30.898
STR40.878
SCRSCR10.9010.790.938
SCR20.882
SCR30.879
SCR40.894
DEMDEM10.8750.7890.918
DEM20.897
DEM30.893
INIINI10.8760.7760.933
INI20.87
INI30.896
INI40.882
PMHPMH10.8780.7760.969
PMH20.899
PMH30.864
PMH40.88
PMH50.881
PMH60.88
PMH70.902
PMH80.88
PMH90.865
Note: LSE: lecturers’ self-efficacy; Collaboration: COL; STR: Student Relations; SCR: School Resources; DEM: Decision-Making; INI: Instructional Innovation; PMH: Positive Mental Health.
Table 4. The square root of the AVE scores.
Table 4. The square root of the AVE scores.
PMHINIDEMSCRSTRCOLLSE
PMH0.878
INI0.2900.881
DEM0.3040.3660.888
SCR0.2890.4370.3430.889
STR0.2430.4090.2260.3790.881
COL0.1520.3220.2810.3620.3450.884
LSE0.2650.5220.3400.4040.4070.3570.881
Note: The diagonals represent the average variance extracted (AVE); LSE: lecturers’ self-efficacy; COL: Collaboration; STR: Student Relations; SCR: School Resources; DEM: Decision-Making; INI: Instructional Innovation; PMH: Positive Mental Health.
Table 5. Hypotheses test results.
Table 5. Hypotheses test results.
βC.R. (t-Value)Hypothesis
H1COL → LSE0.122 *2.401Supported
H2STR → LSE0.163 **3.076Supported
H3SCR → LSE0.12 *2.19Supported
H4DEM → LSE0.11 *2.157Supported
H5INI → LSE0.325 ***5.726Supported
H6LSE → PMH0.27 ***5.027Supported
Note: β: Standardized path coefficient; LSE: lecturers’ self-efficacy; COL: Collaboration; STR: Student Relations; SCR: School Resources; DEM: Decision-Making; INI: Instructional Innovation; PMH: Positive Mental Health; * p < 0.05, ** p < 0.01, *** p < 0.001.
Table 6. Mediating analysis.
Table 6. Mediating analysis.
IVMVDVDirect EffectIndirect EffectTotal EffectVAFResults
COLLSEPMH0.064
(1.205)		0.080 *
(3.330)		0.144 *
(2.892)		55.56%Partial mediation
STRLSEPMH0.154
(2.787)		0.078 *
(2.986)		0.232 ***
(4.466)		33.62%Partial mediation
SCRLSEPMH0.186 ***
(3.775)		0.062 *
(2.520)		0.248 ***
(5.399)		25.15%Partial mediation
DEMLSEPMH0.217 ***
(4.301)		0.057 *
(2.784)		0.274 ***
(5.645)		20.78%Partial mediation
INILSEPMH0.185 *
(3.375)		0.075 *
(2.288)		0.260 **
(5.427)		28.90%Partial mediation
Note: LSE: lecturers’ self-efficacy; COL: Collaboration; STR: Student Relations; SCR: School Resources; DEM: Decision-Making; INI: Instructional Innovation; PMH: Positive Mental Health; * p < 0.05, ** p < 0.01, *** p < 0.001.
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Lai, Q.; Alias, B.S.; Hamid, A.H.A. School Climate and Self-Efficacy Relating to University Lecturers’ Positive Mental Health: A Mediator Model. Educ. Sci. 2025, 15, 852. https://doi.org/10.3390/educsci15070852

AMA Style

Lai Q, Alias BS, Hamid AHA. School Climate and Self-Efficacy Relating to University Lecturers’ Positive Mental Health: A Mediator Model. Education Sciences. 2025; 15(7):852. https://doi.org/10.3390/educsci15070852

Chicago/Turabian Style

Lai, Qin, Bity Salwana Alias, and Aida Hanim A. Hamid. 2025. "School Climate and Self-Efficacy Relating to University Lecturers’ Positive Mental Health: A Mediator Model" Education Sciences 15, no. 7: 852. https://doi.org/10.3390/educsci15070852

APA Style

Lai, Q., Alias, B. S., & Hamid, A. H. A. (2025). School Climate and Self-Efficacy Relating to University Lecturers’ Positive Mental Health: A Mediator Model. Education Sciences, 15(7), 852. https://doi.org/10.3390/educsci15070852

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