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Digital transformation in physical education: chain mediator model of self-efficacy burnout and professional development.

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Digital transformation in physical education: chain mediator model of self-efficacy burnout and professional development - PMC Skip to main content An official website of the United States government Here's how you know Here's how you know Search Log in Primary site navigation Search Log in Search PMC Full-Text Archive Search in PMC Journal List User Guide As a library, NLM provides access to scientific literature. Inclusion in an NLM database does not imply endorsement of, or agreement with, the contents by NLM or the National Institutes of Health. Learn more: PMC Disclaimer | PMC Copyright Notice BMC Psychol . 2026 Apr 22;14:815. doi: 10.1186/s40359-026-04528-z Digital transformation in physical education: chain mediator model of self-efficacy burnout and professional development Luhong Ma 1 , Chen Soon Chee 1, ✉ , Pan Liu 1, ✉ , Saidon Amri 1 Author information Article notes Copyright and License information 1 Department of Sports Studies, Faculty of Educational Studies, Universiti Putra Malaysia, Seri Kembangan, Selangor, 43300 Malaysia ✉ Corresponding author. Received 2025 Nov 27; Accepted 2026 Apr 6; Collection date 2026. © The Author(s) 2026 Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ . PMC Copyright notice PMCID: PMC13231599  PMID: 42015208 Abstract Background This study examined the relationship among burnout, professional development, and self-efficacy among physical education teachers in universities.The focus is on issues such as teachers' self-efficacy and general efficacy, professional burnout, and professional development in the digital age. Physical education teachers in higher education may experience reduced self-efficacy and professional well-being in digital environments, leading to professional burnout and diminished motivation for professional development. Although this issue holds significant implications for professional development, research evidence specifically targeting physical education teachers remains limited. Methods March to April 2025, a total of two hundred and fifty-eight physical education teachers from public universities in Henan Province, China, voluntarily participated in this survey. Data were collected via an online survey including the Burnout Self-Assessment Scale(BSAC), the General Self-Efficacy Scale(GSES),, and the Professional Development Questionnaire(PDQ). Descriptive statistics and SEM were employed for analysis. along with Pearson correlation to assess relationships between variables. Results Physical education teachers' burnout showed a significant negative correlation with personal teaching efficacy ( r = –0.186, p < 0.01), general teaching efficacy ( r = –0.197, p < 0.01), and professional development ( r = –0.151, p < 0.05) in the digital.Among the self-efficacy variables, personal teaching efficacy ( r = 0.674, p < 0.01) and general teaching efficacy ( r = 0.717, p < 0.01) both showed significant positive correlations with professional development. Personal and general teaching efficacy showed a positive correlation ( r = 0.745, p < 0.01). Personal teaching efficacy significantly fully mediated the relationship between professional burnout and general teaching efficacy (β = –0.186, p < 0.01). General teaching efficacy fully mediated the relationship between personal teaching efficacy and professional development (β = 0.566, p < 0.001). In the chain-mediated model, Personal and general teaching efficacy together formed a significant chain-mediating pathway between professional burnout and professional development (β = –0.106, p < 0.01). These findings indicate that self-efficacy plays a significant role in burnout and professional development among physical education teachers. Conclusion This study indicates that self-efficacy and occupational burnout are key factors influencing the professional development of university physical education teachers. Higher levels of self-efficacy enhance teachers' professional development, while higher levels of occupational burnout diminish it. Keywords: Digital, Physical education, Self-Efficacy, Burnout, Professional Development Introduction In recent years, the rapid advancement of digital technology has been transforming education worldwide, reshaping teaching methods, learning environments, and educators' roles. Cutting-edge technologies such as big data, artificial intelligence, virtual technologies, and online learning platforms have been integrated into the educational landscape [ 1 – 3 ]. It has given rise to new teaching models while simultaneously presenting fresh demands for teachers' professional development. Digital professional development represents an inevitable direction for teachers' future career growth [ 4 ]. Every year, many countries invest substantial resources in professional development (PD) to improve teaching quality and classroom effectiveness [ 5 ]. While digital transformation presents opportunities for pedagogical innovation and teaching efficiency, it also poses significant challenges for educators. It is particularly true in physical education disciplines, which heavily rely on the instructor's skills, contextual interaction, and real-time feedback [ 6 , 7 ]. Therefore, teacher professional development remains an important topic in educational research. Giving priority to professional development can greatly enhance teachers' motivation to learn. Factors related to professional development Compared to other subjects, physical education emphasizes physical activity, mastery of athletic skills, and direct interaction with teachers in the classroom. Therefore, integrating digital technology requires physical education teachers to possess not only traditional teaching skills but also advanced digital competencies. It increases teachers' workload and the pressure to continuously learn new technologies, thereby heightening the risk of professional burnout. Effective digital professional development can strengthen teachers' knowledge and instructional competencies [ 8 ], thereby positively influencing student learning. Additionally, teacher professional development influences their sense of self-efficacy. Qualitative research based on RORAIMA emphasises that self-efficacy positively affects the professional development of physical education teachers [ 9 ]. Despite differences among school subjects, the relationship between self-efficacy and teacher professional development remains consistent across disciplines [ 10 ]. Examining the relationship between burnout and professional development among university physical education teachers can yield valuable insights for educators and researchers in PE teaching. This research also establishes a foundation for enhancing the quality of school teaching environments and strengthening teachers' professional competence. Scholars widely recognize professional development as a crucial factor in enhancing teaching quality and driving educational innovation. Against the backdrop of advancing digital technologies, professional development enables teachers to master emerging instructional skills and adapt to evolving teaching environments. However, teachers' participation in professional development is not solely determined by external circumstances; internal psychological mechanisms also influence it. Self-efficacy, a core concept in Bandura's social cognitive theory, has been repeatedly identified as a key factor in teachers' motivation, persistence, and professional commitment [ 11 , 12 ]. Self-efficacy refers to an individual's belief in their ability to perform the necessary behaviours required to achieve specific performance outcomes [ 13 ]. Among university physical education teachers, expectancy self-efficacy is associated with professional development; however, studies exploring this relationship in this population remain limited. For teachers experiencing low levels of burnout, high self-efficacy may further promote professional development. Self-efficacy also serves as an important mediator between teacher burnout and professional development [ 14 , 15 ]. Furthermore, structural equation modelling (SEM) results show that self-efficacy mediates the relationship between teachers' professional development and the two main dimensions: professional attitudes and the application of teaching strategies [ 16 ]. Therefore, future research should place greater emphasis on exploring the relationships among physical education teachers' self-efficacy, burnout, and the effects of self-efficacy on their professional development. Chain mediation of self-efficacy Previous research has confirmed that high levels of professional burnout are typically associated with reduced self-efficacy, which in turn leads to decreased engagement in professional development. However, existing studies primarily examine self-efficacy as a single, isolated factor. According to Bandura's theoretical framework [ 11 ], self-efficacy operates across multiple levels, from specific contexts to broader professional development. In teaching contexts, occupational stress and emotional exhaustion may undermine teachers' Personal Teaching Effectiveness (PTE). In turn, erodes their General Teaching Effectiveness (GTE) and ultimately limits their willingness to engage in continuous professional development (PD). It suggests a chain-mediated mechanism through which burnout influences PD by affecting different dimensions of self-efficacy. Additionally, the primary theoretical framework explaining burnout is the Job Demands–Resources (JDR) model [ 17 , 18 ]. According to Maslach's classic definition, burnout comprises three dimensions: emotional exhaustion, depersonalization, and reduced personal accomplishment [ 19 ]. It has identified numerous variables associated with burnout, such as stress [ 20 ], teacher well-being [ 21 ], job satisfaction [ 22 , 23 ], and work engagement [ 24 ]. These dimensions can also influence teachers' work behaviours, psychological needs, and professional development, as reflected in issues such as low motivation, early retirement, job turnover, and changes in self-efficacy [ 25 ]. Therefore, it is essential to consider multiple factors comprehensively in order to establish supportive work environments and effective professional development mechanisms that can alleviate teachers' occupational burnout. Although this chained mediation process is theoretically plausible, empirical evidence remains limited, especially among physical education instructors in Chinese universities. Most existing studies focus on elementary and secondary school teachers in other disciplines, with few examining the unique professional context of university-level physical education instructors. In China, these teachers face distinctive challenges, including curriculum reform and the digitization of teaching, and these multifaceted pressures may interact in complex ways to shape their professional burnout, self-efficacy, and professional development. At present, few studies have examined the relationship between self-efficacy and occupational burnout among university physical education teachers, nor have they explored how burnout interventions might influence professional development through self-efficacy. Thus, investigating these relationships holds significant value for promoting the professional development of university physical education teachers. Theoretical background and assumptions This study examines the relationship between occupational burnout and professional development by considering the mediating role of self-efficacy. A review of existing literature has been conducted to establish a theoretical foundation and clarify the interactions among these variables. Theoretical framework Social Cognitive Theory [ 26 , 27 ] and Job Demands–Resources (JD-R) theory [ 28 , 29 ] both emphasise the role of cognition in shaping professional development and attitudes. Additionally, Desimone proposed a preliminary conceptual framework for teacher professional development (TPD), focusing primarily on two core components: the key characteristics of effective professional development and the operational theories underlying TPD [ 30 ]. Philipsen et al. further synthesised a conceptual framework for TPD in Online and Blended Learning (OBL), comprising six core elements: programs and environments, existing contexts, teacher mobility, overall goals and relevance, TPD strategies, and assessment of OBL-related knowledge, skills, and attitudes [ 31 ]. Social Cognitive Theory highlights the interaction among individual, behavioural, and environmental factors, underscoring the relationships among self-efficacy, job performance, and professional development. The JD-R theory remains one of the leading conceptual models for explaining factors influencing employee burnout during work processes [ 28 ]. Burnout and stress may arise from two primary dimensions: job demands and job resources [ 32 ]. Extensive research has demonstrated the JD-R model's relevance for studying burnout, self-regulation, job satisfaction, and professional development [ 33 – 36 ]. Digital professional development serves as the central theme of this study, while the TPD theoretical framework represents a mainstream paradigm within the teaching profession. Personal teaching efficacy serves as an individual teacher's psychological resource. At the same time, professional burnout reflects personal psychological emotions, both of which align with the personal resources component of the JD-R model. General teaching efficacy refers to a teacher's overall belief during instruction, and professional development represents the growth-oriented demand within teaching resources. Enhanced by social cognitive theory and teacher professional development theory, the multifaceted integrated JD-R model better adapts to the digital education era. Personal resources, through the replenishment and regulation of work resources, facilitate the fulfillment of work demands. Although the JD-R framework for occupational burnout is well established, it has not yet been applied to digital professional development. Moreover, research examining how occupational burnout influences professional development through self-efficacy among university physical education teachers remains insufficient, underscoring the need for further exploration—a gap this study seeks to address. This study hypothesises that self-efficacy mediates the relationship between occupational burnout and professional development: higher self-efficacy enhances professional development and, in turn, reduces occupational burnout. Therefore, by integrating and extending emerging digital perspectives, this research investigates how self-efficacy and occupational burnout affect the professional development of university physical education teachers. Collectively, this study constructs a chain mediation model, as shown in Fig. 1 : Fig. 1. Open in a new tab Chain mediation hypothesis model Relationship between teacher burnout and professional development Burnout is commonly discussed in relation to teachers' professional development. Fessler and Christensen surveyed 160 teachers and found that those experiencing professional frustration and burnout reported more positive attitudes toward professional growth, suggesting that burnout may in some cases be short-lived or situational [ 37 ]. Furthermore, vocational training and professional education have been examined within the JD-R resource model as interventions aimed at reducing teacher burnout through job remodelling and adaptive regulation [ 17 , 38 , 39 ]. Although some evidence indicates that burnout may coexist with professional engagement under certain conditions, the predominant body of research suggests that sustained professional burnout is more likely to hinder teachers' long-term professional development. Accordingly, this study hypothesises that professional burnout is negatively associated with the professional development of physical education teachers, while acknowledging that this relationship may vary across contexts. H a 1 There is a negative correlation between burnout and digital professional development. Teacher burnout, professional development, and self-efficacy Although the relationship between professional burnout and teacher professional development has been widely studied, research examining the mediating role of self-efficacy in this context remains limited. Existing evidence suggests that self-efficacy not only mitigates professional burnout but also fosters professional development, pointing to its potential role as a mediator between these two variables. For example, Brown found a significant effect between teachers' professional development and self-efficacy [ 40 ]. Teachers need to be confident enough to design and implement online or hybrid courses. Italian scholars define it as the teacher's belief in his or her ability to perform professionally relevant tasks (teaching tasks, managing students and classroom discipline issues, etc.) and challenges (professional competence, innovation) [ 41 ]. Teacher self-efficacy is defined as the teacher's belief in his or her ability to accomplish teaching tasks and to develop professionally and effectively [ 42 ]. Given these findings, this study hypothesizes that self-efficacy mediates the relationship between burnout and professional development among physical education teachers in higher education institutions. H a 2 There is a negative correlation between self-efficacy and burnout. H a 3 There is a positive correlation between self-efficacy and digital professional development. Personal teaching efficacy and general teaching efficacy Building on Rotter's theory, Bandura posited that individual behavior is influenced not only by reinforcement in a broad sense but also by personal self-perception and self-efficacy [ 43 ]. Guskey et al. distinguished between extrinsic and intrinsic factors in personal efficacy and teaching efficacy [ 44 ]. An individual's confidence in teaching depends on the teacher's personal capabilities, such as student management skills and computer proficiency [ 45 ]. Working conditions, workload, and instructional tasks form the core of teaching practice [ 46 ]. A teacher's general teaching confidence reflects the sense of accomplishment gained while performing these duties. Personal teaching efficacy, rooted in self-efficacy, not only fulfills individual needs but also strengthens educators' pedagogical convictions. Teachers with strong PTE are more likely to experience instructional success, accumulate mastery experiences, and develop a stable sense of professional competence. These positive experiences reinforce generalized beliefs about the power of teaching as a whole, thereby enhancing GTE. Conversely, persistent doubts about one’s instructional capabilities may erode confidence in the broader educational mission, thereby weakening GTE. Empirical evidence supports a positive association between PTE and GTE, indicating a sequential belief transmission mechanism. The interaction between personal and general teaching efficacy has not been investigated; therefore, Hypothesis 4 of this study also examines the two dimensions of self-efficacy and their joint mediating effects. H a 4 The mediating role of Self-efficacy on the relationship between burnout and digital professional development. Methodology Study design This study employed a cross-sectional and quantitative correlational research design. Perceived burnout was measured using the Burnout Scale for Physical Education Teachers (BSPET) [ 47 ]. Participants' professional development was assessed using the Scale for Teachers' ICT Integration Proficiency (STICTIP) [ 48 ]. Self-efficacy was measured using the High School Physical Education Teachers Self-Efficacy Scale (HSPETSS) [ 49 ]. Pearson correlation analysis and multiple linear regression analysis were conducted to examine the relationships among professional burnout, professional development, and self-efficacy. The questionnaire survey also collected demographic information, including gender and age. Given the Likert-type nature of the data, nonparametric tests were used to examine gender and age differences in professional development. The Ethics Committee of Universiti Putra Malaysia granted ethical approval for this study, with approval documented in Letter No: JKEUPM-2023–701. Participants sampling This study employed quantitative research methods and used written self-assessment questionnaires as the primary data collection tool. Participants included physical education teachers from 17 public universities in Henan Province, China. In Structural Equation Modeling (SEM) research, Monte Carlo simulations indicate that samples of approximately 200–250 provide sufficient statistical power (≥ 0.80) for detecting mediation effects, particularly when bootstrap techniques are applied [ 50 – 52 ]. Power analysis (e.g., via G-Power) may suggest a much lower number; in a linear multiple regression, the R 2 increase model sample size was 77 (Power > 0.8). The research team used a stratified, proportional random sampling method to survey 260 teachers. After excluding two teachers who declined to provide informed consent, 258 valid data questionnaires were collected. Data collection Data collection was conducted from March to April 2025 using an online questionnaire administered via the WJX.CN platform ( https://www.wjx.cn/ ). First, from among the 178 higher education institutions in Henan Province, private schools were excluded, selecting only 122 public institutions. Subsequently, based on institutional ranking tiers, the sample included 2 key universities, 8 comprehensive universities, and 7 general vocational colleges. The research team generated QR codes and distributed them through WeChat groups managed by the physical education departments of participating institutions. Faculty members from 17 general universities, key colleges, and vocational and technical colleges were invited to participate anonymously and complete the questionnaire at random. All participants provided informed consent prior to participation. The consent procedure clearly outlined the study objectives, procedures, and confidentiality measures, ensuring that respondents fully understood their rights and that their data would remain anonymous and be used solely for research purposes. Only participants who provided consent could access the questionnaire. To reduce common method bias, anonymity was ensured, and respondents were encouraged to answer honestly. All questions must be completed sequentially; respondents cannot proceed to the next question until the current one is finished. The average completion time is approximately 235 s. A total of 258 valid questionnaires were obtained from physical education teachers in higher education institutions across Henan Province. Measures Burnout scale for physical education teachers It measures burnout among college physical education teachers in the context of digital technology. It is primarily based on the recognised Maslach Burnout Inventory (MBI), which has three dimensions: emotional exhaustion, depersonalisation, and personal accomplishment [ 19 ]. Building on this, scholars Li & Wang adapted it for use with university physical education teachers, creating the Burnout Scale for Physical Education Teachers [ 53 ]. The revised burnout scale has 13 items, and the Cronbach's alpha of the total scale is 0.925. Scale for Teachers' ICT Integration Proficiency Professional Development for Physical Education Teachers, revised by the Scale for Teachers' ICT Integration Proficiency by Valverde-Berrocoso et al. [ 48 ]. This scale consists of 20 items, each rated on a 5-point Likert scale ranging from "Strongly disagree" to "Strongly agree." For example, items include "I feel the need for more training and education regarding digital physical education," and "In the digital context, I feel significant improvement in my teaching abilities." These items help measure physical education teachers' professional development levels and provide valuable insights into their current professional development status. The Cronbach's alpha for the scale was 0.934. High school physical education teachers' self-efficacy scale It measures the level of self-efficacy among college physical education teachers in the context of digital technology. It is primarily based on Bandura's self-efficacy theory [ 54 ], and the scholar Pan [ 49 ] adapted it for use with High School Physical Education Teachers, creating the Self-efficacy Scale. The self-efficacy scale has 14 items, and the Cronbach's alpha of the total scale is 0.91. Personal teaching efficacy includes seven items, such as "I am good at physical education curriculum design", and Cronbach's alpha is 0.84. General teaching efficacy includes seven items, such as "Even though I spend much time, I still cannot motivate students who lack interest in physical education", and Cronbach's alpha is 0.928. Data analysis This study used SPSS 29.0 and Amos 29.0 for data analysis [ 55 ]. The data analysis proceeded in three stages. In the first stage, descriptive analysis summarized participants' demographic characteristics. The data met the assumptions of normality, thereby strengthening the validity of the measurement models and supporting the accurate interpretation of the results [ 56 ]. Skewness values ranged from –0.150 to 0.271, and kurtosis values ranged from –0.182 to 0.854. All values fell within the acceptable range of ± 2 [ 57 , 58 ], indicating that the data followed a normal distribution. The sample comprised 155 male and 103 female teachers. Regarding age distribution, 17 participants were younger than 29 years, 86 were aged 30–39 years, 118 were aged 40–49 years, and 36 were aged 50–59 years, indicating that the majority of the sample (79.1%) fell within the 30–49-year age range. The mean age category score was 2.68 (SD = 0.81), and the mean gender score was 1.40 (SD = 0.49). In the second stage, Pearson correlation analysis examined the relationships among professional burnout, the two dimensions of self-efficacy (personal teaching efficacy and general teaching efficacy), and professional development in the digital era. In the third stage, the study applied structural equation modeling (SEM) to evaluate how self-efficacy and occupational burnout predicted professional development, including the mediating role of self-efficacy in the relationship between occupational burnout and professional development [ 50 ]. The study used bootstrap analysis to validate the mediating effect of self-efficacy, setting the parameters as follows: bootstrap sample size of 5000, bias-corrected 95% confidence intervals [ 59 – 61 ], with statistical significance set at p < 0.05. Reliability and validity To ensure the scale demonstrated objective reliability, this study used two measurement approaches: internal consistency and composite reliability. Table 1 shows that the values for Cronbach's alpha, McDonald's omega, and composite reliability (CR) all exceed 0.8, demonstrating strong reliability [ 62 , 63 ]. Following SEM-based criteria for convergent validity, both the average variance extracted (AVE) and factor loadings were greater than 0.5 [ 64 , 65 ], supporting good convergent validity. The research team conducted a confirmatory factor analysis to assess the measurement model, and the results indicated good model fit. Table 1. Reliability and validity for this construct Construct Cronbach's α Omega AVE CR FL Bur (9 items) 0.912 0.908 0.625 0.830 0.779–0.921 PTE (4 items) 0.883 0.883 0.553 0.832 0.730–0.856 GTE (5 items) 0.840 0.840 0.520 0.811 0.672–0.759 PD (9 items) 0.936 0.936 0.517 0.864 0.878–0.970 Open in a new tab Bur burnout, PTE personal teaching efficacy, GTE general teaching efficacy, PD professional development Common method bias test The Harman's one-factor test is a commonly used method for examining common method bias in data [ 66 ]. In addition, the Common Latent Factor (CLF) approach was applied [ 67 , 68 ]. In the predictive model, the unrotated cumulative variance for a single factor reached 37.884%, which remains below the 40% threshold. Furthermore, the chi-square difference between the baseline model (497.792, df = 311) and the control model (492.579, df = 308) was not statistically significant (Δχ 2 = 5.213, Δdf = 3, p > 0.05). These findings indicate that common method bias is unlikely to substantially influence the study findings. Result Descriptive analysis and pearson correlation matrix Table 2 reports the descriptive statistics and correlation matrix for all variables. On the 5-point Likert scale, a mean score of 2.5 serves as the reference level point. The professional burnout level among physical education teachers at universities in Henan Province (M = 2.712, SD = 0.726) was slightly above the moderate level, and teachers show substantial variability in their burnout scores. In contrast, the mean scores for personal teaching efficacy, general teaching efficacy, and professional development (all components of self-efficacy) were significantly greater than 2.5, with SD values ranging from 0.583 to 0.652, reflecting moderate dispersion. These results suggest that teachers' burnout varies considerably. In contrast, differences in self-efficacy (personal and general teaching efficacy) and in professional development are minor, reflecting a degree of consistency across teachers. Table 2. Mean, standard deviation, and Pearson correlations Construct M SD Bur PTE GTE PD Bur 2.712 0.726 1 PTE 3.496 0.652 −0.186** 1 GTE 3.630 0.583 −0.197** 0.745** 1 PD 3.521 0.643 −0.151* 0.674** 0.717** 1 Open in a new tab Bur burnout, PTE personal teaching efficacy, GTE general teaching efficacy, PD professional development * p < 0.05, ** p < 0.01 Table 2 also shows significant correlations among professional burnout, self-efficacy (personal teaching and general teaching self-efficacy), and professional development. Job burnout showed a significant negative correlation with personal teaching efficacy ( r = –0.186, p < 0.01) and general teaching efficacy ( r = –0.197, p < 0.01). In comparison, the negative correlation between professional burnout and professional development was also significant but relatively weaker ( r = –0.151, p < 0.05). Among the self-efficacy variables, personal teaching efficacy ( r = 0.674, p < 0.01) and general teaching efficacy ( r = 0.717, p < 0.01) both showed significant positive correlations with professional development. Moreover, personal and general teaching efficacy showed a strong positive correlation ( r = 0.745, p < 0.01). Figure 2 shows that x 2 /df = 1.601 (< 5.0), CFI = 0.960 (≥ 0.9), GFI = 0.883 (≥ 0.9), IFI = 0.961 (≥ 0.9), TLI = 0.955 (≥ 0.9), and RMSEA = 0.048 (≤ 0.08). The mediation model demonstrated good fit, indicating the validity of this chained mediation model. The structural equation model accounted for 68.1% of the variance in professional development (R 2 = 0.681), indicating moderate to strong explanatory power. In addition, the model explained 4.8% of the variance in personal teaching efficacy and 74.4% of the variance in general teaching efficacy. Consistent with the SEM results, additional multiple regression analysis confirmed the model's strong predictive power for teachers' professional development ( F = 106.619, p < 0.001), explaining 55.7% of the variance (R 2 = 0.557). These two methods have significant explanatory power, further indicating that general teaching efficacy exerts a greater influence on teachers' professional development than personal teaching efficacy. Compared to confidence in personal teaching abilities, teachers' belief in actively participating in collective teaching activities and their broad belief in routine teaching practices appear to stimulate teachers' digital professional development. This finding underscores the importance of collective efficacy and teamwork in digital professional development. Differences between bivariate correlations and structural path coefficients reflect the multivariate nature of SEM, where shared variance among predictors is controlled. Fig. 2. Open in a new tab Structural equations and standardized path coefficients The mediating role of self-efficacy between professional burnout and professional development. The structural equation model specified job burnout as the independent variable, teachers' digital professional development as the dependent variable, and self-efficacy as the mediator, with personal and general teaching efficacy included as chain-mediating variables. First, the model examined how job burnout and self-efficacy influenced teachers' digital professional development. Figure 2 and Table 3 report the standardized path coefficients, standard errors, and significance levels. Table 3. Path Coefficient Results Parameter path Estimate S.E C.R P Bur → PTE −0.219 0.058 −3.008 ** Bur → GTE −0.041 0.040 −0.806 0.420 PTE → GTE 0.853 0.083 10.042 *** GTE → PD 0.664 0.149 4.843 *** Bur → PD 0.026 0.042 0.526 0.599 PTE → PD 0.187 0.135 1.482 0.138 Open in a new tab Bur burnout, PTE personal teaching efficacy, GTE general teaching efficacy, PD professional development ** p < 0.01;*** p < 0.001 Results indicate that job burnout did not directly or significantly predict professional development (β = 0.026, p = 0.559) and general teaching efficacy (β = −0.041, p = 0.42). In contrast, job burnout had a significant negative effect on personal teaching efficacy (β = −0.219, p < 0.01). Personal teaching efficacy, in turn, strongly predicted general teaching efficacy (β = 0.853, p < 0.001). Of the two self-efficacy dimensions, personal teaching efficacy did not significantly predict digital professional development (β = 0.187, p = 0.138), whereas GTE showed a strong positive effect on PD (β = 0.664, p < 0.001). The findings suggest that teachers' professional development is more effectively promoted through collective or general teaching activities. Personal teachers' confidence in their instructional abilities does not directly enhance their professional growth. Instead, it may affect professional development indirectly through multiple pathways, including general teaching efficacy, collaborative interactions among teachers, adaptive strategies, and administrative support (all of which together shape the broader teaching environment). Bootstrap Mediating Result. Table 4 presents the mediating role of self-efficacy in the relationship between professional burnout and teachers' digital professional development. The results identify five mediating paths. Personal teaching efficacy significantly mediated the relationship between professional burnout and general teaching efficacy (β = –0.186, p = 0.008, 95% CI [–0.324, –0.047]). Research indicates that the higher the level of teacher burnout, the lower the personal teaching effectiveness, which in turn further reduces overall teaching effectiveness. The total effect of burnout on general teaching efficacy is significant (β = −0.227, p = 0.018), but the direct effect is not significant (β = −0.041, p = 0.491). Therefore, personal teaching efficacy fully mediates the relationship between burnout and general teaching efficacy, accounting for 81.9% of the effect Proportion. Table 4. Bootstrap Mediating Role of Self-Efficacy in the Relationship Between Professional Burnout and Digital Professional Development Effect path Beta SE P 95% CI EP Lower Upper SDE Bur → GTE −0.041 0.055 0.491 −0.145 0.071 81.9% SIE Bur → PTE → GTE −0.186 0.071 0.008 −0.324 −0.047 STE Bur → GTE −0.227 0.094 0.018 −0.404 −0.039 SDE PTE → PD 0.187 0.158 0.219 −0.146 0.468 75.1% SIE PTE → GTE → PD 0.566 0.145 *** 0.335 0.903 STE PTE → PD 0.753 0.043 *** 0.667 0.831 SDE Bur → PD 0.022 0.048 0.676 −0.085 0.137 74.6% SIE Bur → PTE → PD −0.035 0.035 0.122 −0.128 0.014 Bur → GTE → PD −0.023 0.035 0.452 −0.103 0.035 Bur → PTE → GTE → PD −0.106 0.054 0.006 −0.240 −0.025 Tot indirect effect −0.164 0.073 0.011 −0.325 −0.037 STE Bur → PD −0.142 0.087 0.074 −0.328 0.013 Open in a new tab SE standard error, SDE Standardized Direct Effects, SIE Standardized Indirect Effect, STE Standardized Total Effect, EP Effect Proportion, Bur burnout, PTE personal teaching efficacy, GTE general teaching efficacy, PD professional development *** p < 0.001 General teaching efficacy fully mediated the relationship between personal teaching efficacy and professional development (β = 0.566, p < 0.001, 95% CI [0.335, 0.903]), whereas the direct effect of personal teaching efficacy on professional development was not significant (β = 0.187, p = 0.219). Effect Proportion is 75.1%. This indicates that personal teaching efficacy contributes to professional development primarily by influencing general teaching efficacy. In the chain-mediated model, the total indirect effect of the three self-efficacy pathways is significant (β = −0.164, p = 0.011). Including neither personal teaching efficacy nor general teaching efficacy alone significantly mediated the relationship between burnout and professional development (β = –0.035, p = 0.122; β = –0.023, p = 0.452, respectively). However, personal and general teaching efficacy together formed a significant chain-mediating pathway between professional burnout and professional development (β = –0.106, p = 0.006, 95% CI [–0.240, –0.025]), accounting for 74.6% of the effect proportion. Collectively, these results confirm that self-efficacy plays a meaningful mediating role in the relationship between burnout and digital professional development among physical education teachers, primarily through a sequential mediation mechanism. Discussion This study examines the relationship between job burnout and professional development, with a particular focus on the chained mediating effects of the individual and general teaching dimensions of self-efficacy. The correlation analysis shows significant relationships among burnout, professional development, and self-efficacy. The findings extend existing literature by revealing that general teaching efficacy (GTE), rather than personal teaching efficacy (PTE), plays a central mediating role, and that a sequential pathway from burnout to professional development via PTE and GTE provides a more nuanced explanatory mechanism. Physical education teachers in higher education institutions in Henan Province can reduce job burnout by strengthening their self-efficacy and improving their professional development. Relationship between teacher burnout and professional development The correlation analysis shows a significant negative relationship between teachers' professional burnout and their professional development. This finding is generally consistent with previous research suggesting that professional burnout may constrain teachers' professional development. Digital physical education programs impose greater expectations on physical education teachers, potentially increasing their stress levels and the likelihood of professional burnout. Burnout has been associated with reduced teaching quality, slower improvements in instructional standards, and challenges in advancing school physical education. Professional development can be understood either as a key pathway for enhancing individual competence or as a process that requires considerable resources to improve the overall capability of the teaching workforce. Consistent with these results, a moderate positive correlation was found between teachers' personal sense of accomplishment and professional development, whereas depersonalization showed a slight negative correlation [ 69 , 70 ]. Physical education teachers report concerns about limited professional development opportunities, which may further relate to occupational burnout. Experimental research shows that providing teachers with online stress management programs, including coping strategies and social-emotional skills training, can reduce burnout while enhancing teaching efficacy and professional satisfaction [ 71 ]. In contrast, in the structural equation model, professional burnout did not directly predict professional development. Instead, its influence operated through a chain-mediated pathway involving self-efficacy, including both personal and general teaching efficacy. This finding adds nuance to prior research, suggesting that although burnout is correlated with professional development, its effect may not be directly exerted at the behavioral level. Professional development is a continuous and cumulative process, whereas professional burnout may represent a relatively short-term psychological state. Consequently, transient experiences of burnout may not directly or persistently determine engagement in professional development. In digital teaching contexts, physical education teachers' burnout may relate to lower professional confidence and reduced readiness to adapt to new tools, upgrade skills, and participate in continuous learning [ 72 , 73 ].Teachers with higher burnout levels tend to report lower willingness and participation in school-based and external professional learning activities, such as workshops, teaching research, and curriculum studies [ 74 ]. Additional evidence confirms that burnout is a significant negative predictor of motivation and participation in professional activities [ 75 ]. Teachers with low engagement and high burnout often lag behind other groups in career development involvement, training absorption, and contributions to teaching research [ 76 ]. However, some contrasting perspectives exist. Analyses based on personality and relational stress reveal that the “high stress/high burnout” group shows the highest engagement in professional development activities, suggesting that burnout does not necessarily inhibit professional growth and that individual coping mechanisms may play a critical role [ 77 , 78 ]. Overall, substantial empirical evidence suggests that burnout may reduce teachers' willingness and effectiveness in professional development under certain conditions. At the same time, contextual and individual factors may alter this relationship, offering new avenues for future research. Relationship between self-efficacy and professional development This study found a significant positive correlation between self-efficacy and professional development in university physical education teachers, indicating that teachers with high self-efficacy can promote their own professional development. Existing research indicates that self-efficacy motivates teachers to engage more actively and effectively in professional development (PD) [ 79 ]. Compared to teachers with lower general teaching efficacy, those with higher efficacy adopt more comprehensive and inclusive approaches to understanding students' needs and demonstrate more decisive leadership in their professional growth, rather than acting as passive recipients [ 80 ]. At the same time, the importance of self-efficacy beliefs in teacher professional development has been confirmed, as these beliefs significantly shape teachers' attitudes toward research [ 81 ]. A key finding of this study is that individual teaching beliefs do not directly drive professional development; instead, they must be transformed into higher-order beliefs about overall teaching effectiveness to promote teachers' digital professional growth. From a social cognitive theory perspective, self-efficacy provides the psychological foundation for action, but it does not automatically translate into tangible behaviors, particularly in the context of digital teaching. Bandura [ 11 ] emphasized that personal self-efficacy requires shaping and amplification within social contexts, collective goals, and institutional support to guide behavior effectively. In the organizational culture of Chinese universities, factors such as peer collaboration, leadership support, and institutional incentives are especially critical. Empirical evidence shows that faculty professional development in Chinese higher education is strongly influenced by organizational culture, including collective objectives, team-based initiatives, evaluation systems, and administrative guidance [ 82 ]. Consequently, when individual beliefs remain isolated from organizational practices, their capacity to directly foster professional development is limited. In the present study, personal teaching efficacy significantly predicted general teaching efficacy, which in turn had a substantial effect on faculty professional development. This finding aligns with the multi-level structure theory of teacher efficacy: personal teaching efficacy reflects confidence in one's instructional skills, while general teaching efficacy encompasses broader professional beliefs about teaching quality, student outcomes, and the overall value of teaching [ 83 ]. At the micro level, personal teaching efficacy involves mastery of subject knowledge, instructional techniques, and classroom management. In the context of China's rapidly developing digital education landscape, teachers must not only possess strong domain expertise but also develop advanced competencies in digital instructional design, cross-disciplinary collaboration, and reflective practice to effectively engage in professional development [ 84 ]. In summary, although multiple studies support the relationship between teacher professional development and self-efficacy, its effectiveness depends on factors such as the professional development itself, the implementation context, and individual differences. Further validation and deeper exploration of this relationship across diverse educational contexts remain necessary. Mediating role of self-efficacy in the relationship between teacher burnout and professional development The outcomes of this study suggested that self-efficacy mediated the relationship between teacher burnout and professional development, extending the Job Demands-Resources (JD-R) model in the context of digital teaching. This finding indicates that professional burnout among physical education teachers reduces motivation and behaviours related to professional development by lowering self-efficacy (indirect path) and directly suppressing professional development [ 72 ]. Consistent with prior research, teachers' self-efficacy negatively correlates with three dimensions of burnout: emotional exhaustion, depersonalization, and reduced personal accomplishment [ 70 , 85 ]. Higher self-efficacy is associated with lower susceptibility to burnout, whereas lower self-efficacy is associated with greater vulnerability [ 35 , 86 , 87 ]. Moreover, self-efficacy demonstrates protective and mediating effects across various professional fields. However, a complex interplay of psychological, organizational, and environmental factors influences professional development. Therefore, relying solely on a single mediating factor, such as self-efficacy, cannot fully explain all observed variations [ 88 , 89 ]. Consequently, although the indirect effects were statistically significant, they should be interpreted within a broader contextual framework that acknowledges additional influencing factors. From the JD-R model perspective, occupational burnout reflects psychological resource depletion caused by excessive job demands and insufficient personal resources. This negative emotion impedes the optimal utilization of work resources, thereby undermining teachers' professional development. Self-efficacy, as a critical personal resource within this model, mediates the relationship between burnout and professional development. Although the overall direct effect remained non-significant, the chained mediation process significantly clarified how burnout may influence professional development through efficacy beliefs. Li et al. [ 90 ] found that teachers' self-efficacy significantly mitigates the negative effects of emotional exhaustion on work outcomes. However, it cannot fully account for the influence of professional burnout on all professional development indicators. It is worth noting that although enhancing self-efficacy among university physical education teachers may partially buffer the negative influence of burnout on professional development, it is unlikely to entirely offset this effect. Professional development activities in digital teaching contexts, such as digital technology training and digital teaching seminars, can strengthen teachers' self-efficacy and reduce the direct inhibitory effect of burnout on professional development [ 72 ]. Within the JD-R model framework, low psychological resources indirectly affect teachers' professional development through the mediating role of self-efficacy. At the same time, sufficient job resources and reasonable job demands can reduce teachers' professional burnout, strengthen their motivation for professional development, and help them realise their teaching value [ 17 , 39 , 91 , 92 ]. Based on these research findings, enhancing teachers' self-efficacy and reducing burnout are key pathways to improving the digital professional development of physical education teachers. As university physical education teachers increase their self-efficacy, their level of professional development is also expected to rise. Schools and sports management departments should provide tangible teaching resources along with emotional and professional support, thereby continuously strengthening teachers' self-efficacy and motivating them to engage in professional development. University physical education teachers should likewise recognize the importance of self-efficacy, proactively respond to diverse challenges, continuously acquire new knowledge, and actively work to enhance their own sense of self-efficacy. Conclusion This study found that self-efficacy and job burnout significantly influence teachers' professional development during digital transformation. The integration of digital technologies, such as motion analysis systems, wearable devices, virtual simulation platforms, and online teaching resources, into physical education instruction has heightened teachers' technical, cognitive, and pedagogical demands. These demands have led many educators to experience professional burnout, which may hinder their professional growth. To address these challenges, higher education institutions should implement specialized digital professional development programs for physical education, focusing on enhancing teachers' technology-assisted instructional skills and data-driven performance evaluation capabilities. Additionally, optimizing teaching workloads, strengthening technical support services, and fostering collaborative learning communities among physical education teachers can alleviate burnout and enhance digital self-efficacy, thereby promoting sustainable professional development. Relevant school departments should provide adequate resources for physical education, continuously support the professional development of physical education teachers, and ensure the smooth implementation of physical education programs. Limitations and future research This study offers several strengths, including the identification of key factors influencing the professional development of university physical education teachers and the clarification of the mediating role of self-efficacy. However, it also contains several limitations and suggests important directions for future research. First, the participants came from a single province, which limits the generalizability and broader applicability of the findings and may reflect the influence of regional and cultural contextual factors. Future research should adopt multi-regional sampling, include primary and secondary school physical education teachers, and consider differences in instructional orientations (e.g., skill-based vs. theory-oriented), which may influence teaching demands and professional development needs. Second, the study's cross-sectional design limits causal inference and the understanding of developmental changes over time. Future research should adopt longitudinal or experimental designs to examine the temporal dynamics of the proposed chain mediation mechanism. Third, the reliance on self-report measures may introduce standard-method variance and social desirability bias, thereby reducing objectivity. Future studies should incorporate more objective measurement tools, such as mixed-methods research designs, to obtain more accurate and reliable data. These may include classroom observations, peer evaluations, administrative records, and qualitative interviews to get a more comprehensive and objective assessment of teachers' professional development processes. Authors’ contributions Conceptualization: LM, PL, and CSC; methodology: LM, PL, CSC, and SA; data collection: LM, CSC, SA; formal analysis: LM, PL, and CSC; writing original draft preparation: LM and PL; writing—review and editing: PL and CSC; supervision: CSC. Funding There is no funding support. Data availability All data analyzed during this study are included in this published article and its supplementary information files. Declarations Ethics approval and consent to participate This study received ethical approval from the Ethics Committee of Universiti Putra Malaysia (Approval No. JKEUPM-2023–701).All participants provided informed consent for their involvement in the study and for the use of their contributions in publications. All surveys were conducted in accordance with the Declaration of Helsinki and the relevant laws and regulations of the People's Republic of China. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Footnotes Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Contributor Information Chen Soon Chee, Email: cschee@upm.edu.my. Pan Liu, Email: 498836060@qq.com. References 1. Deng C, Yu Q, Luo G, Zhao Z, Li Y. Big data-driven intelligent governance of college students’ physical health: system and strategy. Front Public Health. 2022;10:924025. 10.3389/fpubh.2022.924025. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 2. Liu L. Research on Information Resource Construction of Aerobics Courses in Universities under the Background of Educational Big Data. Journal of Physics: Conference Series. 2020;1574(1). 10.1088/1742-6596/1574/1/012120. 3. Du S, Han N, Feng Y. Study on the Reform and Development of Modern Physical Education Teaching Based on 5G Internet Communication Technology. Computational Intelligence and Neuroscience : CIN, 2022; 2022. 10.1155/2022/5604141. [ DOI ] [ PMC free article ] [ PubMed ] [ Retracted ] 4. Khan F, Rasli AM, Khan S, Yasir M, Malik MF. Job burnout and professional development among universities academicians. Sci Int Lahore. 2014;26(4):1693–6. [ Google Scholar ] 5. DeMonte J. High-Quality Professional Development for Teachers: Supporting Teacher Training to Improve Student Learning. Center for American Progress. 2013. 6. Karimi J, Karimi M, Mahmoudi S. Teachers’ attitudes toward modern physical education utilizing the transformative potentials of artificial intelligence. Research on Educational Sport. 2025;12(37):87–110. [ Google Scholar ] 7. Martín-Rodríguez A, Madrigal-Cerezo R. Technology-enhanced pedagogy in physical education: bridging engagement, learning, and lifelong activity. Educ Sci. 2025;15(4):409. [ Google Scholar ] 8. Dong Y, Xu C, Chai CS, Zhai X. Exploring the structural relationship among teachers’ technostress, technological pedagogical content knowledge (TPACK), computer self-efficacy and school support. Asia Pac Educ Res. 2020;29(2):147–57. [ Google Scholar ] 9. Filho RAC, Iaochite RT. Constitution of self-efficacy in the early career of physical education teachers. J Phys Educ Sport. 2018;2018(04):2410–6. 10.7752/jpes.2018.04363. [ Google Scholar ] 10. Li W, Manoharan P, Cui X. Self-efficacy and professional development: an investigation of music teachers in primary and secondary schools in CHINA. Int J Educ Pract. 2022;10(2):171–81. 10.18488/61.v10i2.3005. [ Google Scholar ] 11. Bandura A. Social cognitive theory of moral thought and action. In Handbook of moral behavior and development (pp. 45–103). Psychology press. 2014. 12. Bandura A, Adams NE. Analysis of self-efficacy theory of behavioral change. Cogn Ther Res. 1977;1(4):287–310. [ Google Scholar ] 13. Bandura A. The explanatory and predictive scope of self-efficacy theory. J Soc Clin Psychol. 1986;4(3):359–73. [ Google Scholar ] 14. van der Want AC, den Brok P, Beijaard D, Brekelmans M, Claessens LCA, Pennings HJM. The relation between teachers’ interpersonal role identity and their self-efficacy, burnout and work engagement. Prof Dev Educ. 2018;45(3):488–504. 10.1080/19415257.2018.1511453. [ Google Scholar ] 15. Knopik T, Domagała-Zyśk E. Predictors of the subjective effectiveness of emergency remote teaching during the first phase of the COVID-19 pandemic. Int Electron J Elem Educ. 2022;14(4):525–38. 10.26822/iejee.2022.261. [ Google Scholar ] 16. Ezza Mad B, Samsilah R, Hassan SA, Krauss SE, Zaremohzzabieh Z. How do self-esteem, dispositional hope, crisis self-efficacy, mattering, and gender differences affect teacher resilience during COVID-19 school closures? Int J Environ Res Public Health. 2022;19(7):4150. 10.3390/ijerph19074150. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 17. Bakker AB, De Vries JD. Job demands–resources theory and self-regulation: new explanations and remedies for job burnout. Anxiety Stress Coping. 2021;34(1):1–21. 10.1080/10615806.2020.1797695. [ DOI ] [ PubMed ] [ Google Scholar ] 18. Granziera H, Collie R, Martin A. Understanding Teacher Wellbeing Through Job Demands-Resources Theory. In (pp. 229–244). Springer Singapore. 2021. 10.1007/978-981-15-5963-1_14. 19. Maslach C, Schaufeli WB, Leiter MP. Job burnout. Annu Rev Psychol. 2001;52(1):397–422. 10.1146/annurev.psych.52.1.397. [ DOI ] [ PubMed ] [ Google Scholar ] 20. Khan F, Khan Q, Kanwal A, Bukhair N. Impact of job stress and social support with job burnout among universities faculty members. Paradigms. 2018;12(2):201–5. 10.24312/paradigms120214. [ Google Scholar ] 21. Arbia G, Carbone A, Stanzione I, Szpunar G. The work-related stress and well-being of teachers—an exploratory study within primary schools in Italy. Educ Sci. 2023;13(5):505. 10.3390/educsci13050505. [ Google Scholar ] 22. Sang G, Yuan C, Wang M, Chen J, Han X, Zhang R. What Causes Burnout in Special School Physical Education Teachers? Evidence from China. Sustainability. 2022;14(20). 10.3390/su142013037. 23. Vidić T, Đuranović M, Klasnić I. Student misbehaviour, teacher self-efficacy, burnout and job satisfaction: evidence from Croatia. Probl Educ 21st Cent. 2021;79(4):657–73. 10.33225/pec/21.79.657. [ Google Scholar ] 24. Hershko-Leibovits N. Teacher Burnout: An Examination of the Relationships Between Professional Development, Self-Efficacy and Enthusiasm. (Publication Number 29192452) [Master's, University of Haifa (Israel)]. ProQuest Dissertations & Theses Global. Israel. 2021. https://www.proquest.com/dissertations-theses/teacher-burnout-examination-relationships-between/docview/2689295643/se-2?accountid=27932 . 25. Geraci A, Laura Di D, Inguglia C, Antonella DA. Teachers’ Emotional Intelligence, Burnout, Work Engagement, and Self-Efficacy during COVID-19 Lockdown. Behav Sci. 2023;13(4):296. 10.3390/bs13040296. [ DOI ] [ PMC free article ] [ PubMed ] 26. Bandura A. Organisational applications of social cognitive theory. Aust J Manag. 1988;13(2):275–302. [ Google Scholar ] 27. Bandura A. Health promotion by social cognitive means. Health Educ Behav. 2004;31(2):143–64. [ DOI ] [ PubMed ] [ Google Scholar ] 28. Granziera H, Collie R, Martin A. Understanding teacher wellbeing through job demands-resources theory. Cultivating teacher resilience. 2021;24(3):229–44. [ Google Scholar ] 29. Granziera H, Collie R, Martin A. Understanding teacher wellbeing through job demands-resources theory. Cultivating teacher resilience, 2021;229–244. 30. Desimone LM. Improving impact studies of teachers’ professional development: toward better conceptualizations and measures. Educ Res. 2009;38(3):181–99. 10.3102/0013189x08331140. [ Google Scholar ] 31. Philipsen B, Tondeur J, Pareja Roblin N, Vanslambrouck S, Zhu C. Improving teacher professional development for online and blended learning: a systematic meta-aggregative review. Educ Technol Res Dev. 2019;67(5):1145–74. 10.1007/s11423-019-09645-8. [ Google Scholar ] 32. Bakker AB, Hakanen JJ, Demerouti E, Xanthopoulou D. Job resources boost work engagement, particularly when job demands are high. J Educ Psychol. 2007;99(2):274. [ Google Scholar ] 33. Huang Y, Huang B, Yang Z. Factors influencing teaching innovation at a university: an extension of the job demands-resources (JD-R) model in the digital age. Higher Education. 2025. 10.1007/s10734-025-01529-6. 34. Admiraal W, Kittelsen Røberg K-I. Teachers’ job demands, resources and their job satisfaction: satisfaction with school, career choice and teaching profession of teachers in different career stages. Teach Teach Educ. 2023;125:104063. 10.1016/j.tate.2023.104063. [ Google Scholar ] 35. Skaalvik EM, Skaalvik S. Job demands and job resources as predictors of teacher motivation and well-being. Soc Psychol Educ. 2018;21(5):1251–75. [ Google Scholar ] 36. Jansen in de Wal J, van den Beemt A, Martens RL, den Brok PJ. The relationship between job demands, job resources and teachers’ professional learning: is it explained by self-determination theory? Stud Contin Educ. 2018;42(1):17–39. 10.1080/0158037x.2018.1520697. [ Google Scholar ] 37. Wang J, Yang Z, Chen X, Chen H. The positive role of teachers’ social-emotional competence in burnout: the mediating effects of teaching efficacy. Front Psychol. 2026;17:1744311. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 38. Bakker AB, Demerouti E. The job demands‐resources model: state of the art. J Managerial Psychol. 2007;22(3):309–28. 10.1108/02683940710733115. [ Google Scholar ] 39. Bakker AB, Demerouti E. Job demands-resources theory: Taking stock and looking forward. J Occup Health Psychol. 2017;22(3):273–85. 10.1037/ocp0000056. [ DOI ] [ PubMed ] [ Google Scholar ] 40. Brown V, Powers J, Olden D. Raising the bar with professional development in the use of distance learning tools. FDLA J. 2020;5(1):3. [ Google Scholar ] 41. Caprara GV, Barbaranelli C, Steca P, Malone PS. Teachers’ self-efficacy beliefs as determinants of job satisfaction and students’ academic achievement: A study at the school level. J Sch Psychol. 2006;44(6):473–90. 10.1016/j.jsp.2006.09.001. [ Google Scholar ] 42. Kavgacı H. The relationship between psychological resilience, teachers’ self-efficacy and attitudes towards teaching profession: a path analysis. Int J Prog Educ. 2022;18(3):278–96. 10.29329/ijpe.2022.439.18. [ Google Scholar ] 43. Zee M, Koomen HMY. Teacher Self-Efficacy and Its Effects on Classroom Processes, Student Academic Adjustment, and Teacher Well-Being. Rev Educ Res. 2016;86(4):981–1015. 10.3102/0034654315626801. [ Google Scholar ] 44. Guskey TR, Passaro PD. Teacher efficacy: a study of construct dimensions. Am Educ Res J. 1994;31(3):627–43. [ Google Scholar ] 45. Dolighan T, Owen M. Teacher Efficacy for Online Teaching During the COVID-19 Pandemic. Brock Educ J. 2021;1(30). 46. Ortan F, Simut C, Simut R. Self-Efficacy, Job Satisfaction and Teacher Well-Being in the K-12 Educational System. Int J Environ Res Public Health. 2021;18(23):12763. 10.3390/ijerph182312763. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 47. Li G, Wang L. Development of job-burnout inventory for P.E. teachers in universities. Jourmal of Beijing Sport University. 2008;31(2):251–2. [ Google Scholar ] 48. Valverde-Berrocoso J, Fernández-Sánchez MR, Revuelta Dominguez FI, Sosa-Díaz MJ. The educational integration of digital technologies preCovid-19: Lessons for teacher education. PLoS ONE. 2021;16(8):e0256283. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 49. Pan Y-H. The Development of a Teachers-Self-Efficacy Instrument for High School Physical Education Teacher. Int J Educ Pedagog Sci. 2012;6(6):1583–8. [ Google Scholar ] 50. Kline RB. Principles and practice of structural equation modeling. Guilford publications. 2023. 51. Fritz MS, MacKinnon DP. Required sample size to detect the mediated effect. Psychol Sci. 2007;18(3):233–9. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 52. Preacher KJ, Hayes AF. Asymptotic and resampling strategies for assessing and comparing indirect effects in multiple mediator models. Behav Res Methods. 2008;40(3):879–91. [ DOI ] [ PubMed ] [ Google Scholar ] 53. Li K, Xu X, Zhang Y, Xu X. The influence of environmental factors on the job burnout of physical education teachers in tertiary education. Sci Rep. 2024;14(1):9126. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 54. Bandura A. Self-efiicacy: The exercise ofcontrol. New York: Freeman; 1997. [ Google Scholar ] 55. Field A. Discovering statistics using IBM SPSS statistics. Sage publications limited. 2024. 56. Kwak SG, Park S-H. Normality test in clinical research. J Rheum Dis. 2019;26(1):5–11. [ Google Scholar ] 57. Kim HY. Statistical notes for clinical researchers: assessing normal distribution (2) using skewness and kurtosis. Restor Dent Endod. 2013;38(1):52–4. 10.5395/rde.2013.38.1.52. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 58. Demir S. Comparison of normality tests in terms of sample sizes under different skewness and kurtosis coefficients. Int J Assess Tools Educ. 2022;9(2):397–409. [ Google Scholar ] 59. Hesterberg T. Bootstrap. Wiley Interdiscip Rev Comput Stat. 2011;3(6):497–526. [ Google Scholar ] 60. Hair JF, Black WC, Babin BJ, Anderson RE. Multivariate data analysis. In: Cengage Learning EMEA. 2019. 61. Singh K, Xie M. Bootstrap: a statistical method. Unpublished manuscript, Rutgers University, USA. 2008. Retrieved from http://www.stat.rutgers.edu/home/mxie/RCPapers/bootstrap.pdf , 1–14. 62. Hair J. Multivariate data analysis: A global perspective (Vol. 7). 2010. 63. Hajjar S. Statistical analysis: internal-consistency reliability and construct validity. Int J Quan Qual Res Methods. 2018;6(1):27–38. [ Google Scholar ] 64. Alarcón D, Sánchez JA, De Olavide U. Assessing convergent and discriminant validity in the ADHD-R IV rating scale: User-written commands for Average Variance Extracted (AVE), Composite Reliability (CR), and Heterotrait-Monotrait ratio of correlations (HTMT). Spanish STATA meeting, 2015. 65. dos Santos PM, Cirillo MÂ. Construction of the average variance extracted index for construct validation in structural equation models with adaptive regressions. Commun Stat Simul Comput. 2023;52(4):1639–50. [ Google Scholar ] 66. Aguirre-Urreta MI, Hu J. Detecting common method bias: performance of the Harman’s single-factor test. ACM SIGMIS database: the DATABASE for Advances in Information Systems. 2019;50(2):45–70. [ Google Scholar ] 67. Afthanorhan A, Awang Z, Abd Majid N, Foziah H, Ismail I, Al Halbusi H, Tehseen S. Gain more insight from common latent factor in structural equation modeling. J Physics: Conference Series. 2021. 68. Eichhorn BR. Common method variance techniques. Cleveland State University, Department of Operations & Supply Chain Management. Cleveland, OH: SAS Institute Inc, 2014;1(11). 69. Özer N, Beycioglu K. The relationship between teacher professional development and burnout. Procedia Soc Behav Sci. 2010;2(2):4928–32. 10.1016/j.sbspro.2010.03.797. [ Google Scholar ] 70. Ozer N, Beycioglu K. The relationship between teacher professional development and burnout [Proceedings Paper]. Innov Creat Educ. 2010. 10.1016/j.sbspro.2010.03.797. 71. Ansley BM, Houchins DE, Varjas K, Roach A, Patterson D, Hendrick R. The impact of an online stress intervention on burnout and teacher efficacy. Teach Teach Educ. 2021;98:103251. [ Google Scholar ] 72. Ma L, Chee CS, Amri S, Gao X, Wang Q, Wang N, et al. Impact of self-efficacy and burnout on professional development of physical education teachers in the digital age: a systematic review. PeerJ. 2025;13:e18952. 10.7717/peerj.18952. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 73. Heppe D, Baduashvili A, Limes JE, Suddarth K, Mann A, Gottenborg E, et al. Resident burnout, wellness, professional development, and engagement before and after new training schedule implementation. JAMA Netw Open. 2024;7(2):e240037–e240037. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 74. Kulavuz-Onal D, Tatar S. Teacher burnout and participation in professional learning activities: perspectives from university English language instructors in Turkey. J Lang Linguist Stud. 2017;13(1):283–303. [ Google Scholar ] 75. Zhang X, Admiraal W, Saab N. Teachers’ motivation to participate in continuous professional development: relationship with factors at the personal and school level. J Educ Teach. 2021;47(5):714–31. 10.1080/02607476.2021.1942804. [ Google Scholar ] 76. Holmström A, Tuominen H, Laasanen M, Veermans M. Teachers’ work engagement and burnout profiles: associations with sense of efficacy and interprofessional collaboration in school. Teach Teach Educ. 2023;132:104251. 10.1016/j.tate.2023.104251. [ Google Scholar ] 77. Lee BY, Park S-Y, Yujung Hong. Differences in Teacher Burnout and Professional Development Activities According to Relationship Stress Profiles in Elementary School Teachers [Differences in Teacher Burnout and Professional Development Activities According to Relationship Stress Profiles in Elementary School Teachers]. J Educ Res. 2025;63(1):277–321. 10.30916/KERA.63.1.277. 78. Hlado P, Juhaňák L, Harvankova K. The roles of burnout, self-rated health, and teacher self-efficacy in fostering perceived teacher work ability. Hum Soc Sci Commun. 2025;12(1). 10.1057/s41599-025-05603-3. 79. Noor S, Adnan M, Rehman L, Shafiq A. The impact of leadership styles on teacher self-efficacy and professional development. Bulletin of Business and Economics (BBE). 2024;13(3):248–55. [ Google Scholar ] 80. Woodcock S, Hardy I. Teacher self-efficacy, inclusion and professional development practices: cultivating a learning environment for all. Prof Dev Educ. 2023;51(5):890–904. 10.1080/19415257.2023.2267058. [ Google Scholar ] 81. Tekin O. The mediating role of teacher self-efficacy in predicting teachers’ research attitudes. Teach Dev. 2023;27(3):314–32. 10.1080/13664530.2023.2201579. [ Google Scholar ] 82. Cai Y, Wang L, Bi Y, Tang R. How can the professional community influence teachers’ work engagement? The mediating role of teacher self-efficacy. Sustainability. 2022;14(16):10029. [ Google Scholar ] 83. Luo X, Alias BS, Adnan NH. Exploring the interplay between teacher leadership and self-efficacy: a systematic literature review (2013–2024). Educ Sci. 2024;14(9):990. [ Google Scholar ] 84. Sun M, Feng Z, Xiao L. The relationship between home-kindergarten-community collaboration and socioemotional competence among Chinese preschoolers: the chain mediating roles of principals’ transformational leadership and teachers’ socioemotional competence. Front Psychol. 2025;16:1647323. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 85. Zysberg L, Maskit D. Teachers’ professional development, emotional experiences and burnout. J Adv Educ Res. 2017;2(4):287–300. [ Google Scholar ] 86. Skaalvik EM, Skaalvik S. Teacher self-efficacy and teacher burnout: a study of relations. Teach Teach Educ. 2010;26(4):1059–69. [ Google Scholar ] 87. Li S. The effect of teacher self-efficacy, teacher resilience, and emotion regulation on teacher burnout: a mediation model. Front Psychol. 2023;14:1185079. [ DOI ] [ PMC free article ] [ PubMed ] [ Google Scholar ] 88. Li S. The effect of teacher self-efficacy, teacher resilience, and emotion regulation on teacher burnout: a mediation model. Front Psychol. 2023;14. 10.3389/fpsyg.2023.1185079. [ DOI ] [ PMC free article ] [ PubMed ] 89. Li Y. A Study on the Relationship Between Social Support, Self-Efficacy, and Job Satisfaction Among Secondary School Physical Education Teachers in Henan Province [Master's Degree, Henan University]. 2023. https://kns.cnki.net/KCMS/detail/detail.aspx?dbname=CMFD202401&filename=1023810245.nh . 90. Liman Kaban A, Kaynar N. Too much screen? An exploratory examination of digital exhaustion of educators in Turkiye. Turk Online J Distance Educ. 2023;24(1):54–73. 10.17718/tojde.1071640. [ Google Scholar ] 91. Fiorilli C, Gabola P, Pepe A, Meylan N, Curchod-Ruedi D, Albanese O, et al. The effect of teachers’ emotional intensity and social support on burnout syndrome. A comparison between Italy and Switzerland. Eur Rev Appl Psychol. 2015;65(6):275–83. 10.1016/j.erap.2015.10.003. [ Google Scholar ] 92. Fiorilli C, Buonomo I, Romano L, Passiatore Y, Iezzi DF, Santoro PE, et al. Teacher confidence in professional training: the predictive roles of engagement and burnout. Sustainability. 2020;12(16):6345. 10.3390/su12166345. [ Google Scholar ] Associated Data This section collects any data citations, data availability statements, or supplementary materials included in this article. Data Availability Statement All data analyzed during this study are included in this published article and its supplementary information files. 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