A Longitudinal Study on Emotional Burnout Among Novice Early Childhood Education Teachers: Change from Entry to 24 months

A Longitudinal Study on Emotional Burnout Among Novice Early Childhood Education Teachers: Change from Entry to 24 months | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article A Longitudinal Study on Emotional Burnout Among Novice Early Childhood Education Teachers: Change from Entry to 24 months Fan Pan, Yuhong Lei, Qiuxia Guo This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6884218/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 09 Jan, 2026 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract In early childhood education, the emotional well-being of teachers plays a crucial role in fostering the development of children. Emotional burnout, a significant indicator of teachers’ mental health, affect both their teaching effectiveness and the interaction with children. Consequently, a comprehensive longitudinal examination of the emotional burnout among novice early childhood education (ECE) teachers is important for enhancing ECE quality and promoting the professional and mental well-being of educators. The purpose of this study was to examine the trajectory of emotional burnout among novice ECE teachers over a period of 24 months. We employed Growth Mixed Model (GMM) to measured emotional burnout trends of 2,455 novice ECE teachers over a 24-month period after they just entry into the profession. The emotional burnout contains three domains: emotional exhaustion (EE), depersonalization (DP), and reduced personal accomplishments (PA). The study also examined the impact of education background, rural or urban preschool, gender, and have internship or not, on novice ECE teachers’ emotional burnout. The findings contribute to the existing theoretical framework on emotional burnout and provide effective intervention strategies to reduce the incidence of emotional burnout, enhancing the overall quality of ECE. Biological sciences/Psychology Health sciences/Health occupations Emotional burnout Novice ECE Teachers Growth Mixed Model Figures Figure 1 Figure 2 Figure 3 Introduction Early Childhood Education (ECE) teachers are essential in developing children's cognitive ability, emotional ability, and social skills. With the increasing expectations from families, communities, and society, ECE teachers are encountering unprecedented pressures and challenges (Stein, R., Garay, M., & Nguyen, A. 2024 ; Purper, C. J et al. 2023 ; Ntim, S. Y., et al. 2023). These challenges include the diversification demands of ECE, heightened social expectations, and significant changes in the educational environment brought about by the digital era (Goodwin, A. L., & Low, E. L., et al., 2019). Li et al. ( 2021 ) highlighted that ECE teachers are particularly susceptible to physical and mental exhaustion due to the high pressure nature of their work environment. This high pressure environment often results in ECE teachers’ emotional fatigue and a diminished enthusiasm. Furthermore, the inherent demands of ECE require teachers to sustain a high level of commitment and focus over extended periods. However, ECE teachers’ dedication was always unrecognized and unrewarded, contributing to the diminished sense of teachers’ personal accomplishment (Mischo, 2015 ). Additionally, the multifaceted challenges of ECE requires teachers to possess diverse skills and abilities, including effective communication, organizational and coordination capabilities, as well as innovative teaching strategies (Stein et al., 2024 ). ECE teachers need to devote large amount time and energy to develop and practice these abilities. These challengesAll these professional requirements not only affect ECE teachers’ own physical and mental health but also potentially having a profound impact on children's development (Tuxford, L. M., & Bradley, G. L., 2015; Żołnierczyk-Zreda, D., 2005 ; Klusmann, U., et al., 2008 ). Among these mental problems, emotional burnout is particularly prominent. Emotional burnout can be conceptualized as a dynamic construct that reflects an individual's psychological state and changes over time in response to different job demands (Maslach & Schaufeli, 2017; DeAngelis, K. J., 2013). A lots of previous research have studied emotional burnout, primarily focusing on definition, influencing factors, and potential interventions (McKinley, T. F., et al. 2017 ; Dorman, J., 2003 ; Shaheen, F., 2018 ; Shaheen, F., & Mahmood, N., et al. 2016). The concept of emotional burnout was first introduced by Maslach and Jackson in 1981 and is recognized as one of the three core dimensions of a person’s overall burnout. Shaheen ( 2018 ) and Ansari (2022) suggested that emotional burnout is characterized by emotional exhaustion, depersonalization, and a diminished sense of accomplishment. Depersonalization is characterized by indifference and alienation to the individuals they serve (Dorman, 2003 ). Decreased sense of accomplishment indicates teachers' negative assessment of their job effectiveness. The emotional burnout is precipitated by various factors, including work pressure, professional challenges, and the disparity between personal expectations and reality. The manifestations of emotional burnout primarily include the unstable emotion situation, a sense of indifference toward work, and feelings of powerlessness. Novice ECE teachers are particularly vulnerable to emotional burnout. According to Thomas et al. ( 2019 ), novice ECE teachers, who just begin their careers and whose passion and motivation for education have yet to solidify, are particularly incline to suffer emotion burnout. Previous studies have indicated that emotional burnout among novice ECE teachers is linked to a variety of factors (Fantilli, R. D., & McDougall, D. E., 2009; Grygas Coogle, C., et al., 2018; Mikser, R., Õun, T., et al., 2021). Given the high requirements of ECE, novice teachers must devote substantial time and energy to form close relationships with children and support their development. If teachers’ energy is not adequately replenished and restored, they are highly likely to suffer emotional burnout after an period (Wiltshire, C. A., 2024 ). Many novice ECE teachers often felt exhausted by the end of the day, resulting in a low level of enthusiasm for their work and prompting them to question their career choices (Li, J. B., & Li, Z., et al., 2021; Hooper, A., et al., 2023 ). Novice ECE teachers often encounter various challenges which significantly contribute to their emotional burnout. Job stress, particularly, is a major contribution factor. DeAngelis, K. J. et al. ( 2013 ) highlights that novice teachers frequently feel overwhelmed by classroom management, parent communication, and daily teaching responsibilities. For instance, novice teachers may experience frustration due to an inability to maintain classroom order. Their frustration can accumulate over time and ultimately result in emotional burnout. Support from family, colleagues, and school administer sis a crucial intervention factor for novice ECE teachers’ emotional burnout (Żołnierczyk-Zreda, D., 2005 ; Hogan, J. P., & White, P., 2021). Teacher's emotional burnout can be significantly mitigated by guidance from an experienced colleague or encouragement from families. Additionally, previous studies revealed significant effects among various demographic information and ECE teachers' emotional burnout (Fiorilli, C., & Benevene, P., et al., 2019) The demographic information including gender, age, education, teaching experience, and academic qualifications and so on (Fisher, 2011). Other factors such as professional background, internship, and preschool’s geographic location are also significant when examining the ECE teachers’ emotional burnout (Faiza Shaheen & Nasir Mahmood, 2016; Núñez del Rosario, P. D., 2020; DeAngelis, K. J., et al., 2013 ). Previous research indicated that female ECE teachers are more vulnerable than male ECE teachers when confronted with the daily job challenges, so female teachers have a higher risk of emotional burnout (Noor, N. M., & Zainuddin, M., 2011). Ansari et al. ( 2022 ) and Chang ( 2009 )’s study suggested that teachers with high educational levels tend to have high expectations and aspirations for their professional development. However, the discrepancy between high expectations and the realities of the work environment can exacerbate feelings of emotional burnout. ECE teacher's professional background also significantly influences their self-efficacy and career satisfaction. Novice teachers who engaged in internship before find it easier to adapt to the teaching environment(Stein, Garay, & Nguyen, 2024 ). Because the internship provide them an deep understanding of educational principles, teaching methods, curriculum design, and a robust knowledge base to address actual teaching problems. So ECE teachers can quickly adapt to the preschool have low risk of emotional burnout. ECE teachers with out internship are unfamiliar with the children's characteristics psychological development and effective teaching methods. Consequently, the new working situation can increase their work-related stress, potentially leading to emotional burnout (Voitenko, E., et al., 2021 ; Ansari, A., 2022). Besides, limited scholars have examined the impact of preschools’ geographic location on the ECE teachers’ emotional burnout. Previous research suggested that a preschool’ geographic location significantly influences a ECE teacher's work environment and access to different educational resources, which in turn affects teacher burnout (DeAngelis, K. J., 2013). Purpose of the study Despite the growing interest in emotional burnout, there is limited empirical research examining changes of emotional burnout specifically among novice ECE teachers (Tuxford & Bradley, 2015 ). Most previous studies employed cross-sectional methods to examine the novice ECE teachers’ emotional burnout. These methods fail to capture the dynamic nature of novice ECE teachers’ emotional burnout over time. Longitudinal studies can track the changes of novice ECE teachers’ emotional burnout, enhancing our understanding of the underlying mechanisms and influencing factors associated with novice ECE teachers’ emotional burnout (Mischo, C., 2015 ). This study aims to fill the research gap and conduct a longitudinal analysis of novice ECE teachers/ emotional burnout. By collecting and analyzing longitudinal data at six intervals, this research seeks to elucidate the patterns of novice ECE teachers’ emotional burnout, and show underlying factors contributing to this pattern. This research aims to categorize the trajectory of novice ECE teachers’ emotional burnout into several distinct patterns. Additionally, the study will examine the influence of demographic factors, including education degree, rural or urban preschool, gender, and have internship or not, on the patterns. With the comprehensively understanding of the change patterns of novice ECE teachers’ emotional burnout, researchers and administers can accurately identify the stages in which the novice ECE teachers are most susceptible to emotional burnout. This study will also as well as the statistical variables that significantly contribute to their emotional depletion. This knowledge will provide a robust foundation for developing targeted interventions.The objective is to propose effective interventions based on these findings. METHOD Procedure and Participants This research investigated dataset from the China National Program for Child Development. The program was developed to provide consolidated early childhood development for children. The program also provide professional development for ECE educators to construct a respect and warm ECE atmosphere. The program includes several dimensions, including Health of Children, Education of Children, Welfare of Children, Children and the Social Environment, and the Legal Protection of Children. It includes 51,700 children and related teachers, parents, and preschools information in different regions and cities from 2013 to 2023. The research protocol and all procedures involving human participants were reviewed and approved by the Huizhou University Institutional Review Board. This study was conducted in accordance with the ethical principles outlined in the Huizhou University`s guidelines and regulations. Informed consent was obtained from all participants included in the study prior to their participation. We got a list of teachers and their related information from the board of the The China National Program for Child Development. ECE teachers were contacted immediately after their enter the preschools and begin their career. When teachers agree to participate the research, we emailed the purpose of the study and detailed privacy policy, along with the informed consent. Then we emailed the online Maslach Burnout Inventory questionnaire to all consenting participants to complete. Finally, we obtained a subsample of 2,455 teachers. Maslach Burnout Inventory was measured at six times points: at 4, 8, 12, 16, 20, and 24 months after starting the job. We administered the first Maslach Burnout Inventory questionair in the middle of October 2021. Response rates for 4, 8, 12, 16, 20, and 24 months for X were 95.27, 74.49, 62.04, 59.22, 53.26, and 48.39%, respectively, Besides, at least 67.8% of teachers had completed three or more Maslach Burnout Inventory, and 38% of teachers had completed all six Maslach Burnout Inventory. Across all teachers, 31% had a bachelor’s degree, 17% had bachelor’s degree above, and 52% has a bachelor’s degree below. The average age of teachers was 25 years old (Standard Deviation = 10.78), ranging from 21 to 28. Most teachers (79.2%, N = 2732) were female. The percentages of teachers work in rural and urban preschools were 51.6 and 48.4. The teachers who has internship in preschools before they officially begin the career is 67.3%, where as 32.7% teachers do not have any experience in ECE before they act as ECE teachers. Besides, 59% teachers in our study have a ECE degree, 28% the teachers have a education related degree (not ECE related), and 13% teachers have non-education related degree. Instruments Burnout was measured using the Maslach Burnout Inventory (MBI), a self-report questionnaire developed to measure burnout and validated in various occupational groups. The MBI has been widely used in the previous studies to evaluate burnout in different professions and is regarded as one of the the important measurements for the evaluation of burnout. The MBI scale has 22 items assessing 3 domains related to burnout: EE (emotional exhaustion), DP (depersonalization), and PA (reduced personal accomplishments). EE includes 9 items assessing the fatigue and emotional depletion of teachers; DP includes 5 items assessing the extent that teachers become cynical towards students; PA includes 8 items assessing the extent that teachers achieves their personal goals. Each item is rated on a on a 7-point Likert scale, indicating how often the respondents experience job-related feelings in specific areas. For items belong to EE and DP, higher score shows high level of severity, whereas for items in PA, low scores are viewed as indicators of burnout.The overall reliability of MBI was 0.81. The Cronbach alpha’s value (α) for EE, DP, and PA was 0.76, 0.73, and 0.90. Analysis We performed GMM analyses with robust maximum likelihood estimation. Thw analysis were conducted using Mplus Version 8.4 (Muthén and Muthén, 2010). We employed Full information maximum likelihood (FIML) to deal with missing data. First of all, we ran three different unconditional GMM for each domain of MBI: no growth model, linear growth model, and non-linear growth model. Then, the the chi-square statistics were used to compare these three models of each domain, and the non-linear unconditional model showed the best fit for each domain. Next, for each domain, we compared 2 class to 5 class non-linear unconditional GMMs to get the non-linear unconditional GMM model with the best number of class. Both the model with all growth factors and the variances freely estimated and models with constrained the variances across the classes are failed to converge. The appropriate unconditional GMM model was structured when the variances for the intercepts, linear, and quadtirc parameters were constrained equal across all classes. To compare the GMM with K classes and GMM with K − 1 classes, several mode fit indices include Akaike Information Criterion (AIC; Akaike, 1973), the Bayesian Information Criterion (BIC; Schwarz, 1978), and the samplesize adjusted BIC (ABIC; Sclove, 1987) were used in our study. Entropy value, Lo–Mendell–Rubin (LMR) and adjusted Lo-Mendell-Rubin likelihood-ratio test (ALRT) were also include in the study (Muthén, 2003 ). K − 1 classes. A significant p-value of LMR and ALRT indicates that the model with K classes is better than the model with K − 1 classes, whereas non-significant p-value shows that the K classes model and K − 1 classes model perform similar. When a model’s entropy value close to 1.0, the model is more suitable for the data we studied. After the appriproate unconditional GMM model was identified, we will investigate predictors and outcomes of each class using the three-step approach in Mplus for each domain of MBI. RESULTS Growth Curve Models For Three Domains The FLML showed that the lowest covariance coverage for the analysed was 0.278, which is larger than the threshold of 0.10. So the missing data in this study are acceptable for model convergence. Firstly, we examined a growth curve model of EE, DP, and PA over 24 months. For EE, model fit values were moderate: χ2(36) = 158.23, p < 0.001, CFI (Comparative Fit Index) = 0.88, TLI (Tucker Lewis Index) = 0.91, RMSEA (Root Mean Squared Error of Approximation) = 0.07, SRMR (standardized root mean square residual) = 0.075. The values of intercept (I = 14.61, p < 0.001), slope (S = 0.39, p = 0.038), and quadratic (Q = 0.42, p = 0.007) are all significant, revealing curvilinear trend of EE with slight upward trend for all participants over time. Besides, the variance of the intercept (w = 9.21, p < 0.001), slope (w = 1.42, p < 0.001), and quadratic (w = 0.03, p < 0.05) is significant, indicating EE contains multiple trajectories during 24 months. For DP, model fit values were large: χ2(36) = 385.53, p < 0.001, CFI (Comparative Fit Index) = 0.95, TLI (Tucker Lewis Index) = 0.96, RMSEA (Root Mean Squared Error of Approximation) = 0.08, SRMR (standardized root mean square residual) = 0.05. The values of intercept (I = 5.21, p < 0.001), slope (S = 0.41, p = 0.005), and quadratic (Q = 0.46, p = 0.001) are all significant, revealing curvilinear trend of DP with slight upward trend for all participants over time. Besides, the variance of the intercept (w = 6.71, p < 0.001), slope (w = 1.82, p < 0.001), and quadratic (w = 0.01, p < 0.05) is significant, indicating DP contains multiple trajectories during 24 months. For PA, model fit values were large: χ2(36) = 418.21, p < 0.001, CFI (Comparative Fit Index) = 0.98, TLI (Tucker Lewis Index) = 0.96, RMSEA (Root Mean Squared Error of Approximation) = 0.08, SRMR (standardized root mean square residual) = 0.06. The values of intercept (I = 23.41, p < 0.001), slope (S = − .36, p = 0.005), and quadratic (Q = 0.51, p = 0.001) are all significant, revealing curvilinear trend of PA with slight downward trend for all participants over time. Besides, the variance of the intercept (w = 13.49, p < 0.001), slope (w = 1.71, p < 0.001), and quadratic (w = 0.06, p < 0.05) is significant, indicating PA contains multiple trajectories during 24 months. GMMs With Different Classes For Three Domains Next, we performed GMMs for to investigate possible class membership for each domain. Table 1 shows the model fit indices for the 1 to 5 class models of EE, DP, and PA. For EE, as shown in the table, all indices decreased from the 1 to 5 class models. The decrements were relatively larger from the 1 to 3 class models than to the 4 to 5 class models, and the decrement of the model fit indices values from the 3 to 5 class models were larger than the 4 to 5 class models. The LMR and ALRT values for the 1 to 3 class models were significant, but not significant for the 4 and 5 class model. Besides, The entropy value for the 3 class models (0.82) was higher than the 2 class (0.78), 4 class (0.79) and 5 class (0.78) models. Also, the model fit indicates that the 4 and 5 class models simply separated one class of the 3 class modes into two and three classes. Thus, based on above statistical information, the 3 class model can be considered most appropriate for the sample. For DP and PA, all indices also decreased from the 1 to 5 class models. The decrements were relatively larger from the 1 to 2 class models than to the 3 to 5 class models, and the decrement of the model fit indices values from the 2 to 5 class models were larger than the 3 to 5 class models. The LMR and ALRT values for the 1 to 2 class models were significant, but not significant for the 4 and 5 class model. Besides, The entropy value for the 2 class models was higher than the 3, 4 and 5 classes models. Also, the model fit indicates that the 3 to 5 class models simply separated one class of the 2 class models into two and three classes. Thus, based on above statistical information, the 2 class model can be considered most appropriate for both the DP and PA domains. Table 1 Model Fit Indices by Number of Classes for Each Domain of MBI Model Fit Indices 1 class 2 classes 3 classes 4 classes 5 classes EE (emotional exhaustion) AIC 19863.87 19632.21 19481.79 19459.25 19326.93 BIC 20135.21 19899.89 19704.39 19683.84 19676.94 ABIC 19925.46 19636.35 19422.36 19393.68 19379.61 Entropy 0.78 0.82 0.79 0.78 ALRT(p-value) 0.02 0.03 0.33 0.32 LMR(p-value) 0.03 0.03 0.31 0.34 DP (depersonalization) AIC 21045.38 19213.56 19187.58 19176.82 19172.74 BIC 21672.84 20392.17 20315.56 20298.48 20291.29 ABIC 21018.93 20015.69 19998.12 19987.84 19982.87 Entropy 0.88 0.81 0.77 0.79 ALRT(p-value) 0.03 0.37 0.34 0.33 LMR(p-value) 0.02 0.31 0.29 0.24 PA (reduced personal accomplishments) AIC 20842.98 19482.12 19412.45 19398.74 19386.43 BIC 21024.21 19652.76 19498.34 19435.76 19421.83 ABIC 20981.24 19821.25 19129.32 19004.87 18997.35 Entropy 0.83 0.77 0.77 0.76 ALRT(p-value) 0.02 0.29 0.31 0.37 LMR(p-value) 0.02 0.26 0.36 0.35 Figure 1 indicates the growth trajectories of EE’s three classes, and Table 2 shows the growth parameters for each class. Class 1 (9 percent, n = 221) showed a relative high intercept and with a steady decrease before 16 months, followed by an steady increase from 16 months to 24 months. We name this class as ‘‘High.’’ Class 2 (26 percent, n = 638) had a moderate intercept with a different growth trajectory to Class High, increasing before 12 months and decreasing from 12 months to 24 months. Class 2 was called as ‘‘Moderates.’’ Finally, Class 3 (65 percent, n = 196) had low initial levels of emotional exhaustion and slightly increased over 24 months. We refer to this class as ‘‘Low .’’ Figure 2 indicates the growth trajectories of the DP’s two classes, and Table 2 also indicates the growth parameters of these two classes. Class 1 (29 percent, n = 712) had high initial levels of reduced personal accomplishments and slightly decreased over 24 months. We refer to this class as ‘‘High.’’ Class 2 (64 percent, n = 1571) had low initial levels of reduced personal accomplishments and moderately increased over 24 months. We call Class 2 as ‘‘Low.’’ Figure 3 indicates the growth trajectories of the PA’s two classes, and Table 2 also includes the growth parameters of these two classes. Class 1 (36 percent, n = 884) has a very high initial level of depersonalization and stead a downward trend over the study period. We refer to this class as ‘‘High”.Class 2 (71 percent, n = 1743) showed low PA level throughout the study period and stead a upward trend over the study period. We call Class 2 as ‘‘Low.’’ Table 2 Growth Parameters for Each Class of Each Domain Class(percent of sample) Intercept Linear slope Quadratic B(SE) B(SE) B(SE) EE (emotional exhaustion) 1(9) 34.12(0.72) −0.16(0.08) 0.01(0.01) 2(26) 20.87(0.15) 0.87(0.16) -0.02(0.005) 3(65) 11.46(0.76) 0.36(0.02) 0.009(0.02) DP (depersonalization) 1(29) 17.95(0.64) -0.92(0.06) 0.04(0.03) 2(71) 6.09(0.36) 0.72(0.15) -0.06(0.02) PA (reduced personal accomplishments) 1(36) 44.28(0.25) -0.24(0.09) 0.008(0.06) 2(64) 17.47(0.61) 0.26(0.02) 0.006(0.01) Next, We investigated predictors of the trajectories of three domains of MBI with Mplus 8.3. Predictors contained education background, rural or urban preschool, biological sex, have ECE experience or not, and degree from 4 months to 24 months. As for EE, females were more likely to be in the ‘‘High’’ class compared with the ‘‘Moderate’’ (b = 2.07, p = 0.01) and ‘‘Low’’ (b = 2.31, p = 0.01) classes. Besides, females were more likely to be in the ‘‘Moderate’’ class compared with the‘‘Low’’class (b = 0.71, p = 0.02). The ‘‘High’’ class had higher numbers of participants working in urban preschools than both the ‘‘Moderate’’ (b = 2.42, p = 0.01) and ‘‘Low’’ classes (b = 1.81, p = 0.04), but lower numbers of teachers with ECE experience (b = -3.98, p = 0.001; b = -3.87, p = 0.001, respectively). In addition, participants with educated related degree (non ECE related) were more likely to be in the‘‘Moderate’’ class than ‘‘Low’’ (b = 2.69, p = 0.007) classes. As for DP, males were more likely to be in the ‘‘High’’ class compared with the ‘‘Low ’’ (b = 2.53, p = 0.007) class. Participants with ECE experience were more likely to be in the ‘High’’ class compared with the ‘‘Low ’’ class (b = 1.79, p = 0.005). The ‘‘High’’ class had higher numbers of participants from urban preschools than ‘‘Low’’ class (b = 2.49, p = 0.001), but lower levels of bachelor’s degree and above (b = -3.98, p = 0.001). Finally for PA, males were also more likely to be in the ‘‘High’’ class compared with the ‘‘Low ’’ (b = 3.26, p = 0.001) class. Participants with bachelor’s degree and above were more likely to be in the ‘High’’ class compared with the ‘‘Low ’’ class (b = 3.71, p = 0.001). The ‘‘High’’ class also had higher numbers of participants from urban preschools than ‘‘Low’’ class (b = 3.09, p = 0.001). Discussion The Growth Curve Models findings indicated that EE and DP exhibited a slight upward trend over time, whereas PA demonstrated a slight downward trend. Romano, L., et al. ( 2021 ) investigated the influence of perceived emotional support on these three domains. Their results indicated that the all three domains exhibited a significant upward trend over time. Novice ECE teachers often have high expectations for their roles in education, aspiring to inspire children's creativity, cultivate their interest in learning, and establish a nurturing educational environment. However, they confront lots of difficulties in daily classroom management, parent communication, and children’s diverse needs after they begin daily work. The daily ECE job is significantly more stressful than they anticipated, resulting in a gradual accumulation of EE. The high work pressure and challenges can lead to the negative attitudes toward both the children and the profession, leading to the high DP level (Morrison, C. M., 2013 ). As for PA, this study the exhibited a slight decline, contradicting Romano, L., et al. ( 2021 )’ s findings. This discrepancy may due to the different sample studied. Romano, L., et al. ( 2021 ) investigated the experienced teachers, whereas this research studied novice teachers. Although novice ECE teachers gradually gain experience and skills, they still encounter challenges due to an inadequate education evaluation system, ambiguous career development opportunities, and lack of effective incentives (Thomas, L., et al., 2019 ). To accurately understand the trajectory of the three domains of emotional burnout, this study employed the GMM as to identify the optimal classification model for each domain. Previous studies showed the developmental trajectories of teachers' emotional burnout due to occupational stress are not singular and fixed. The trajectories exhibit a high degree of individual variation (Brunsting, N. C., Bettini, E., et al., 2023; Tuxford, L. M., et al., 2015). Each teacher's personality traits could significantly influence their coping styles for stress, leading to distinct trajectories in the development of emotional burnout. Zysberg et al. ( 2017 ) and Ding et al. ( 2022 ) have examined the emotional burnout of English teachers and highlight the interplay of personal upbringing, educational background, and psychological resilience as key factors influencing the psychological mechanisms of these educators. Separating novice ECE teachers into multiple class with GMM based on their emotional burnout trajectories has significant practical implications. Based on the GMM, researchers and administers could design individualized interventions tailored to the unique circumstances of each class and effectively alleviate novice ECE teachers’ emotional burnout. Novice ECE teachers' EE can be classified into three distinct trajectory classes: high, medium, and low over the 24-month period. The high class remained relatively high EE level throughout the period. From 0 to 16 months, the high class showed a decreasing trend, and then increase from 16 to 24 months. Teachers in this class could work in preschools that have higher significant job demands than preschools, in which medium and lows classes teachers work(Baran, G., et al., 2010 ). The decreasing tread during the 0–16 month period indicate that these novice ECE teachers in high class gradually adapt to their new work environment and acquire essential educational skills and methods (DeAngelis, K. J., et al., 2013 ). The accumulation of work stress, insufficient emotional support, and inadequate coping strategies could cause the upward trend from the 16 to 24 month (Zysberg, L., et al., 2017 ; Thomas, L., et al., 2019 ). This high class teachers novice ECE requires special attention, along with appropriate support and interventions. The moderate class initially showed moderate level of EE and then significantly increased from 6 to 12 month. This class has highest point around 12 months can then declined back to moderate level from 12 to 24 month. The increasing may be attributed to the limited work experience before entering the profession, coupled with the lack of understanding about how to seek support from others (Lindqvist, H., et al., 2023 ). The subsequent declining for novice EE teachers in moderate class could associated with the gradual adaptation, the establishment of stable professional relationships, and the acquisition of additional experience and skills (DeAngelis, K. J., et al., 2013 ). The low class exhibited consistently low and stable level of EE throughout the period. The novice ECE teachers in the class may possess a high degree of mental toughness and resilience, enabling them to effectively deal with the challenges and pressures associated with their new profession (Kinman, G., et al., 2011 ). Besides, they could effectively employ coping strategies and emotion regulation skills, allowing them to mitigate EE while keep their work ethic standards (Chang, M. L., 2020 ). Chang’s ( 2020 ) study about the relationship between teachers' emotional performance rules, emotion regulation, and burnout in one United States western state indicated that teachers' emotion regulation strategies significantly influenced burnout levels. Novice ECE teachers exhibited a bipolar phenomenon on their levels of DP, which shows teachers’ enthusiasm and dedication to working with children and in ECE. For high class, a steady decline was observed from 0 to 16 month. This decline may be attributed to the accumulation of experience, which enables teachers to gradually adapt to teaching and develop more effective emotion regulation and coping strategies (DeAngelis, K. J., et al., 2013 ; Chang, M. L., 2020 ). After 16 months, DP levels of high class began to rise. Potential explanation factors include the accumulation of job stress, the onset of burnout, or the influence of external circumstances (Zysberg, L., et al., 2017 ; Chang, M. L., 2020 ; Shaheen, F., 2016 ). The low class demonstrated relatively low initial level of DP, and exhibited a consistent increase from 0 to 16 months. This changing pattern may stem from a combination of factors, including the accumulated experience, job-related stress, and the personal characteristics of the teachers, as previously discussed (Goodwin, A. L., et al., 2019 ; Brunsting, N. C., et al., 2023). Notably, while the teachers' levels of DP increased, the overall level still remained relatively low. This finding suggested that the novice ECE teachers in low class were able to sustain passion and commitment to students and educational responsibilities, avoiding excessive depersonalization. Future research should further investigate the underlying reasons for this changing pattern through in-depth analyses from various perspectives, including the personal traits of teachers, their work environments, and the availability of social support. It is imperative to focus on novice ECE teachers whose DP continue to rise and understand the challenges they.To mitigate this increasing, schools and educational administrations could implement appropriate support systems and interventions to assist teachers in maintaining their teaching effectiveness and mental well-being. PA were also categorized into high and low classed. Both class showed relative stability PA levels. Teachers in the high class consistently exhibited high self-efficacy. This high sense of accomplishment may be attributed to the fact that teachers manage effective coping strategies when confronted with the daily challenges of teaching and managing children. A study on K-12 teachers' emotional burnout and emotional work by Chang, M. L. ( 2009 ) noted that effective coping strategies can assist teachers in better managing their emotions and reducing burnout. Their sense of self-efficacy can reduce emotional burnout (Trauernicht, M., et al., 2023 ). In contrast, teachers who demonstrate low PA levels may not possess adaptive skills and positive work attitudes. They may be need development at adjusting their mindsets, maintaining optimism in the face of difficulties, remaining humble about their accomplishments, and identifying opportunities for growth from challenges. These teachers may also be lack skills about exploring available resources, such as mutual support among colleagues, professional training, and family support, to alleviate work-related stress and thus maintain a relatively stable psychological state (Żołnierczyk-Zreda, D., 2005 ).Therefore, it is essential to focus on the personal sense of achievement of novice ECE teachers during their support and training. By offering professional development opportunities, psychological support, and training about effective teaching strategies, researchers and administers can assist these teachers to gain enthusiasm and confidence, ultimately enhancing their career satisfaction and retention. Besides, the study investigated the impact of various demographic variables, include education background, rural or urban preschool, gender, and have internship or not, on novice ECE teachers’ emotional burnout trajectories. The results indicated that these variables significantly influenced the emotional burnout trajectories. These findings corroborate the research conducted by Shaheen, F. and Mahmood, N. ( 2016 ) about the determinants of public school teachers’ emotional burnout. Shaheen, F. and Mahmood, N. ( 2016 ) revealed that gender, district, qualifications, and teaching level significantly affected teachers’ emotional burnout. Núñez del Rosario, P. D. (2020) conducted a study on novice teachers transfered from other field, indicating that teachers' educational backgrounds and work experiences may significantly influence their levels of emotional burnout by impacting their capacity to adapt to and manage their teaching responsibilities. This study indicated that female novice ECE teachers were more likely to be categorized as high or medium EE class. This phenomenon may due to that compared to male, female act as more roles in both their professional and personal lives and encounter more stress (Noor, N. M., & Zainuddin, M., 2011). Female tend to exhibit emotional sensitivity, making them more susceptible to feelings of EE. Male novice ECE teachers are more likely to fall into the high DP class. This observation aligns with the findings of Shaheen and Mahmood ( 2016 ), who suggest that male teachers often display higher levels of apathy and cynicism toward their students compared to their female counterparts. As male teachers have limited coping strategies and emotional expression patterns, they prone to adopting a DP approach to manage stress and challenges in order shield themselves from emotional repercussions. Novice ECE teachers with non-education related degrees are more likely to fall into the "medium" category of EE. Those teachers often lack specialized knowledge in education, and they need more time and effort to adapt to and learn the demands of preschools(Ntim, S. Y., et al., 2023). Moreover, As education is not their best option, they may perceive ECE as a secondary or part-time pursuit, resulting in insufficient time and effort dedicated to their work (Park, E. Y., & Shin, M., 2020). Novice ECE teachers who work in urban preschool are more likely to show high EE level. Teachers in urban preschools often encounter high parental and societal expectations, which inherently place greater demands on teachers. The high expectations and pressures contribute to a high stress work environment, leading to novice ECE teachers’ emotion burnout (Shaheen, F. & Mahmood, N., 2016 ). Besides, novice ECE teachers with ECE internship are more likely to be categorized as experiencing 'low' EE. The previous experience provide them the coping strategies and appropriate expectation about the work, enabling them to adapt to their current roles (Goodwin, A. L., et al., 2019 ). In conclusion, these findings provide a crucial foundation for the development of effective interventions. Future research should explore strategies to prevent and mitigate emotional burnout by enhancing the work environment and offering psychological support. Declarations Declaration of competing interest: The authors declare that they have no known competing financialinterests or personal relationships that could have appeared to influencethe work reported in this paper. Funding This work was supported by 2021 Guangdong Provincial College Innovation Team Project (Humanities and Social Sciences): "Innovative Team of Early Childhood Education Theory and Practice Research" (2021WCXTD030) Author Contribution Authorship contributionYuhong Lei: Validation, Supervision, Conceptualization. Fan Pan :Software, Methodology, Data curation. Qiuxia Guo: Projectadministration. Data Availability The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request. References Ansari, A., Pianta, R. C., Whittaker, J. V., Vitiello, V. E., & Ruzek, E. A. (2022). Preschool teachers’ emotional exhaustion in relation to classroom instruction and teacher-child interactions.Early Education and Development,33(1), 107-120. Bakker, A. B., & Schaufeli, W. B. (2000). Burnout contagion processes among teachers 1.Journal of applied social Psychology,30(11), 2289-2308. Baran, G., Bıçakçı, M. 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O., Chen, S., & Mensah, E. T. (2023). Early childhood educators’ emotional labor and burnout in an emerging economy: The mediating roles of affective states. Heliyon, 9(3). Núñez del Rosario, P. D. (2020). Novice Second-Career Teachers: Experiences and Meaning-Making of the Transition Process. Park, E. Y., & Shin, M. (2020). A meta-analysis of special education teachers’ burnout. Sage Open, 10(2), 2158244020918297. Purper, C. J., Thai, Y., Frederick, T. V., & Farris, S. (2023). Exploring the challenge of teachers’ emotional labor in early childhood settings.Early Childhood Education Journal,51(4), 781-789. Räsänen, K., Pietarinen, J., Soini, T., Väisänen, P., & Pyhältö, K. (2022). Experienced risk of burnout among teachers with persistent turnover intentions.Teacher development,26(3), 317-337. Romano, L., Angelini, G., Consiglio, P., & Fiorilli, C. (2021). The effect of students’ perception of teachers’ emotional support on school burnout dimensions: Longitudinal findings. International journal of environmental research and public health, 18(4), 1922. Shaheen, F. (2018). Development and validation of emotional burnout scale (EBS) for teachers.Journal of Behavioural Sciences,28(1), 127-146. Shaheen, F., & Mahmood, N. (2016). Demographic Variables as Determinants of Emotional Burnout among Public School Teachers.Journal of Research & Reflections in Education (JRRE),10(1). Shaheen, F., & Mahmood, N. (2020). Burnout and its Predictors: Testing a Model Among Public School Teachers. Pakistan Journal of Psychological Research, 35(2). Stein, R., Garay, M., & Nguyen, A. (2024). It matters: Early childhood mental health, educator stress, and burnout.Early Childhood Education Journal,52(2), 333-344. Thomas, L., Tuytens, M., Moolenaar, N., Devos, G., Kelchtermans, G., & Vanderlinde, R. (2019). Teachers’ first year in the profession: The power of high-quality support.Teachers and Teaching,25(2), 160-188. Tuxford, L. M., & Bradley, G. L. (2015). Emotional job demands and emotional exhaustion in teachers. Educational Psychology, 35(8), 1006-1024. Trauernicht, M., Anders, Y., Oppermann, E., & Klusmann, U. (2023). Early childhood educators’ emotional exhaustion and the frequency of educational activities in preschool. European Early Childhood Education Research Journal,31(6), 1016-1032. Voitenko, E., Kaposloz, H., Zazymko, O., & Osodlo, V. (2021). Influence of characteristics of self-actualization and coping behavior on resistance of teachers to professional stressors and emotional burnout.International journal of organizational leadership,10, 1-14. Wiltshire, C. A. (2024). Early childhood education teacher workforce: Stress in relation to identity and choices.Early Childhood Education Journal,52(4), 655-668. Żołnierczyk-Zreda, D. (2005). An intervention to reduce work-related burnout in teachers.International Journal of Occupational Safety and Ergonomics,11(4), 423-430. Zysberg, L., & Maskit, D. (2017). Teachers' professional development, emotional experiences and burnout.Journal of Advances in Education Research,2(4), 287-300. Zysberg, L., Orenshtein, C., Gimmon, E., & Robinson, R. (2017). Emotional intelligence, personality, stress, and burnout among educators.International Journal of Stress Management,24(S1), 122. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6884218","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":479639989,"identity":"c916b21a-198e-4609-b0ad-3799e73325fe","order_by":0,"name":"Fan Pan","email":"","orcid":"","institution":"Huizhou University","correspondingAuthor":false,"prefix":"","firstName":"Fan","middleName":"","lastName":"Pan","suffix":""},{"id":479639990,"identity":"bd692b74-393c-4270-963e-3960a3a9b41c","order_by":1,"name":"Yuhong Lei","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYBACNv7m4x8+VNjI8bO3H3yQUFFDWAufxLE0xhln0owle84kGzw4c4ywFjmGHDVm3rbDiQYzEswkH7YwE+EwhjNsD4BaEgx4DqRVJDawMfC3dyfg18Lce9xA4lx6njl747EbiTtkGCTOnN1AwJZzCRIGZdbFlj0H0m4knmFjMJDIJaQlx0AigY05ccONBLOCxDZmorSYSRxocwZrYSBOi8SxZMMGaCBLJJw5xkPQL/L9zQcf/4FG5ccfFTVy/O29+LVgAB7SlI+CUTAKRsEowAoA2npPlNiLn24AAAAASUVORK5CYII=","orcid":"","institution":"Huizhou University","correspondingAuthor":true,"prefix":"","firstName":"Yuhong","middleName":"","lastName":"Lei","suffix":""},{"id":479639991,"identity":"c5227e36-9345-4f56-a3af-0e1097d2bae5","order_by":2,"name":"Qiuxia Guo","email":"","orcid":"","institution":"Shanwei Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Qiuxia","middleName":"","lastName":"Guo","suffix":""}],"badges":[],"createdAt":"2025-06-13 03:23:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6884218/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6884218/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-026-35199-w","type":"published","date":"2026-01-09T15:58:02+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":86141066,"identity":"5a9b816c-9cda-4cfd-8bb1-b3e175ad63c7","added_by":"auto","created_at":"2025-07-07 08:24:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":57932,"visible":true,"origin":"","legend":"\u003cp\u003eTrajectories of the GMM 3-class models for EE\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6884218/v1/696e8f36acc3fed3de7b4d4b.png"},{"id":86141068,"identity":"ea04c307-ae58-44b7-a80b-a6d611f8e3e2","added_by":"auto","created_at":"2025-07-07 08:24:18","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":49297,"visible":true,"origin":"","legend":"\u003cp\u003eTrajectories of the GMM 2-class models for DP\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6884218/v1/52d374d277cbff5316b16f84.png"},{"id":86141074,"identity":"e8d03954-a399-4dbd-aa50-1efc18bee59e","added_by":"auto","created_at":"2025-07-07 08:24:19","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":43488,"visible":true,"origin":"","legend":"\u003cp\u003eTrajectories of the GMM 2-class models for PA\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6884218/v1/c5ed91668443b6ebeb24071a.png"},{"id":100069822,"identity":"5017a602-7964-4163-a60f-3582abdab56c","added_by":"auto","created_at":"2026-01-12 16:15:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":756075,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6884218/v1/fe8a749d-3054-49ee-a9d3-4b4151522d53.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Longitudinal Study on Emotional Burnout Among Novice Early Childhood Education Teachers: Change from Entry to 24 months","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEarly Childhood Education (ECE) teachers are essential in developing children's cognitive ability, emotional ability, and social skills. With the increasing expectations from families, communities, and society, ECE teachers are encountering unprecedented pressures and challenges (Stein, R., Garay, M., \u0026amp; Nguyen, A. \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e; Purper, C. J et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Ntim, S. Y., et al. 2023). These challenges include the diversification demands of ECE, heightened social expectations, and significant changes in the educational environment brought about by the digital era (Goodwin, A. L., \u0026amp; Low, E. L., et al., 2019). Li et al. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) highlighted that ECE teachers are particularly susceptible to physical and mental exhaustion due to the high pressure nature of their work environment. This high pressure environment often results in ECE teachers’ emotional fatigue and a diminished enthusiasm. Furthermore, the inherent demands of ECE require teachers to sustain a high level of commitment and focus over extended periods. However, ECE teachers’ dedication was always unrecognized and unrewarded, contributing to the diminished sense of teachers’ personal accomplishment (Mischo, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Additionally, the multifaceted challenges of ECE requires teachers to possess diverse skills and abilities, including effective communication, organizational and coordination capabilities, as well as innovative teaching strategies (Stein et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). ECE teachers need to devote large amount time and energy to develop and practice these abilities. These challengesAll these professional requirements not only affect ECE teachers’ own physical and mental health but also potentially having a profound impact on children's development (Tuxford, L. M., \u0026amp; Bradley, G. L., 2015; Żołnierczyk-Zreda, D., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Klusmann, U., et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong these mental problems, emotional burnout is particularly prominent. Emotional burnout can be conceptualized as a dynamic construct that reflects an individual's psychological state and changes over time in response to different job demands (Maslach \u0026amp; Schaufeli, 2017; DeAngelis, K. J., 2013). A lots of previous research have studied emotional burnout, primarily focusing on definition, influencing factors, and potential interventions (McKinley, T. F., et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Dorman, J., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Shaheen, F., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Shaheen, F., \u0026amp; Mahmood, N., et al. 2016). The concept of emotional burnout was first introduced by Maslach and Jackson in 1981 and is recognized as one of the three core dimensions of a person’s overall burnout. Shaheen (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and Ansari (2022) suggested that emotional burnout is characterized by emotional exhaustion, depersonalization, and a diminished sense of accomplishment. Depersonalization is characterized by indifference and alienation to the individuals they serve (Dorman, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). Decreased sense of accomplishment indicates teachers' negative assessment of their job effectiveness. The emotional burnout is precipitated by various factors, including work pressure, professional challenges, and the disparity between personal expectations and reality. The manifestations of emotional burnout primarily include the unstable emotion situation, a sense of indifference toward work, and feelings of powerlessness.\u003c/p\u003e \u003cp\u003eNovice ECE teachers are particularly vulnerable to emotional burnout. According to Thomas et al. (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), novice ECE teachers, who just begin their careers and whose passion and motivation for education have yet to solidify, are particularly incline to suffer emotion burnout. Previous studies have indicated that emotional burnout among novice ECE teachers is linked to a variety of factors (Fantilli, R. D., \u0026amp; McDougall, D. E., 2009; Grygas Coogle, C., et al., 2018; Mikser, R., Õun, T., et al., 2021). Given the high requirements of ECE, novice teachers must devote substantial time and energy to form close relationships with children and support their development. If teachers’ energy is not adequately replenished and restored, they are highly likely to suffer emotional burnout after an period (Wiltshire, C. A., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Many novice ECE teachers often felt exhausted by the end of the day, resulting in a low level of enthusiasm for their work and prompting them to question their career choices (Li, J. B., \u0026amp; Li, Z., et al., 2021; Hooper, A., et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Novice ECE teachers often encounter various challenges which significantly contribute to their emotional burnout. Job stress, particularly, is a major contribution factor. DeAngelis, K. J. et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) highlights that novice teachers frequently feel overwhelmed by classroom management, parent communication, and daily teaching responsibilities. For instance, novice teachers may experience frustration due to an inability to maintain classroom order. Their frustration can accumulate over time and ultimately result in emotional burnout. Support from family, colleagues, and school administer sis a crucial intervention factor for novice ECE teachers’ emotional burnout (Żołnierczyk-Zreda, D., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Hogan, J. P., \u0026amp; White, P., 2021). Teacher's emotional burnout can be significantly mitigated by guidance from an experienced colleague or encouragement from families.\u003c/p\u003e \u003cp\u003eAdditionally, previous studies revealed significant effects among various demographic information and ECE teachers' emotional burnout (Fiorilli, C., \u0026amp; Benevene, P., et al., 2019) The demographic information including gender, age, education, teaching experience, and academic qualifications and so on (Fisher, 2011). Other factors such as professional background, internship, and preschool’s geographic location are also significant when examining the ECE teachers’ emotional burnout (Faiza Shaheen \u0026amp; Nasir Mahmood, 2016; Núñez del Rosario, P. D., 2020; DeAngelis, K. J., et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Previous research indicated that female ECE teachers are more vulnerable than male ECE teachers when confronted with the daily job challenges, so female teachers have a higher risk of emotional burnout (Noor, N. M., \u0026amp; Zainuddin, M., 2011). Ansari et al. (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) and Chang (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2009\u003c/span\u003e)’s study suggested that teachers with high educational levels tend to have high expectations and aspirations for their professional development. However, the discrepancy between high expectations and the realities of the work environment can exacerbate feelings of emotional burnout. ECE teacher's professional background also significantly influences their self-efficacy and career satisfaction. Novice teachers who engaged in internship before find it easier to adapt to the teaching environment(Stein, Garay, \u0026amp; Nguyen, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Because the internship provide them an deep understanding of educational principles, teaching methods, curriculum design, and a robust knowledge base to address actual teaching problems. So ECE teachers can quickly adapt to the preschool have low risk of emotional burnout. ECE teachers with out internship are unfamiliar with the children's characteristics psychological development and effective teaching methods. Consequently, the new working situation can increase their work-related stress, potentially leading to emotional burnout (Voitenko, E., et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Ansari, A., 2022). Besides, limited scholars have examined the impact of preschools’ geographic location on the ECE teachers’ emotional burnout. Previous research suggested that a preschool’ geographic location significantly influences a ECE teacher's work environment and access to different educational resources, which in turn affects teacher burnout (DeAngelis, K. J., 2013).\u003c/p\u003e\n\u003ch3\u003ePurpose of the study\u003c/h3\u003e\n\u003cp\u003eDespite the growing interest in emotional burnout, there is limited empirical research examining changes of emotional burnout specifically among novice ECE teachers (Tuxford \u0026amp; Bradley, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Most previous studies employed cross-sectional methods to examine the novice ECE teachers’ emotional burnout. These methods fail to capture the dynamic nature of novice ECE teachers’ emotional burnout over time. Longitudinal studies can track the changes of novice ECE teachers’ emotional burnout, enhancing our understanding of the underlying mechanisms and influencing factors associated with novice ECE teachers’ emotional burnout (Mischo, C., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). This study aims to fill the research gap and conduct a longitudinal analysis of novice ECE teachers/ emotional burnout.\u003c/p\u003e \u003cp\u003eBy collecting and analyzing longitudinal data at six intervals, this research seeks to elucidate the patterns of novice ECE teachers’ emotional burnout, and show underlying factors contributing to this pattern. This research aims to categorize the trajectory of novice ECE teachers’ emotional burnout into several distinct patterns. Additionally, the study will examine the influence of demographic factors, including education degree, rural or urban preschool, gender, and have internship or not, on the patterns. With the comprehensively understanding of the change patterns of novice ECE teachers’ emotional burnout, researchers and administers can accurately identify the stages in which the novice ECE teachers are most susceptible to emotional burnout. This study will also as well as the statistical variables that significantly contribute to their emotional depletion. This knowledge will provide a robust foundation for developing targeted interventions.The objective is to propose effective interventions based on these findings.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003c/div\u003e \u003c/div\u003e\n\n\n\n"},{"header":"METHOD","content":"\u003ch2\u003eProcedure and Participants\u003c/h2\u003e\u003cp\u003eThis research investigated dataset from the China National Program for Child Development. The program was developed to provide consolidated early childhood development for children. The program also provide professional development for ECE educators to construct a respect and warm ECE atmosphere. The program includes several dimensions, including Health of Children, Education of Children, Welfare of Children, Children and the Social Environment, and the Legal Protection of Children. It includes 51,700 children and related teachers, parents, and preschools information in different regions and cities from 2013 to 2023. The research protocol and all procedures involving human participants were reviewed and approved by the Huizhou University Institutional Review Board. This study was conducted in accordance with the ethical principles outlined in the Huizhou University`s guidelines and regulations. Informed consent was obtained from all participants included in the study prior to their participation.\u003c/p\u003e\u003cp\u003eWe got a list of teachers and their related information from the board of the The China National Program for Child Development. ECE teachers were contacted immediately after their enter the preschools and begin their career. When teachers agree to participate the research, we emailed the purpose of the study and detailed privacy policy, along with the informed consent. Then we emailed the online Maslach Burnout Inventory questionnaire to all consenting participants to complete. Finally, we obtained a subsample of 2,455 teachers. Maslach Burnout Inventory was measured at six times points: at 4, 8, 12, 16, 20, and 24 months after starting the job. We administered the first Maslach Burnout Inventory questionair in the middle of October 2021. Response rates for 4, 8, 12, 16, 20, and 24 months for X were 95.27, 74.49, 62.04, 59.22, 53.26, and 48.39%, respectively, Besides, at least 67.8% of teachers had completed three or more Maslach Burnout Inventory, and 38% of teachers had completed all six Maslach Burnout Inventory. Across all teachers, 31% had a bachelor’s degree, 17% had bachelor’s degree above, and 52% has a bachelor’s degree below. The average age of teachers was 25 years old (Standard Deviation = 10.78), ranging from 21 to 28. Most teachers (79.2%, N = 2732) were female. The percentages of teachers work in rural and urban preschools were 51.6 and 48.4. The teachers who has internship in preschools before they officially begin the career is 67.3%, where as 32.7% teachers do not have any experience in ECE before they act as ECE teachers. Besides, 59% teachers in our study have a ECE degree, 28% the teachers have a education related degree (not ECE related), and 13% teachers have non-education related degree.\u003c/p\u003e\u003ch3\u003eInstruments\u003c/h3\u003e\u003cp\u003eBurnout was measured using the Maslach Burnout Inventory (MBI), a self-report questionnaire developed to measure burnout and validated in various occupational groups. The MBI has been widely used in the previous studies to evaluate burnout in different professions and is regarded as one of the the important measurements for the evaluation of burnout. The MBI scale has 22 items assessing 3 domains related to burnout: EE (emotional exhaustion), DP (depersonalization), and PA (reduced personal accomplishments). EE includes 9 items assessing the fatigue and emotional depletion of teachers; DP includes 5 items assessing the extent that teachers become cynical towards students; PA includes 8 items assessing the extent that teachers achieves their personal goals. Each item is rated on a on a 7-point Likert scale, indicating how often the respondents experience job-related feelings in specific areas. For items belong to EE and DP, higher score shows high level of severity, whereas for items in PA, low scores are viewed as indicators of burnout.The overall reliability of MBI was 0.81. The Cronbach alpha’s value (α) for EE, DP, and PA was 0.76, 0.73, and 0.90.\u003c/p\u003e\u003ch3\u003eAnalysis\u003c/h3\u003e\u003cp\u003eWe performed GMM analyses with robust maximum likelihood estimation. Thw analysis were conducted using Mplus Version 8.4 (Muthén and Muthén, 2010). We employed Full information maximum likelihood (FIML) to deal with missing data. First of all, we ran three different unconditional GMM for each domain of MBI: no growth model, linear growth model, and non-linear growth model. Then, the the chi-square statistics were used to compare these three models of each domain, and the non-linear unconditional model showed the best fit for each domain. Next, for each domain, we compared 2 class to 5 class non-linear unconditional GMMs to get the non-linear unconditional GMM model with the best number of class. Both the model with all growth factors and the variances freely estimated and models with constrained the variances across the classes are failed to converge. The appropriate unconditional GMM model was structured when the variances for the intercepts, linear, and quadtirc parameters were constrained equal across all classes. To compare the GMM with K classes and GMM with K − 1 classes, several mode fit indices include Akaike Information Criterion (AIC; Akaike, 1973), the Bayesian Information Criterion (BIC; Schwarz, 1978), and the samplesize adjusted BIC (ABIC; Sclove, 1987) were used in our study. Entropy value, Lo–Mendell–Rubin (LMR) and adjusted Lo-Mendell-Rubin likelihood-ratio test (ALRT) were also include in the study (Muthén, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). K − 1 classes. A significant p-value of LMR and ALRT indicates that the model with K classes is better than the model with K − 1 classes, whereas non-significant p-value shows that the K classes model and K − 1 classes model perform similar. When a model’s entropy value close to 1.0, the model is more suitable for the data we studied. After the appriproate unconditional GMM model was identified, we will investigate predictors and outcomes of each class using the three-step approach in Mplus for each domain of MBI.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eGrowth Curve Models For Three Domains\u003c/h2\u003e \u003cp\u003eThe FLML showed that the lowest covariance coverage for the analysed was 0.278, which is larger than the threshold of 0.10. So the missing data in this study are acceptable for model convergence. Firstly, we examined a growth curve model of EE, DP, and PA over 24 months. For EE, model fit values were moderate: χ2(36)\u0026thinsp;=\u0026thinsp;158.23, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, CFI (Comparative Fit Index)\u0026thinsp;=\u0026thinsp;0.88, TLI (Tucker Lewis Index)\u0026thinsp;=\u0026thinsp;0.91, RMSEA (Root Mean Squared Error of Approximation)\u0026thinsp;=\u0026thinsp;0.07, SRMR (standardized root mean square residual)\u0026thinsp;=\u0026thinsp;0.075. The values of intercept (I\u0026thinsp;=\u0026thinsp;14.61, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), slope (S\u0026thinsp;=\u0026thinsp;0.39, p\u0026thinsp;=\u0026thinsp;0.038), and quadratic (Q\u0026thinsp;=\u0026thinsp;0.42, p\u0026thinsp;=\u0026thinsp;0.007) are all significant, revealing curvilinear trend of EE with slight upward trend for all participants over time. Besides, the variance of the intercept (w\u0026thinsp;=\u0026thinsp;9.21, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), slope (w\u0026thinsp;=\u0026thinsp;1.42, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and quadratic (w\u0026thinsp;=\u0026thinsp;0.03, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) is significant, indicating EE contains multiple trajectories during 24 months. For DP, model fit values were large: χ2(36)\u0026thinsp;=\u0026thinsp;385.53, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, CFI (Comparative Fit Index)\u0026thinsp;=\u0026thinsp;0.95, TLI (Tucker Lewis Index)\u0026thinsp;=\u0026thinsp;0.96, RMSEA (Root Mean Squared Error of Approximation)\u0026thinsp;=\u0026thinsp;0.08, SRMR (standardized root mean square residual)\u0026thinsp;=\u0026thinsp;0.05. The values of intercept (I\u0026thinsp;=\u0026thinsp;5.21, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), slope (S\u0026thinsp;=\u0026thinsp;0.41, p\u0026thinsp;=\u0026thinsp;0.005), and quadratic (Q\u0026thinsp;=\u0026thinsp;0.46, p\u0026thinsp;=\u0026thinsp;0.001) are all significant, revealing curvilinear trend of DP with slight upward trend for all participants over time. Besides, the variance of the intercept (w\u0026thinsp;=\u0026thinsp;6.71, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), slope (w\u0026thinsp;=\u0026thinsp;1.82, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and quadratic (w\u0026thinsp;=\u0026thinsp;0.01, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) is significant, indicating DP contains multiple trajectories during 24 months. For PA, model fit values were large: χ2(36)\u0026thinsp;=\u0026thinsp;418.21, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, CFI (Comparative Fit Index)\u0026thinsp;=\u0026thinsp;0.98, TLI (Tucker Lewis Index)\u0026thinsp;=\u0026thinsp;0.96, RMSEA (Root Mean Squared Error of Approximation)\u0026thinsp;=\u0026thinsp;0.08, SRMR (standardized root mean square residual)\u0026thinsp;=\u0026thinsp;0.06. The values of intercept (I\u0026thinsp;=\u0026thinsp;23.41, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), slope (S\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;.36, p\u0026thinsp;=\u0026thinsp;0.005), and quadratic (Q\u0026thinsp;=\u0026thinsp;0.51, p\u0026thinsp;=\u0026thinsp;0.001) are all significant, revealing curvilinear trend of PA with slight downward trend for all participants over time. Besides, the variance of the intercept (w\u0026thinsp;=\u0026thinsp;13.49, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), slope (w\u0026thinsp;=\u0026thinsp;1.71, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and quadratic (w\u0026thinsp;=\u0026thinsp;0.06, p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) is significant, indicating PA contains multiple trajectories during 24 months.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGMMs With Different Classes For Three Domains\u003c/h3\u003e\n\u003cp\u003eNext, we performed GMMs for to investigate possible class membership for each domain. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the model fit indices for the 1 to 5 class models of EE, DP, and PA. For EE, as shown in the table, all indices decreased from the 1 to 5 class models. The decrements were relatively larger from the 1 to 3 class models than to the 4 to 5 class models, and the decrement of the model fit indices values from the 3 to 5 class models were larger than the 4 to 5 class models. The LMR and ALRT values for the 1 to 3 class models were significant, but not significant for the 4 and 5 class model. Besides, The entropy value for the 3 class models (0.82) was higher than the 2 class (0.78), 4 class (0.79) and 5 class (0.78) models. Also, the model fit indicates that the 4 and 5 class models simply separated one class of the 3 class modes into two and three classes. Thus, based on above statistical information, the 3 class model can be considered most appropriate for the sample. For DP and PA, all indices also decreased from the 1 to 5 class models. The decrements were relatively larger from the 1 to 2 class models than to the 3 to 5 class models, and the decrement of the model fit indices values from the 2 to 5 class models were larger than the 3 to 5 class models. The LMR and ALRT values for the 1 to 2 class models were significant, but not significant for the 4 and 5 class model. Besides, The entropy value for the 2 class models was higher than the 3, 4 and 5 classes models. Also, the model fit indicates that the 3 to 5 class models simply separated one class of the 2 class models into two and three classes. Thus, based on above statistical information, the 2 class model can be considered most appropriate for both the DP and PA domains.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eModel Fit Indices by Number of Classes for Each Domain of MBI\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel Fit Indices\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 class\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 classes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 classes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 classes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 classes\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eEE (emotional exhaustion)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19863.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19632.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19481.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19459.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19326.93\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20135.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19899.89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19704.39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19683.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19676.94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eABIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19925.46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19636.35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19422.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19393.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19379.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEntropy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALRT(p-value)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.32\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLMR(p-value)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eDP (depersonalization)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21045.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19213.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19187.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19176.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19172.74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21672.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20392.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20315.56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e20298.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e20291.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eABIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21018.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20015.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19998.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19987.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19982.87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEntropy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALRT(p-value)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLMR(p-value)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003ePA (reduced personal accomplishments)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20842.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19482.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19412.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19398.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19386.43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21024.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19652.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19498.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19435.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19421.83\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eABIC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20981.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19821.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19129.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19004.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18997.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEntropy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALRT(p-value)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLMR(p-value)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e indicates the growth trajectories of EE\u0026rsquo;s three classes, and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the growth parameters for each class. Class 1 (9 percent, n\u0026thinsp;=\u0026thinsp;221) showed a relative high intercept and with a steady decrease before 16 months, followed by an steady increase from 16 months to 24 months. We name this class as \u0026lsquo;\u0026lsquo;High.\u0026rsquo;\u0026rsquo; Class 2 (26 percent, n\u0026thinsp;=\u0026thinsp;638) had a moderate intercept with a different growth trajectory to Class High, increasing before 12 months and decreasing from 12 months to 24 months. Class 2 was called as \u0026lsquo;\u0026lsquo;Moderates.\u0026rsquo;\u0026rsquo; Finally, Class 3 (65 percent, n\u0026thinsp;=\u0026thinsp;196) had low initial levels of emotional exhaustion and slightly increased over 24 months. We refer to this class as \u0026lsquo;\u0026lsquo;Low .\u0026rsquo;\u0026rsquo;\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e indicates the growth trajectories of the DP\u0026rsquo;s two classes, and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e also indicates the growth parameters of these two classes. Class 1 (29 percent, n\u0026thinsp;=\u0026thinsp;712) had high initial levels of reduced personal accomplishments and slightly decreased over 24 months. We refer to this class as \u0026lsquo;\u0026lsquo;High.\u0026rsquo;\u0026rsquo; Class 2 (64 percent, n\u0026thinsp;=\u0026thinsp;1571) had low initial levels of reduced personal accomplishments and moderately increased over 24 months. We call Class 2 as \u0026lsquo;\u0026lsquo;Low.\u0026rsquo;\u0026rsquo;\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e indicates the growth trajectories of the PA\u0026rsquo;s two classes, and Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e also includes the growth parameters of these two classes. Class 1 (36 percent, n\u0026thinsp;=\u0026thinsp;884) has a very high initial level of depersonalization and stead a downward trend over the study period. We refer to this class as \u0026lsquo;\u0026lsquo;High\u0026rdquo;.Class 2 (71 percent, n\u0026thinsp;=\u0026thinsp;1743) showed low PA level throughout the study period and stead a upward trend over the study period. We call Class 2 as \u0026lsquo;\u0026lsquo;Low.\u0026rsquo;\u0026rsquo;\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGrowth Parameters for Each Class of Each Domain\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eClass(percent of sample)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLinear slope\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eQuadratic\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eB(SE)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB(SE)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eB(SE)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eEE (emotional exhaustion)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1(9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34.12(0.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026minus;0.16(0.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01(0.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2(26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.87(0.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.87(0.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.02(0.005)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3(65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.46(0.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.36(0.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.009(0.02)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eDP (depersonalization)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1(29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.95(0.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.92(0.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.04(0.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2(71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.09(0.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.72(0.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.06(0.02)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003ePA (reduced personal accomplishments)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1(36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.28(0.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.24(0.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.008(0.06)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2(64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.47(0.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.26(0.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.006(0.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eNext, We investigated predictors of the trajectories of three domains of MBI with Mplus 8.3. Predictors contained education background, rural or urban preschool, biological sex, have ECE experience or not, and degree from 4 months to 24 months. As for EE, females were more likely to be in the \u0026lsquo;\u0026lsquo;High\u0026rsquo;\u0026rsquo; class compared with the \u0026lsquo;\u0026lsquo;Moderate\u0026rsquo;\u0026rsquo; (b\u0026thinsp;=\u0026thinsp;2.07, p\u0026thinsp;=\u0026thinsp;0.01) and \u0026lsquo;\u0026lsquo;Low\u0026rsquo;\u0026rsquo; (b\u0026thinsp;=\u0026thinsp;2.31, p\u0026thinsp;=\u0026thinsp;0.01) classes. Besides, females were more likely to be in the \u0026lsquo;\u0026lsquo;Moderate\u0026rsquo;\u0026rsquo; class compared with the\u0026lsquo;\u0026lsquo;Low\u0026rsquo;\u0026rsquo;class (b\u0026thinsp;=\u0026thinsp;0.71, p\u0026thinsp;=\u0026thinsp;0.02). The \u0026lsquo;\u0026lsquo;High\u0026rsquo;\u0026rsquo; class had higher numbers of participants working in urban preschools than both the \u0026lsquo;\u0026lsquo;Moderate\u0026rsquo;\u0026rsquo; (b\u0026thinsp;=\u0026thinsp;2.42, p\u0026thinsp;=\u0026thinsp;0.01) and \u0026lsquo;\u0026lsquo;Low\u0026rsquo;\u0026rsquo; classes (b\u0026thinsp;=\u0026thinsp;1.81, p\u0026thinsp;=\u0026thinsp;0.04), but lower numbers of teachers with ECE experience (b = -3.98, p\u0026thinsp;=\u0026thinsp;0.001; b = -3.87, p\u0026thinsp;=\u0026thinsp;0.001, respectively). In addition, participants with educated related degree (non ECE related) were more likely to be in the\u0026lsquo;\u0026lsquo;Moderate\u0026rsquo;\u0026rsquo; class than \u0026lsquo;\u0026lsquo;Low\u0026rsquo;\u0026rsquo; (b\u0026thinsp;=\u0026thinsp;2.69, p\u0026thinsp;=\u0026thinsp;0.007) classes.\u003c/p\u003e \u003cp\u003eAs for DP, males were more likely to be in the \u0026lsquo;\u0026lsquo;High\u0026rsquo;\u0026rsquo; class compared with the \u0026lsquo;\u0026lsquo;Low \u0026rsquo;\u0026rsquo; (b\u0026thinsp;=\u0026thinsp;2.53, p\u0026thinsp;=\u0026thinsp;0.007) class. Participants with ECE experience were more likely to be in the \u0026lsquo;High\u0026rsquo;\u0026rsquo; class compared with the \u0026lsquo;\u0026lsquo;Low \u0026rsquo;\u0026rsquo; class (b\u0026thinsp;=\u0026thinsp;1.79, p\u0026thinsp;=\u0026thinsp;0.005). The \u0026lsquo;\u0026lsquo;High\u0026rsquo;\u0026rsquo; class had higher numbers of participants from urban preschools than \u0026lsquo;\u0026lsquo;Low\u0026rsquo;\u0026rsquo; class (b\u0026thinsp;=\u0026thinsp;2.49, p\u0026thinsp;=\u0026thinsp;0.001), but lower levels of bachelor\u0026rsquo;s degree and above (b = -3.98, p\u0026thinsp;=\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eFinally for PA, males were also more likely to be in the \u0026lsquo;\u0026lsquo;High\u0026rsquo;\u0026rsquo; class compared with the \u0026lsquo;\u0026lsquo;Low \u0026rsquo;\u0026rsquo; (b\u0026thinsp;=\u0026thinsp;3.26, p\u0026thinsp;=\u0026thinsp;0.001) class. Participants with bachelor\u0026rsquo;s degree and above were more likely to be in the \u0026lsquo;High\u0026rsquo;\u0026rsquo; class compared with the \u0026lsquo;\u0026lsquo;Low \u0026rsquo;\u0026rsquo; class (b\u0026thinsp;=\u0026thinsp;3.71, p\u0026thinsp;=\u0026thinsp;0.001). The \u0026lsquo;\u0026lsquo;High\u0026rsquo;\u0026rsquo; class also had higher numbers of participants from urban preschools than \u0026lsquo;\u0026lsquo;Low\u0026rsquo;\u0026rsquo; class (b\u0026thinsp;=\u0026thinsp;3.09, p\u0026thinsp;=\u0026thinsp;0.001).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe Growth Curve Models findings indicated that EE and DP exhibited a slight upward trend over time, whereas PA demonstrated a slight downward trend. Romano, L., et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) investigated the influence of perceived emotional support on these three domains. Their results indicated that the all three domains exhibited a significant upward trend over time. Novice ECE teachers often have high expectations for their roles in education, aspiring to inspire children's creativity, cultivate their interest in learning, and establish a nurturing educational environment. However, they confront lots of difficulties in daily classroom management, parent communication, and children\u0026rsquo;s diverse needs after they begin daily work. The daily ECE job is significantly more stressful than they anticipated, resulting in a gradual accumulation of EE. The high work pressure and challenges can lead to the negative attitudes toward both the children and the profession, leading to the high DP level (Morrison, C. M., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). As for PA, this study the exhibited a slight decline, contradicting Romano, L., et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e)\u0026rsquo; s findings. This discrepancy may due to the different sample studied. Romano, L., et al. (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) investigated the experienced teachers, whereas this research studied novice teachers. Although novice ECE teachers gradually gain experience and skills, they still encounter challenges due to an inadequate education evaluation system, ambiguous career development opportunities, and lack of effective incentives (Thomas, L., et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo accurately understand the trajectory of the three domains of emotional burnout, this study employed the GMM as to identify the optimal classification model for each domain. Previous studies showed the developmental trajectories of teachers' emotional burnout due to occupational stress are not singular and fixed. The trajectories exhibit a high degree of individual variation (Brunsting, N. C., Bettini, E., et al., 2023; Tuxford, L. M., et al., 2015). Each teacher's personality traits could significantly influence their coping styles for stress, leading to distinct trajectories in the development of emotional burnout. Zysberg et al. (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and Ding et al. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) have examined the emotional burnout of English teachers and highlight the interplay of personal upbringing, educational background, and psychological resilience as key factors influencing the psychological mechanisms of these educators. Separating novice ECE teachers into multiple class with GMM based on their emotional burnout trajectories has significant practical implications. Based on the GMM, researchers and administers could design individualized interventions tailored to the unique circumstances of each class and effectively alleviate novice ECE teachers\u0026rsquo; emotional burnout.\u003c/p\u003e \u003cp\u003eNovice ECE teachers' EE can be classified into three distinct trajectory classes: high, medium, and low over the 24-month period. The high class remained relatively high EE level throughout the period. From 0 to 16 months, the high class showed a decreasing trend, and then increase from 16 to 24 months. Teachers in this class could work in preschools that have higher significant job demands than preschools, in which medium and lows classes teachers work(Baran, G., et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The decreasing tread during the 0\u0026ndash;16 month period indicate that these novice ECE teachers in high class gradually adapt to their new work environment and acquire essential educational skills and methods (DeAngelis, K. J., et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The accumulation of work stress, insufficient emotional support, and inadequate coping strategies could cause the upward trend from the 16 to 24 month (Zysberg, L., et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Thomas, L., et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This high class teachers novice ECE requires special attention, along with appropriate support and interventions. The moderate class initially showed moderate level of EE and then significantly increased from 6 to 12 month. This class has highest point around 12 months can then declined back to moderate level from 12 to 24 month. The increasing may be attributed to the limited work experience before entering the profession, coupled with the lack of understanding about how to seek support from others (Lindqvist, H., et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The subsequent declining for novice EE teachers in moderate class could associated with the gradual adaptation, the establishment of stable professional relationships, and the acquisition of additional experience and skills (DeAngelis, K. J., et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The low class exhibited consistently low and stable level of EE throughout the period. The novice ECE teachers in the class may possess a high degree of mental toughness and resilience, enabling them to effectively deal with the challenges and pressures associated with their new profession (Kinman, G., et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Besides, they could effectively employ coping strategies and emotion regulation skills, allowing them to mitigate EE while keep their work ethic standards (Chang, M. L., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Chang\u0026rsquo;s (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) study about the relationship between teachers' emotional performance rules, emotion regulation, and burnout in one United States western state indicated that teachers' emotion regulation strategies significantly influenced burnout levels.\u003c/p\u003e \u003cp\u003eNovice ECE teachers exhibited a bipolar phenomenon on their levels of DP, which shows teachers\u0026rsquo; enthusiasm and dedication to working with children and in ECE. For high class, a steady decline was observed from 0 to 16 month. This decline may be attributed to the accumulation of experience, which enables teachers to gradually adapt to teaching and develop more effective emotion regulation and coping strategies (DeAngelis, K. J., et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Chang, M. L., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). After 16 months, DP levels of high class began to rise. Potential explanation factors include the accumulation of job stress, the onset of burnout, or the influence of external circumstances (Zysberg, L., et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Chang, M. L., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Shaheen, F., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The low class demonstrated relatively low initial level of DP, and exhibited a consistent increase from 0 to 16 months. This changing pattern may stem from a combination of factors, including the accumulated experience, job-related stress, and the personal characteristics of the teachers, as previously discussed (Goodwin, A. L., et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Brunsting, N. C., et al., 2023). Notably, while the teachers' levels of DP increased, the overall level still remained relatively low. This finding suggested that the novice ECE teachers in low class were able to sustain passion and commitment to students and educational responsibilities, avoiding excessive depersonalization. Future research should further investigate the underlying reasons for this changing pattern through in-depth analyses from various perspectives, including the personal traits of teachers, their work environments, and the availability of social support. It is imperative to focus on novice ECE teachers whose DP continue to rise and understand the challenges they.To mitigate this increasing, schools and educational administrations could implement appropriate support systems and interventions to assist teachers in maintaining their teaching effectiveness and mental well-being.\u003c/p\u003e \u003cp\u003ePA were also categorized into high and low classed. Both class showed relative stability PA levels. Teachers in the high class consistently exhibited high self-efficacy. This high sense of accomplishment may be attributed to the fact that teachers manage effective coping strategies when confronted with the daily challenges of teaching and managing children. A study on K-12 teachers' emotional burnout and emotional work by Chang, M. L. (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2009\u003c/span\u003e) noted that effective coping strategies can assist teachers in better managing their emotions and reducing burnout. Their sense of self-efficacy can reduce emotional burnout (Trauernicht, M., et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In contrast, teachers who demonstrate low PA levels may not possess adaptive skills and positive work attitudes. They may be need development at adjusting their mindsets, maintaining optimism in the face of difficulties, remaining humble about their accomplishments, and identifying opportunities for growth from challenges. These teachers may also be lack skills about exploring available resources, such as mutual support among colleagues, professional training, and family support, to alleviate work-related stress and thus maintain a relatively stable psychological state (Żołnierczyk-Zreda, D., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2005\u003c/span\u003e).Therefore, it is essential to focus on the personal sense of achievement of novice ECE teachers during their support and training. By offering professional development opportunities, psychological support, and training about effective teaching strategies, researchers and administers can assist these teachers to gain enthusiasm and confidence, ultimately enhancing their career satisfaction and retention.\u003c/p\u003e \u003cp\u003eBesides, the study investigated the impact of various demographic variables, include education background, rural or urban preschool, gender, and have internship or not, on novice ECE teachers\u0026rsquo; emotional burnout trajectories. The results indicated that these variables significantly influenced the emotional burnout trajectories. These findings corroborate the research conducted by Shaheen, F. and Mahmood, N. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) about the determinants of public school teachers\u0026rsquo; emotional burnout. Shaheen, F. and Mahmood, N. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) revealed that gender, district, qualifications, and teaching level significantly affected teachers\u0026rsquo; emotional burnout. N\u0026uacute;\u0026ntilde;ez del Rosario, P. D. (2020) conducted a study on novice teachers transfered from other field, indicating that teachers' educational backgrounds and work experiences may significantly influence their levels of emotional burnout by impacting their capacity to adapt to and manage their teaching responsibilities. This study indicated that female novice ECE teachers were more likely to be categorized as high or medium EE class. This phenomenon may due to that compared to male, female act as more roles in both their professional and personal lives and encounter more stress (Noor, N. M., \u0026amp; Zainuddin, M., 2011). Female tend to exhibit emotional sensitivity, making them more susceptible to feelings of EE. Male novice ECE teachers are more likely to fall into the high DP class. This observation aligns with the findings of Shaheen and Mahmood (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), who suggest that male teachers often display higher levels of apathy and cynicism toward their students compared to their female counterparts. As male teachers have limited coping strategies and emotional expression patterns, they prone to adopting a DP approach to manage stress and challenges in order shield themselves from emotional repercussions. Novice ECE teachers with non-education related degrees are more likely to fall into the \"medium\" category of EE. Those teachers often lack specialized knowledge in education, and they need more time and effort to adapt to and learn the demands of preschools(Ntim, S. Y., et al., 2023). Moreover, As education is not their best option, they may perceive ECE as a secondary or part-time pursuit, resulting in insufficient time and effort dedicated to their work (Park, E. Y., \u0026amp; Shin, M., 2020). Novice ECE teachers who work in urban preschool are more likely to show high EE level. Teachers in urban preschools often encounter high parental and societal expectations, which inherently place greater demands on teachers. The high expectations and pressures contribute to a high stress work environment, leading to novice ECE teachers\u0026rsquo; emotion burnout (Shaheen, F. \u0026amp; Mahmood, N., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Besides, novice ECE teachers with ECE internship are more likely to be categorized as experiencing 'low' EE. The previous experience provide them the coping strategies and appropriate expectation about the work, enabling them to adapt to their current roles (Goodwin, A. L., et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn conclusion, these findings provide a crucial foundation for the development of effective interventions. Future research should explore strategies to prevent and mitigate emotional burnout by enhancing the work environment and offering psychological support.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eDeclaration of competing interest:\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no known competing financialinterests or personal relationships that could have appeared to influencethe work reported in this paper.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by 2021 Guangdong Provincial College Innovation Team Project (Humanities and Social Sciences): \"Innovative Team of Early Childhood Education Theory and Practice Research\" (2021WCXTD030)\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAuthorship contributionYuhong Lei: Validation, Supervision, Conceptualization. Fan Pan :Software, Methodology, Data curation. Qiuxia Guo: Projectadministration.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAnsari, A., Pianta, R. C., Whittaker, J. V., Vitiello, V. E., \u0026amp; Ruzek, E. A. (2022). Preschool teachers\u0026rsquo; emotional exhaustion in relation to classroom instruction and teacher-child interactions.Early Education and Development,33(1), 107-120.\u003c/li\u003e\n\u003cli\u003eBakker, A. B., \u0026amp; Schaufeli, W. B. (2000). Burnout contagion processes among teachers 1.Journal of applied social Psychology,30(11), 2289-2308.\u003c/li\u003e\n\u003cli\u003eBaran, G., Bı\u0026ccedil;ak\u0026ccedil;ı, M. Y., İnci, F., \u0026Ouml;ng\u0026ouml;r, M., Ceran, A., \u0026amp; Atar, G. (2010). Analysis of burnout levels of teacher. 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Emotional intelligence, personality, stress, and burnout among educators.International Journal of Stress Management,24(S1), 122.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Emotional burnout, Novice ECE Teachers, Growth Mixed Model","lastPublishedDoi":"10.21203/rs.3.rs-6884218/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6884218/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIn early childhood education, the emotional well-being of teachers plays a crucial role in fostering the development of children. Emotional burnout, a significant indicator of teachers\u0026rsquo; mental health, affect both their teaching effectiveness and the interaction with children. Consequently, a comprehensive longitudinal examination of the emotional burnout among novice early childhood education (ECE) teachers is important for enhancing ECE quality and promoting the professional and mental well-being of educators. The purpose of this study was to examine the trajectory of emotional burnout among novice ECE teachers over a period of 24 months. We employed Growth Mixed Model (GMM) to measured emotional burnout trends of 2,455 novice ECE teachers over a 24-month period after they just entry into the profession. The emotional burnout contains three domains: emotional exhaustion (EE), depersonalization (DP), and reduced personal accomplishments (PA). The study also examined the impact of education background, rural or urban preschool, gender, and have internship or not, on novice ECE teachers\u0026rsquo; emotional burnout. The findings contribute to the existing theoretical framework on emotional burnout and provide effective intervention strategies to reduce the incidence of emotional burnout, enhancing the overall quality of ECE.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e","manuscriptTitle":"A Longitudinal Study on Emotional Burnout Among Novice Early Childhood Education Teachers: Change from Entry to 24 months","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-07 08:24:02","doi":"10.21203/rs.3.rs-6884218/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-09-22T06:21:18+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-09-21T08:40:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"2819314654305004528685016833714678986","date":"2025-08-27T15:22:55+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-19T05:02:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"185825680542675834360999667442870678830","date":"2025-07-21T14:22:48+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-02T12:44:52+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-02T12:44:12+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-02T12:16:19+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-06-19T03:13:59+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-06-19T03:09:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a2740082-296a-4e47-97db-77e5033d6d48","owner":[],"postedDate":"July 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":50932320,"name":"Biological sciences/Psychology"},{"id":50932321,"name":"Health sciences/Health occupations"}],"tags":[],"updatedAt":"2026-01-12T16:08:15+00:00","versionOfRecord":{"articleIdentity":"rs-6884218","link":"https://doi.org/10.1038/s41598-026-35199-w","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2026-01-09 15:58:02","publishedOnDateReadable":"January 9th, 2026"},"versionCreatedAt":"2025-07-07 08:24:02","video":"","vorDoi":"10.1038/s41598-026-35199-w","vorDoiUrl":"https://doi.org/10.1038/s41598-026-35199-w","workflowStages":[]},"version":"v1","identity":"rs-6884218","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6884218","identity":"rs-6884218","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}