Resilient Teachers in a Strained System: Mental Health and Resilience Amidst School Transformation Processes

Abstract

In light of profound transformation processes within the education system—such as digitalization, increasing societal pluralization, and global crises—growing attention is being paid to the mental health and resilience of teachers. This paper draws on the Job Demands–Resources (JD-R) model to explore, both theoretically and empirically, how individual and organizational resources influence teachers’ professional agency. The analysis is based on data of the GEW-Frühjahrsreport 2025 (March 2025), from 5859 teachers in North Rhine-Westphalia. The findings reveal that emotional exhaustion and work engagement are significantly shaped by personal resilience, collegial support, and leadership culture. Resilience demonstrates a dual function, acting as a protective factor against exhaustion and as a motivational driver of engagement. In conjunction with leadership and collegiality resilience, it exerts significant indirect effects on teachers’ commitment and job satisfaction via emotional exhaustion and work engagement. The results underscore the need for a systemic understanding of resilience that integrates individual coping capacities with structural conditions. This article offers practice-oriented implications for health-promoting school development and advocates for the strategic integration of resilience promotion at the individual, collegial, and institutional levels.

1. Introduction

Education systems worldwide are under immense pressure to adapt to profound and ongoing change. Technological innovation, societal pluralization, the digital transformation of teaching and learning processes, and, not least, global crises such as the COVID-19 pandemic and climate change demand a fundamental reconfiguration of school organizations. At the same time, teachers have increasingly come into focus as key actors in determining how education can not only be sustained under adverse conditions but also further developed in terms of quality. Teachers make a vital contribution to educational outcomes and school climate; they serve as crucial links between system and individual, between institution and pedagogical relationship. Their mental health and professional agency are therefore considered pivotal to the overall resilience of the education system.

Resilient teachers are better prepared to handle daily challenges and report higher job satisfaction and instructional quality (Lu et al., 2024). Moreover, they contribute to a resilient school culture by modeling problem-solving and perseverance for their students (Lu et al., 2024).

Against this backdrop, it is becoming increasingly important not only to examine the stressors teachers face but also to identify the protective and resource-related factors that enable them to remain capable, engaged, and healthy under challenging conditions. Resilience—understood as the capacity to develop positively despite adverse circumstances—offers a promising conceptual framework in this regard. Resilient teachers are able to tolerate uncertainty, respond constructively to setbacks, and actively embrace new challenges. At the same time, resilience is not merely an individual trait but is closely linked to the structural and organizational conditions under which schooling takes place.

Resilience is conceptualized as a collective challenge and as a goal of professional school development. It requires critical engagement with working conditions, leadership culture, and support structures within the education system. In this context, teachers’ mental health is not solely a personal concern but also a structural and political issue.

This article addresses the question of how teachers’ mental health and resilience can be strengthened in the face of current transformations in schooling. Central to the analysis is the Job Demands–Resources (JD-R) model, which serves as a theoretical framework for examining occupational stress and resources in the teaching profession. Drawing on recent empirical data from the 2025 GEW-Frühjahrsreport, the article investigates key factors influencing emotional exhaustion and work engagement. The objective is to derive both theoretical insights and practice-oriented implications for fostering resilience within educational systems.

2. Theoretical Framework: The Job Demands–Resources Model and the Concept of Resilience

2.1. The JD-R Model as an Analytical Framework

The Job Demands–Resources (JD-R) model (Demerouti et al., 2001) distinguishes between two central categories of work-related factors: demands and resources. Demands are understood as stressors that consume energy and can potentially lead to exhaustion—examples include high performance pressure, student behavioral issues, or emotional strain. In contrast, resources act both as motivational drivers and as protective factors against such demands. These include, among others, social support from colleagues, leadership quality, opportunities for self-regulation, and personal traits such as resilience and self-efficacy (Bakker & Demerouti, 2007).

In the school context, the JD-R model proves particularly relevant, as it accounts for the complex interplay between individual, team-related, and structural variables. Empirical studies have shown that collegial collaboration, transparent communication by school leadership, and perceived autonomy are especially critical resources for teachers’ occupational well-being (Keller-Schneider, 2014).

Moreover, the JD-R model offers a dynamic understanding of these interactions: High demands can, under certain conditions, be offset by sufficient resources, while the absence of resources may lead to strain even when demands are moderate. This makes the model particularly useful for analyzing educational settings, where structural and interpersonal factors are deeply intertwined. Recent extensions of the JD-R model also emphasize the role of personal resources such as optimism, mindfulness, and goal orientation, which can moderate how demands are perceived and experienced (Xanthopoulou et al., 2007).

The JD-R model further allows for distinguishing between hindrance and challenge demands. While hindrance demands deplete energy and hinder goal achievement, challenge demands can promote personal growth and performance when supported by adequate resources (Lu et al., 2024).

One of the model’s particular strengths lies in its practical applicability: it can serve as a basis for internal school analyses and targeted interventions aimed at identifying stressors and enhancing available resources. Thus, the JD-R model contributes not only to theoretical development in occupational health psychology but also offers practice-oriented insights for school improvement and teacher education.

2.2. Resilience in the Context of School Work

In psychological research, resilience is understood as a dynamic process of adaptation to adverse circumstances (Masten, 2014). It is not merely about “enduring” or “surviving” difficult situations but about engaging with stressors in a constructive way that can lead to personal growth. Key protective factors operate at both the individual level (e.g., emotional regulation, coping strategies, sense of purpose) and the social level (e.g., social networks, institutional support) (Rutter, 2006).

Resilience is not merely the result of external conditions but also depends on personal resources such as self-efficacy, optimism, and emotion regulation (Lu et al., 2024). Within educational contexts, teachers’ resilience has been found to be closely linked to their self-efficacy, professional identity, and capacity for emotion regulation (Howard & Johnson, 2004). At the same time, it is increasingly evident that resilience cannot be viewed solely as an individual trait. Rather, it emerges from the interaction between personal capacities and organizational and systemic conditions (Brunetti, 2006).

Resilient teachers typically exhibit a proactive stance toward challenges, demonstrate flexibility in adapting to change, possess a realistic self-concept, and maintain stable social relationships within their professional environment. Studies indicate that resilient educators are less prone to burnout, are more likely to remain in the profession, and often function as catalysts for health-promoting structures within their schools (Beltman et al., 2011).

Furthermore, resilience may be considered a key competence for implementing school reforms and navigating innovation processes. Teachers with resilient coping patterns are better equipped to handle the pressures of reform, reflect on complex demands, and respond constructively to new situations (Gu & Day, 2007). In this sense, resilience constitutes a prerequisite for professional continuity and agency—and thereby also for the resilience of the school system as a whole.

The report “Education and Resilience” by the German Expert Council on Education (Aktionsrat Bildung; Anders et al., 2022) accordingly argues that educational institutions must be conceptualized as resilient organizations in order to effectively foster the individual resilience of their members—especially of teachers. This includes, not least, a cultural shift that recognizes mental health as being on par with academic excellence and creates structural conditions that support mindfulness, reflection, and self-care.

2.3. Research Questions

This study addresses the following key research questions:

• How does individual teacher resilience influence emotional exhaustion and work engagement?
• What role do organizational resources—particularly collegial support and leadership quality—play in fostering teacher resilience?
• How do individual and organizational resources jointly affect teachers’ mental health, work engagement, and job satisfaction within the framework of the Job Demands–Resources (JD-R) model?

3. Data and Methods

3.1. Data Source and Study Design

We used data of the GEW-Frühjahrsreport 2025 (March 2025) (Reintjes et al., 2025) that investigates the mental health of teachers with particular emphasis on individual and organizational resources. The study is based on a representative, state-wide sample of 5859 teachers working at public schools in North Rhine-Westphalia. The German school system is divided into primary school (elementary level), lower secondary school (Hauptschule, Realschule, Gymnasium, and Gesamtschule), and upper secondary school (gymnasial upper level and vocational schools). Participant selection accounted for all school types as well as regional distributions.

Data collection took place in spring 2025 via a standardized online questionnaire, which combined validated psychometric instruments with context-specific items developed to reflect the particularities of different school types. The survey was disseminated through school administrations and union channels, with participation being voluntary and anonymous.

The dataset included variables such as: Sociodemographic characteristics (e.g., age, gender, professional experience), institutional indicators (e.g., school type, school size, leadership role), and psychological constructs related to stress, well-being, and resources. It is important to note some limitations of our data. As a cross-sectional study, it is difficult to draw definitive conclusions about cause and effect. Additionally, the voluntary nature of the survey and reliance on online participation may introduce some self-selection bias. Additionally, the findings are based on data from North Rhine-Westphalia and may not be directly transferable to other regions.

3.2. Measures

Compared to previous research, the review by Lu et al. (2024) shows that the majority of studies employed qualitative designs (41%), while only a small portion used longitudinal or experimental approaches. Overall, the methodological quality of quantitative studies was higher than that of qualitative ones.

To assess the central constructs of the study, we employed a set of well-established and psychometrically validated measurement scales. Emotional exhaustion was measured using the corresponding subscale of the Maslach Burnout Inventory (Maslach et al., 1996; German version: Enzmann & Kleiber, 1989). Work engagement was assessed via the German version of the Utrecht Work Engagement Scale (UWES-9) developed by Schaufeli and Bakker (2003). Individual resilience was measured using the RS-11 Resilience Scale by Schumacher et al. (2005). Collegial support and perceived leadership quality were operationalized using subscales from the Teacher Work Assessment Checklist (Arbeits-Bewertungs-Check für Lehrkräfte) by Kieschke and Schaarschmidt (2007). General self-efficacy was captured using the scale by Schwarzer and Schmitz (1999), while Big Five personality traits were measured using the short-form TIPI-G developed by Muck et al. (2007). Job satisfaction was assessed using a single-item measure adapted from the OECD TALIS framework (OECD, 2013). In addition, social support in the private sphere was measured using a subscale from the AVEM-K instrument (Schaarschmidt & Fischer, 2001). The internal consistencies of the multi-item scales (Cronbach’s α) ranged between 0.86 and 0.95.

3.3. Methods

In a first step descriptive statistics are reported before we test our theoretical assumptions, using structural equation modeling (SEM). SEM allows for the modeling of latent variables, thereby correcting for measurement error and avoiding biased parameter estimates (e.g., Bollen, 2009). In addition, SEM enables the analysis of indirect effects and allows for testing the robustness of their significance using bias-corrected confidence intervals (e.g., Hayes, 2013). To appropriately address missing data, we applied the Full Information Maximum Likelihood (FIML) estimation method. FIML is considered one of the most reliable approaches for handling missing data, particularly when data are missing at random (Arbuckle, 1996; Enders & Bandalos, 2001).

4. Results

4.1. Descriptive Results

Before testing our theoretical model with a structural equation model, we briefly examine the variables under investigation and their related descriptive summaries. In terms of the effect size of the bivariate relationships, we follow the interpretation by Cohen (1992): small (r = 0.1), medium (r = 0.3), and large (r = 0.5).

First, we take a look at the job resources. Resilience is central as an individual job resource. In our data, the mean value is 5.5 (SD = 0.73), which suggests a relatively resilient group based on the scale. With regard to external job resources, we can observe that collegial support has a relatively high mean value of 5.1 (SD = 1.3) School management support was also assessed on a 7-point scale and has a mean value of 4.1 (SD = 1.5), which is lower than collegial support. Turning to job demands, we find that the average number of mentions of special tasks is 2.6 (SD = 1.4). Additionally, 59 percent of teachers indicate that their largest class includes up to 19 students, while 41 percent of female teachers report that their largest class has at least 20 students and up to 40 students. The mediating variables, emotional exhaustion, measured on a 7-point scale, have a mean of 4 (SD = 1.1), and work engagement, also measured on a 7-point scale, has a mean of 4.4 (SD = 1.0). Regarding the expected relationships, significant correlations (p < 0.05) can be observed between job demands and the mediating variables. Specifically, there are correlations between job demands and emotional exhaustion, with coefficients ranging from r = 0.09 to 0.01. Additionally, between job demands and work motivation, it is interesting to note that the relationship with class size is negative (r = −0.09), while the relationship with additional tasks is positive (r = 0.08). Regarding resources, significant correlations (p < 0.001) are also observed. Resilience (r = 0.36), colleague support (r = −0.25), and school management support (r = −0.33) are related to emotional exhaustion, as well as to work motivation. The correlations for resilience with work motivation are r = 0.43, for colleague support r = 0.32, and for school management support r = 0.37. Overall, there are notably larger correlations between resources and the mediating variables than between stressors and the mediating variables. The outcome variables, organizational commitment (M = 4.3, SD = 1.3) and job satisfaction (M = 4.2, SD = 1.5), were also measured on a 7-point scale. Here, significant correlations (p < 0.01) are observed between organizational commitment and the predictor variables, with r = −0.4797 for emotional exhaustion and r = 0.5784 for work engagement. For job satisfaction, there are associations of r = −0.66 with emotional exhaustion and r = 0.57 with work engagement. Bivariately, relationships can be explored that align with the Job Demands-Resources Model, even though the correlations vary quite significantly in their strength.

The subsequent multivariate analyses offer the opportunity to obtain a more detailed understanding by controlling for confounding variables through third-variable control, correcting measurement errors using latent variables, and determining the magnitude and significance of the indirect effects of job demands and resources on the outcome variables

4.2. Multivariate Results

4.2.1. Structural Equation Model: JD-R Model with Demands and Resources

Based on the Job Demands–Resources (JD-R) framework, we estimated a structural equation model that incorporates both central job demands (class size, number of additional responsibilities) and key resources at the individual (resilience) and organizational level (collegial support, support from school leadership). The outcome variables were organizational commitment and job satisfaction. Following the explanations for interpreting standardized coefficients as effect sizes, effect sizes were categorized as small (β = 0.10–0.29), medium (β = 0.30–0.49), and large (β ≥ 0.50) (Fey et al., 2023; Nieminen, 2022). Concerning the direct effects, it can be observed (see Figure 1) that the results of the descriptive analyses are nearly confirmed, specifically that the strongest relationships are found between job resources and the mediating variables, as well as between the mediating variables and the outcome variables. In the following, the indirect effects will be reported and interpreted.

Resilience shows by far the strongest indirect effects on both outcome variables (see

Table 1. (a) Indirect effects from Resilience to Organizational Commitment. (b) Indirect effects from Resilience to Organizational Commitment (standardized coefficients).

(a)
	Estimate	S.E.	p-Value
Total indirect	0.322	0.011	0.000
Specific indirect 1
Organizational Commitment
Work Engagement
Resilience	0.259	0.012	0.000
Specific indirect 2
Organizational Commitment
Emotional Exhaustion
Resilience	0.063	0.009	0.000
(b)
	Estimate	S.E.	p-Value
Total indirect	0.403	0.011	0.000
Specific indirect 1
Job Satisfaction
Work Engagement
Resilience	0.242	0.011	0.000
Specific indirect 2
Job Satisfaction
Emotional Exhaustion
Resilience	0.160	0.009	0.000

a,b, with a total indirect effect of β = 0.322 (p < 0.001) on organizational commitment and β = 0.403 (p < 0.001) on job satisfaction. These effects operate through both increased work engagement (β = 0.259 and β = 0.242, respectively) and reduced emotional exhaustion (β = 0.063, p < 0.001 and β = 0.160, p < 0.001). This dual pathway highlights the key role of resilience as a personal resource in the teaching profession. Support from school leadership also shows significant indirect effects (see

Table 2. (a) Indirect effects from School Management Support to Organizational Commitment. (b) Indirect effects from School Management Support to Job Satisfaction (standardized coefficients).

(a)
	Estimate	S.E.	p-Value
Total indirect	0.215	0.012	0.000
Specific indirect 1
Organizational Commitment
Work Engagement
School Management Support	0.172	0.012	0.000
Specific indirect 2
Organizational Commitment
Emotional Exhaustion
School Management Support	0.043	0.007	0.000
(b)
	Estimate	S.E.	p-Value
Total indirect	0.270	0.013	0.000
Specific indirect 1
Job Satisfaction
Work Engagement
School Management Support	0.161	0.011	0.000
Specific indirect 2
Job Satisfaction
Emotional Exhaustion
School Management Support	0.109	0.009	0.000

a,b), amounting to β = 0.215 (p < 0.001) for organizational commitment and β = 0.270 (p < 0.001) for job satisfaction. The effects are transmitted via both the motivational pathway (through work engagement) and the protective pathway (through reduced exhaustion), emphasizing the importance of a participatory, transparent, and appreciative leadership culture. Collegial support exhibits similarly positive, though somewhat weaker, effects (see

Table 3. (a) Indirect effects from Collegial Support to Organizational Commitment. (b) Indirect effects from Collegial Support to Job Satisfaction (standardized coefficients).

(a)
	Estimate	S.E.	p-Value
Total indirect	0.068	0.011	0.000
Specific indirect 1
Organizational Commitment
Work Engagement
Collegial Support	0.061	0.011	0.000
Specific indirect 2
Organizational Commitment
Emotional Exhaustion
Collegial Support	0.007	0.003	0.027
(b)
	Estimate	S.E.	p-Value
Total indirect	0.074	0.013	0.000
Specific indirect 1
Job Satisfaction
Work Engagement
Collegial Support	0.057	0.010	0.000
Specific indirect 2
Job Satisfaction
Emotional Exhaustion
Collegial Support	0.017	0.007	0.019

a,b), with β = 0.068 (p < 0.001) for organizational commitment and β = 0.074 (p < 0.001) for job satisfaction, where the engagement pathway is particularly relevant. The comparatively lower effect size relative to leadership support may reflect the greater context dependence of collegial dynamics. Class size has consistently negative effects (see

Table 4. (a) Indirect effects from Size of Class to Organizational Commitment. (b) Indirect effects from Size of Class to Job Satisfaction (standardized coefficients).

(a)
	Estimate	S.E.	p-Value
Total indirect	−0.035	0.009	0.000
Specific indirect 1
Organizational Commitment
Work Engagement
Size of Class	−0.022	0.008	0.007
Specific indirect 2
Organizational Commitment
Emotional Exhaustion
Size of Class	−0.013	0.003	0.000
(b)
	Estimate	S.E.	p-Value
Total indirect	−0.053	0.010	0.000
Specific indirect 1
Job Satisfaction
Work Engagement
Size of Class	−0.021	0.008	0.007
Specific indirect 2
Job Satisfaction
Emotional Exhaustion
Size of Class	−0.032	0.006	0.000

a,b), with β = −0.035 (p < 0.001) for organizational commitment and β = −0.053 (p < 0.001) for job satisfaction. Additional responsibilities, such as administrative tasks or coordination roles, show an ambivalent pattern of effects (see

Table 5. (a) Indirect Effects from Special Tasks to Organizational Commitment. (b) Indirect Effects from Special Tasks to Job Satisfaction (standardized coefficients).

(a)
	Estimate	S.E.	p-Value
Total indirect	0.024	0.008	0.005
Specific indirect 1
Organizational Commitment
Work Engagement
Special Tasks	0.033	0.008	0.000
Specific indirect 2
Organizational Commitment
Emotional Exhaustion
Special Tasks	−0.009	0.003	0.000
(b)
	Estimate	S.E.	p-Value
Total indirect	0.007	0.009	0.432
Specific indirect 1
Job Satisfaction
Work Engagement
Special Tasks	0.031	0.007	0.000
Specific indirect 2
Job Satisfaction
Emotional Exhaustion
Special Tasks	−0.023	0.006	0.000

a,b): they exert a positive influence via increased engagement (β = 0.033, p < 0.001 for organizational commitment and β = 0.031, p < 0.001 for job satisfaction) but a negative influence via increased exhaustion (β = −0.009, p < 0.001 and β = −0.023, p < 0.001, respectively). These findings point to a tension: while additional roles may foster recognition, responsibility, and motivation, they also carry the risk of overload if not adequately supported by resources.

4.2.2. Interpretation in Light of the JD-R Model

The results confirm the core assumption of the Job Demands–Resources (JD-R) model: job demands affect employee outcomes through both motivational and health-impairing pathways, while resources—at both the individual and organizational levels—can buffer strain and enhance motivation.

Notably, our findings show that resilience operates across both pathways simultaneously, functioning as a dual resource that protects against exhaustion while enhancing engagement. The mixed effects of additional responsibilities highlight the need for a nuanced approach to job design in schools: such responsibilities should not be introduced in isolation but embedded within supportive structures and cooperative practices to unlock their potential benefits. Importantly, teacher resilience is not a fixed trait but a malleable capacity that can be systematically strengthened through targeted training and long-term developmental initiatives (Lu et al., 2024).

5. Discussion: Building Resilience Between Individual Adaptation and Systemic Responsibility

The review by Lu et al. (2024) stresses that future research and practice should further investigate how to differentiate hindrance demands from challenge demands, since these categories lead to very different outcomes for teacher well-being and resilience. Moreover, Lu et al. (2024) show that the methodological quality of existing studies varies substantially, with quantitative studies often stronger than qualitative ones. This underlines the need for more longitudinal and intervention-based research to understand how resilience can be cultivated sustainably in schools. The review by Lu et al. (2024) highlights two important discussion points. First, it stresses the need to differentiate hindrance demands from challenge demands, as these categories lead to very different outcomes for teacher well-being and resilience. Second, the review shows that the methodological quality of existing studies varies substantially, with quantitative studies often stronger than qualitative ones. This underlines the need for more longitudinal and intervention-based research to understand how resilience can be cultivated sustainably in schools.

Several limitations need to be acknowledged. The results are based on data from North Rhine-Westphalia and may not be directly generalizable to other regions. Moreover, the data collection was conducted online and relied on self-reports, which may introduce potential biases. Finally, the cross-sectional design does not allow for causal conclusions.

The multivariate analysis highlights the central role of individual resilience within the JD-R framework. Its dual effect—protective via the reduction in emotional exhaustion and motivational via the enhancement of work engagement—positions resilience as a key structural element within the architecture of resilient school organizations. Unlike isolated or one-time interventions, these mechanisms exert a long-term stabilizing influence on both organizational commitment and job satisfaction.

This challenges traditional stress-compensation models and suggests that systemic resilience emerges not from eliminating deficits, but from the strategic cultivation of organizational resources.

This insight aligns with the guiding idea of the Special Issue: education should not be seen primarily as a site for individual coping, but rather resilience should be understood as a systemic resource. Teachers’ mental health, in this light, can be regarded as an indicator of a school’s overall resilience (Kutsyuruba et al., 2019): only in learning- and health-promoting environments can teachers act professionally over time.

Thus, resilience promotion must not be limited to isolated measures, such as individual coaching sessions, but rather be established as an integral component of strategic school development. This requires a systematic perspective on organizational structures, leadership practices, and cultures of collaboration. This includes the following 4 Points: 1. Binding structures for collegial collaboration, such as professional learning communities, peer feedback systems, and interdisciplinary teamwork. 2. Reliable leadership culture, where school leaders act as agents of health promotion by fostering transparent communication, participatory decision-making, and appreciative recognition. 3. Support for self-regulation, through protected time for planning and reflection, access to supervision, and structured spaces for professional dialogue. 4. Structural relief, including clear task allocation, administrative support, and the avoidance of overload from additional project assignments.

The calibration of these measures is crucial: as shown in the findings on additional responsibilities, the same job demand can be perceived either as a stressful burden or as a developmental challenge, depending on the level of available resources. Therefore, task distribution within schools must be more closely aligned with individual resource profiles and the school system as a whole.

In sum, only through an integrated approach—anchored at the individual, collegial, and organizational levels—can resilience be sustainably established within the education system.

6. Conclusions and Implications for Research and Practice

This study provides empirical evidence that school context significantly affects TWB and that individual and job resources play a key role in enhancing work engagement. These insights should inform leadership training and systemic reform toward resource-enabling school environments.

Particularly noteworthy are the differentiated path effects uncovered through advanced modeling: resilience, leadership support, and collegiality influence key outcomes via distinct mechanisms—either through work engagement or through reduced emotional exhaustion—and help explain job satisfaction and organizational commitment. These multi-dimensional pathways call for a more complex and systemic understanding of health promotion in schools than is typically applied.

Resilience promotion must be systemically embedded within schools; simply strengthening individual competencies is insufficient without addressing underlying structural prerequisites. Both educational policymakers and school authorities share the responsibility of creating enabling conditions through effective resource allocation, clearly defined roles, and genuine opportunities for participation. Importantly, a differentiated approach is needed, as the results demonstrate variations in workload and resource efficacy across different school types. Consequently, interventions must be context-sensitive and specifically targeted to meet the unique needs of each school environment.

Furthermore, the data suggest that key stressors—such as the number of additional responsibilities—are not universally detrimental. Depending on the context, they may have opposing effects: motivational benefits via increased engagement versus health risks via emotional exhaustion. This duality requires a more deliberate management of job demands, for instance through formal reflection cycles in task distribution.

Resilience does not present as a static personality trait but as a dynamic, context-sensitive, and socially embedded phenomenon. It arises from the interaction between individual coping skills and the structural, social, and cultural conditions within educational organizations. Schools seeking to meaningfully promote resilience must therefore go beyond the role of instructional institutions—they must operate as professional learning and development communities. This requires intentional, strategically guided design of resilience-enhancing conditions—value-oriented and transparent leadership, robust collegial networks, and education policy measures aimed at the long-term support and relief of educational professionals.

6.1. Implications for Research

To advance a systemically grounded understanding of resilience in the teaching profession, targeted empirical research is required, including (1) longitudinal studies assessing the long-term effects of resilience-building measures—at both individual and organizational levels, (2) impact research on systemic interventions, such as the introduction of supervision, establishment of collegial case consultation formats, or development of stress-sensitive leadership cultures and (3) international comparative studies exploring how different educational cultures, school systems, and teacher training models shape resilience mechanisms.

6.2. Implications for Practice

Concrete steps can already be taken within school practice to foster resilience. It is essential that such measures are not isolated but embedded within a broader strategy of school health and quality development. This includes embedding resilience promotion as a cross-cutting objective in all phases of teacher education—both in university-based training, the preparatory service, and in continuing professional development.

Furthermore, schools should develop and implement health and stress prevention concepts based on the Job Demands–Resources (JD-R) model, focusing on both individual well-being and organizational resources. Crucially, this requires fostering a leadership culture built on appreciation, participation, and professional autonomy, actively supported by school supervisory authorities through targeted training, ongoing monitoring, and the implementation of supportive structural incentives.