Buffer or Boost? The Role of Job Resources in Predicting Teacher Work Engagement and Emotional Exhaustion in Different School Types

Drawing upon the Job Demands-Resources (JD-R) model, this study examines the association between different school types and teacher work engagement as well as emotional exhaustion, in addition to the moderating roles of job (collegial and school management support) and individual (resilience) resources. We utilized multivariate regression models with interaction terms, applied to data from the GEW-Frühjahrsreport 2025—a cross-sectional quantitative survey assessing teacher well-being (TWB) among a representative sample of 5859 teachers in North Rhine-Westphalia. The findings reveal that vocational and special needs schools are associated with significantly higher work engagement and lower emotional exhaustion compared to other school types. Resilience emerged as the strongest predictor across both outcomes, followed by school management support. Moderation analyses indicate predominantly boosting effects, meaning that job resources exert greater positive influence in already-favorable school contexts. These results challenge the assumption that job resources primarily serve as buffers in high-demand settings. Instead, the study highlights the importance of systemic conditions and leadership quality in enabling the effective utilization of resources. Implications are discussed with regard to professional development, structural school reform, and the integration of well-being into educational policy.

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Publication Details

Journal
Education Sciences
Published
2025-06-06
DOI
https://doi.org/10.3390/educsci15060708
Citations
2
Primary Topic
Early Childhood Education and Development
Type
article
Field-Weighted Citation Impact
17.85
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article

Buffer or Boost? The Role of Job Resources in Predicting Teacher Work Engagement and Emotional Exhaustion in Different School Types

Christian Reintjes, Till Kaiser, I.J. Winter, Gabriele Bellenberg
2 citations
Education Sciences
Early Childhood Education and Development
17.85
article

Buffer or Boost? The Role of Job Resources in Predicting Teacher Work Engagement and Emotional Exhaustion in Different School Types

Christian Reintjes, Till Kaiser, I.J. Winter, Gabriele Bellenberg
article en
2 citations

Abstract

Drawing upon the Job Demands-Resources (JD-R) model, this study examines the association between different school types and teacher work engagement as well as emotional exhaustion, in addition to the moderating roles of job (collegial and school management support) and individual (resilience) resources. We utilized multivariate regression models with interaction terms, applied to data from the GEW-Frühjahrsreport 2025—a cross-sectional quantitative survey assessing teacher well-being (TWB) among a representative sample of 5859 teachers in North Rhine-Westphalia. The findings reveal that vocational and special needs schools are associated with significantly higher work engagement and lower emotional exhaustion compared to other school types. Resilience emerged as the strongest predictor across both outcomes, followed by school management support. Moderation analyses indicate predominantly boosting effects, meaning that job resources exert greater positive influence in already-favorable school contexts. These results challenge the assumption that job resources primarily serve as buffers in high-demand settings. Instead, the study highlights the importance of systemic conditions and leadership quality in enabling the effective utilization of resources. Implications are discussed with regard to professional development, structural school reform, and the integration of well-being into educational policy.

Education SciencesVol. 15(6)
Osnabrück University (DE), Ruhr University Bochum (DE)
Openalex Percentile: Top 1%
Early Childhood Education and Development
17.85
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Buffer or Boost? The Role of Job Resources in Predicting Teacher Work Engagement and Emotional Exhaustion in Different School Types — Christian Reintjes, Till Kaiser, et al. · Education Sciences (2025) | TGRS Research Map | TGRS