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The Study Demands-Resources Framework: An Empirical Introduction

Based on the well-established job demands-resources (JD-R) framework, in our study we introduce the novel study demands-resources (SD-R) framework. The SD-R framework allows the study of salutogenic and pathogenic effects of university settings on students’ health and well-being. Using a large sampl...

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Detalles Bibliográficos
Autores principales: Lesener, Tino, Pleiss, Leonard Santiago, Gusy, Burkhard, Wolter, Christine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7400357/
https://www.ncbi.nlm.nih.gov/pubmed/32709128
http://dx.doi.org/10.3390/ijerph17145183
Descripción
Sumario:Based on the well-established job demands-resources (JD-R) framework, in our study we introduce the novel study demands-resources (SD-R) framework. The SD-R framework allows the study of salutogenic and pathogenic effects of university settings on students’ health and well-being. Using a large sample of university students (n = 5660), our aim was to translate and validate the JD-R’s essential assumptions within the university context, and thus establish the SD-R framework. We performed structural equation modelling to examine these essential assumptions. As assumed, we found that study demands—the “bad things” at university—predict student burnout (β = 0.50), whereas study resources—the “good things” at university—predict student engagement (β = 0.70) as well as burnout (β = −0.35). Also, in line with the SD-R’s assumptions, student burnout predicts life satisfaction negatively (β = −0.34), whereas student engagement predicts life satisfaction positively (β = 0.29). Hence, we were able to introduce the novel SD-R framework and validate its core assumptions. The SD-R framework serves as an excellent theoretical basis to examine both the salutogenic and pathogenic effects of the study context on students’ health and well-being. However, the framework needs further longitudinal and meta-analytical verification in accordance with the research on the JD-R framework.