Vural Özkan, Gülşah

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Dr.Öğrt.Gör.
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01.01.05.03. Psikoloji Bölümü
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Journal of Organizational Effectiveness1
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  • Article
    Rethinking Job Demands–Resources-Based Interventions for Evolving Work Environments: A Problematizing Review
    (Emerald Group Publishing Ltd, 2026) Vural Özkan, Gülşah; Yavuz Serçekman, Meltem; Ayaz, Özlem; Kilic Hawarneh, Ozge
    PurposeThe Job Demands-Resources (JD-R) theory is widely used for workplace interventions targeting well-being, satisfaction and burnout reduction. However, shifting work contexts raise questions about the adaptability of its core constructs. This paper aims to critically examine how JD-R theory has been applied in intervention design, with particular attention to the assumptions that may limit responsiveness across diverse organizational and cultural settings.Design/methodology/approachAdopting a problematization review approach, we analyze 109 studies that employ the JD-R theory in the design of workplace interventions. Our review identifies underlying assumptions, conceptual tensions and the ways in which demands and resources have been interpreted across different contexts, roles and cultures.FindingsThe review reveals that JD-R constructs are often treated as stable and universally applicable, thereby constraining adaptability. We highlight overlooked assumptions and tensions, proposing a taxonomy of interventions that emphasizes contextual sensitivity, design flexibility and cross-level integration.Practical implicationsThe proposed taxonomy offers organizations a framework for developing workplace interventions that better align with diverse employee needs and evolving work environments.Social implicationsBy promoting more sustainable and responsive workplace interventions, this study supports healthier and more equitable organizational practices, with potential benefits for employee well-being across diverse cultural and occupational contexts.Originality/valueThis paper applies problematization review to JD-R interventions, offering a novel critique that highlights contextual variation and adaptability, while providing a practical taxonomy for future applications.