ArticleFrontiers in psychology2026
Preschool teachers' AI adoption and occupational well-being: an integrated TAM-JD-R analysis of technostress dual-edged effects.
Article in Frontiers in psychology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: The rapid integration of generative artificial intelligence (AI) in early childhood education presents both opportunities and challenges for preschool teachers, yet empirical investigations explicating adoption mechanisms and well-being implications remain scarce. This study developed and tested an integrated framework synthesizing the Technology Acceptance Model (TAM) and Job Demands-Resources (JD-R) theory to examine how cognitive evaluations, technostress dimensions, and contextual factors jointly determine AI adoption intentions and occupational well-being among preschool teachers. Methods: Survey data from 300 Chinese preschool teachers, recruited via multistage stratified random sampling, were analyzed through covariance-based structural equation modeling. Results: Results confirmed TAM's core pathways, with perceived usefulness ( Discussion: These findings advance understanding of technology adoption in early childhood education by demonstrating that technostress operates through dual pathways-facilitating and impeding adoption-moderated by organizational and personal resources. Practical implications include targeted support strategies that buffer hindrance stressors while cultivating challenge-oriented appraisals among preschool teachers.
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