Articlegold2025

AI-Supported Healthcare Technology Resistance and Behavioral Intention: A Serial Mediation Empirical Study on the JD-R Model and Employee Engagement

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Technology Adoption and User Behaviour Job Satisfaction and Organizational Behavior Artificial Intelligence in Healthcare and Education

Abstract

This study combines innovation resistance theory, the stimulus–organism–response (SOR) framework, and the job demands–resources model to facilitate an in-depth exploration of the barriers faced by healthcare professionals and the psychological responses they exhibit when adopting AI-supported healthcare technologies. We conducted a questionnaire survey and obtained 296 valid responses from healthcare professionals to examine the relationship between resistance to AI-supported healthcare technologies and AI adoption behavioral intentions. Using the SOR framework as a basis, this study validated a serial mediation model with moderating effects, demonstrating that resistance to AI-supported healthcare technologies influenced AI adoption behavioral intentions through job resource, job demand, and levels of employee engagement. Further, this study sought to validate the relationship between age-moderated job resource and job demand in employees exhibiting resistance to AI-supported healthcare technologies and their associated AI adoption behavioral intentions. The results indicated that job resources, job demands, and employee engagement serially mediated the relationship between resistance to AI-supported healthcare technologies and AI adoption behavioral intentions. Additionally, age only exhibited significant moderating effects on the relationship between job demands in resistance to AI-supported healthcare technologies and AI adoption behavioral intentions. The findings of this study can aid in promoting the adoption of AI-supported healthcare technologies by healthcare professionals, generating new insights and broadening the scope and vision of existing literature.

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2003User Acceptance of Information Technology: Toward A Unified View1 2011Sources of Method Bias in Social Science Research and Recommendations on How to Control It 1990PSYCHOLOGICAL CONDITIONS OF PERSONAL ENGAGEMENT AND DISENGAGEMENT AT WORK.2002The Measurement of Engagement and Burnout: A Two Sample Confirmatory Factor Analytic Approach 2001The Influence of Culture, Community, and the Nested‐Self in the Stress Process: Advancing Conservation of Resources Theory 2016Job demands–resources theory: Taking stock and looking forward.2010Job Engagement: Antecedents and Effects on Job Performance 2015Common methods variance detection in business research

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