ArticleHealth science reports2026
Modeling Factors Affecting Physicians' Acceptance of E-Prescriptions Using Structural Equation Modeling-Partial Least Squares Analysis: A Cross-Sectional Study.
Article in Health science reports, 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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5 authors.
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Abstract
Background and Aims: The acceptance of technology is a critical factor influencing the success of health information systems. This study aimed to investigate the key factors affecting physicians' acceptance of electronic prescription (e-prescription) systems by applying a structured partial least squares structural equation modeling (PLS-SEM) approach. Methods: This cross-sectional descriptive-analytical study integrated constructs from three theoretical frameworks: the technology acceptance model (TAM), the innovation diffusion theory (IDT), and the health belief model (HBM). A researcher-developed questionnaire was designed based on these models. The questionnaire underwent a three-step validation process: face validity assessment, content validity ratio (CVR) calculation, and reliability testing using Cronbach's alpha ( Results: The results showed that relative advantage, compatibility, and perceived ease of use significantly influenced perceived usefulness and benefits. These variables, along with perceived usefulness and benefits, were also significantly associated with behavioral intention and e-prescription acceptance. However, cues to action did not have a meaningful effect on behavioral intention. Among all variables, perceived usefulness and benefits had the strongest impact on behavioral intention, while relative advantage showed a weaker but still significant influence. Conclusion: The findings suggest that health policymakers should prioritize enhancements to system usability, usefulness, and alignment with physicians' needs to facilitate adoption. Efforts to increase acceptance should include better training, intuitive system design, responsiveness to user feedback, and active promotion of the system's benefits over traditional methods.
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