ObjectiveThis study investigates the factors influencing physicians’ acceptance and adoption of artificial intelligence (AI) technologies in clinical practice, integrating the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM), while also examining the mediating role of trust.MethodsA structured survey was conducted among 414 physicians assessing their perceptions of AI technologies using constructs from TPB, TAM, and trust-related factors. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed for data analysis.ResultsFindings confirm that TPB and TAM effectively explain physicians’ AI acceptance, with TPB exhibiting a stronger predictive power compared to TAM. Trust emerged as a critical determinant in AI adoption, fully mediating the relationship between perceived behavioral control (p < 0.001), subjective norms (p < 0.05), perceived usefulness (p < 0.001), ease of use (p < 0.001), and behavioral intention. Notably, perceived ease of use (p < 0.001) had the strongest direct impact on trust, while perceived usefulness (p < 0.001) significantly influenced behavioral intention. Attitude toward AI showed a significant effect (p < 0.01). Subjective norms and perceived behavioral control had weaker direct influences (p < 0.05 and p = 0.07, respectively).ConclusionTrust plays a pivotal role in AI adoption, shaping physicians’ acceptance beyond traditional TPB and TAM factors. Healthcare administrators, policymakers, and technology developers should focus on enhancing trust by improving AI transparency, interpretability, and user-friendly design.
Analysis of intellectual property strategies across different categories of digital therapeutics
Advances in digital technology and the coronavirus disease (COVID-19) pandemic have accelerated the digital transformation of healthcare. Digital therapeutics (DTx), which deliver evidence-based interventions through