Factors Influencing Healthcare Professional Adoption of Artificial Intelligence: A Mixed-Methods Systematic Review and Meta-Analysis

The adoption of artificial intelligence (AI) by healthcare professionals is a critical challenge for its successful integration into clinical care. This mixed-methods systematic review and meta-analysis synthesizes quantitative and qualitative evidence to identify key factors influencing this adoption. Based on a meta-analysis of eleven quantitative studies, performance expectancy (perceived usefulness) was the strongest predictor of intention to use (r=0.64), followed by effort expectancy (perceived ease of use), social influence, facilitating conditions, trust, and perceived risk. A qualitative synthesis of 38 studies (including primary research and reviews) revealed that these individual factors are embedded within broader organizational and systemic contexts. Other key determinants include task-technology fit, workflow integration, organizational support, professional identity and autonomy, transparency, governance, and equity considerations. The findings indicate that effective AI adoption requires moving beyond purely technology acceptance models. Success depends on designing tools as part of a comprehensive sociotechnical system that delivers tangible clinical value, integrates seamlessly into routine workflows, operates within transparent and trustworthy governance frameworks, and addresses healthcare professionals' concerns regarding identity and equity.