Determinants of the Acceptance of Health-Related Use of Artificial Intelligence in the General Population: A Cross-Sectional Study

Abstract

The successful integration of artificial intelligence (AI) in healthcare hinges on user acceptance, which is influenced by cognitive, emotional, and contextual factors. This study investigates how general attitudes toward AI, e-health readiness (eHR), and technology anxiety (TA) relate to acceptance of AI applications in healthcare. A computer-assisted web survey of 1,108 Polish Internet users assessed acceptance of AI use in healthcare using a 9-item scale. eHR was measured with the seven-item e-Health Readiness Scale, general attitudes toward AI with a five-item Attitudes Towards AI Scale, and TA with the 11-item Technology Anxiety Scale. Multivariable linear regression, controlling for demographics, socioeconomic status, and health conditions, examined predictors of AI acceptance in healthcare. The model explained 43.3% of the variance in acceptance of health-related AI use (R=0.66, adjusted R2=0.42, F(19,1088)=43.76, p<0.001). Higher eHR (B=0.51, 95%CI=0.42-0.60) and general positive AI attitudes (B=0.85, 0.71-0.98) were strong positive predictors. TA showed a modest positive association (B = 0.16, 0.11-0.21), while AI fear was a negative predictor (B=-0.11, -0.19 to -0.02). Male gender and lower social media use also predicted greater acceptance. Digital readiness and positive attitudes drive AI acceptance, with smaller contributions from anxiety. These findings support tailored training to strengthen eHR in order to enhance the adoption of AI-driven health technologies.