Influencing public acceptance of artificial intelligence (AI) in healthcare delivery

作者：Selin Aras, Calvin Drakos, Vineesha Manimangalam, Moiz Ali Nasir, Christina Burns, Davey M. Smith, Ozlem Equils · 发表于：Frontiers in Digital Health · 年份：2026 · DOI：10.3389/fdgth.2025.1664345 · 被引用次数：8 · 研究领域：Artificial Intelligence in Healthcare and Education、Digital Mental Health Interventions、AI in Service Interactions

Introduction Despite the potential of artificial intelligence (AI) to transform healthcare delivery and reduce costs, adoption remains uneven across populations. Understanding the demographic, behavioral, and cognitive factors influencing public willingness to use AI-powered health tools is critical for equitable implementation. This study examined determinants of AI adoption in healthcare among adults in the United States (U.S.). Methods A cross-sectional survey was conducted between March and June 2024 using convenience sampling across the U.S. The study included 568 adult respondents recruited via Qualtrics. The survey assessed demographic characteristics, digital health behaviors, self-reported health status, cognitive and attitudinal factors, and behavioral intentions related to AI use in healthcare. Logistic regression models were used to examine associations between predictors and willingness to adopt AI, with z-tests for subgroup comparisons and Bonferroni correction applied for multiple hypothesis testing. Results The sample was predominantly female (66.7%) and Hispanic/Latino (50.7%), with moderate income and education levels. Older age was negatively associated with AI adoption ( β = −0.029), males were less likely to use AI than females ( β = −0.388), and income was positively correlated with AI adoption ( β = 0.096). Trust in AI was substantially lower than trust in physicians: 14.6% trusted ChatGPT's diagnosis for serious illness compared with 92.3% trusting phy...