Human Engagement with Artificial Intelligence in Health: Trust, Literacy, Adoption and Responsible Use

Artificial intelligence (AI), including generative AI and large language models, is increasingly shaping how people access, interpret and use health information, communicate about health, and make health-related decisions. AI-enabled tools are now being used across a wide range of settings, from consumer health information seeking and lifestyle advice to patient education, clinical communication, decision support and digital health interventions.Alongside these opportunities, the rapid adoption of AI raises important questions about how individuals understand, trust, evaluate and use AI-generated information and recommendations. Users may differ substantially in their willingness to rely on AI, their ability to critically assess its outputs, whether they verify information using other sources, and whether they ultimately act on AI-generated advice. AI literacy, health literacy, digital literacy, perceived credibility, transparency, usability, prior experience and broader social and contextual factors may all influence these behaviours.This Research Topic will bring together interdisciplinary research examining human engagement with AI in health and healthcare, with particular interest in how patients, consumers, health professionals and other users perceive, understand, evaluate, adopt and interact with AI-enabled technologies.The collection will encompass research across the continuum from initial awareness and acceptance of AI through to trust, literacy, verification, adoption, implementation and real-world use. It will also examine the opportunities, risks and safeguards associated with increasingly widespread use of AI for health information, communication, behaviour change and decision-making.Rather than focusing primarily on the technical development of AI systems, the Research Topic will emphasize the human, behavioral, communication and implementation dimensions of AI in health.We welcome contributions addressing topics including, but not limited to:• Trust, acceptance and perceived credibility of AI-enabled health technologies.• Adoption and intention to use AI for health information, healthcare or health-related decision-making.• AI literacy, health literacy and digital health literacy.• How patients and consumers understand and interpret AI-generated health information.• Verification, fact-checking and information-seeking behaviours following AI-generated advice.• Human–AI interaction in health and healthcare settings.• Patient, consumer and clinician attitudes toward generative AI and other AI-enabled technologies.• AI-generated health information, patient education and health communication.• Use of generative AI for healthy lifestyle advice, including physical activity, nutrition, sleep and wellbeing.• AI-supported behaviour change and self-management.• Use of AI for clinical communication, shared decision-making and patient–provider interactions.• Factors influencing appropriate reliance, over-reliance, under-reliance and scepticism toward AI.• Recognition and evaluation of inaccurate, misleading, incomplete or potentially harmful AI-generated information.• Misinformation, hallucinations and information quality in AI-enabled health communication.• Transparency, explainability, uncertainty communication and disclosure in AI systems.• Effects of source attribution, citations, warnings and confidence statements on user perceptions and behaviours.• User experience, usability and accessibility of AI-enabled health technologies.• Patient and public expectations regarding AI in health and healthcare.• Clinician perspectives, readiness, confidence and competencies for using AI.• Psychological and behavioural determinants of AI adoption and use.• Equity, inclusion and the digital divide in access to and use of AI-enabled health technologies.• Differences in AI engagement according to age, education, socioeconomic circumstances, cultural background, digital access and other population characteristics.• Ethical and responsible use of AI in health and healthcare.• Privacy, data governance and user concerns regarding AI-enabled health tools.• Educational approaches designed to improve AI literacy and responsible AI use.• Development and validation of measures assessing trust, AI literacy, acceptance, verification and related constructs.• Implementation and integration of AI-enabled tools into healthcare and public health settings.• Evaluation of interventions designed to improve safe, critical and effective engagement with AI.• Policy, governance and regulatory considerations relating to human use of AI in health.The aim of this Research Topic is to advance understanding of how people engage with artificial intelligence across health and healthcare contexts, and the factors that support safe, effective, equitable and responsible use.By bringing together research from digital health, behavioural science, psychology, public health, health communication, health literacy, human–computer interaction, implementation science and clinical research, the collection will provide a multidisciplinary perspective on the rapidly evolving relationship between people and AI-enabled health technologies.Particular attention will be given to the factors that influence whether individuals understand, trust, critically evaluate, adopt and act upon AI-generated health information and recommendations. This includes the roles of AI literacy and health literacy, verification behaviours, perceived credibility, transparency, usability and contextual factors.Ultimately, the Research Topic will help identify the competencies, design principles, implementation strategies and safeguards needed to support responsible human engagement with AI in health and healthcare. Topic editors: Ben Singh, Parisis Gallos Source: https://www.frontiersin.org/research-topics/85295/human-engagement-with-artificial-intelligence-in-health-trust-literacy-adoption-and-responsible-use