Mapping needles, reducing harm: Findings from a geospatial, community-based needle collection and naloxone training initiative in Saskatchewan, Canada.

eHealth refers to the cost-effective and secure use of information and communications technologies (ICTs) to support health services, surveillance, education, knowledge exchange, and research []. As ICTs have rapidly evolved, digital technologies have become deeply embedded in healthcare delivery. More recently, the proliferation of artificial intelligence (AI) has further transformed how health information is created, accessed, and used. In this context, the ability of patients to effectively engage with digital health resources is important for care participation and health management. This ability was conceptualized by Norman and Skinner in 2006 as eHealth literacy (eHL), defined as “the ability to seek, find, understand, and appraise health information from electronic sources and apply the knowledge gained to addressing or solving a health problem [].“The Lily model conceptualizes eHL as a set of six interrelated literacies: traditional literacy, information literacy, media literacy, health literacy, computer literacy, and scientific literacy []. These domains explain the broad range of skills required for meaningful engagement with eHealth and provide the theoretical foundation for subsequent eHL assessment. Evidence has shown that higher eHL is associated with better health management, improved treatment adherence, and lower healthcare costs, whereas limited eHL may contribute to delayed care and poorer outcomes [–]. However, eHL is not static but evolves alongside technological advancements and shifts in social, personal, and environmental contexts []. The transition from Web 1.0 (read-only) to Web 2.0 (interactive and social) and now Web 3.0 (semantic and machine-driven integration) has changed the demands placed on patients. While Web 1.0 emphasized basic information retrieval, and Web 2.0 introduced interactivity and collaboration, Web 3.0 demands higher-order skills, such as personal data management, cybersecurity, and critical appraisal of AI-generated hallucinations [, ]. These changes are especially relevant in hospital settings, where digital tools such as patient portals, AI-assisted services, indoor navigation systems, and generative AI applications are increasingly integrated into care [–]. Although these technologies may improve efficiency and access, they also create new challenges for inpatients, who are often in physically or emotionally vulnerable conditions but are expected to make health-related decisions and engage actively in care procedures. Previous research has shown that patients often turn to the internet as their first source of health information before consulting physicians, regardless of the severity of their condition []. However, many do not make full use of authoritative digital health resources and may lack the skills required to critically appraise information quality or safeguard personal data. Recent evidence suggests that at least 30% of text on active web pages is AI-generated, increasing the risks of exposure to unverified information []. Shekar et al. [] found that people without medical background often perceived low-accuracy AI-generated responses as valid, trustworthy, and satisfactory, and were highly inclined to follow potentially harmful medical advice or seek unnecessary medical attention based on those responses. The mismatch between the large volume of inaccurate or inappropriate medical advice available online and the high level of trust placed in such information may result in misinformed decisions, misdiagnosis, and harmful consequences for inpatients, highlighting the urgent need to better understand eHL in this population. Despite growing interest in eHL, existing studies have focused mainly on people with chronic diseases or those in outpatient settings, with limited attention to hospitalized patients in the Web 3.0 era. For example, lower self-efficacy, negative attitudes toward aging, and technophobia have been associated with lower eHL in patients with chronic obstructive pulmonary disease [], while better eHL has been linked to greater acceptance of disease management applications among patients with type 2 diabetes []. However, these studies did not capture contemporary eHL demands in hospitalized settings. This gap is primarily attributed to the weakness of previous instruments which remain anchored in the Web 1.0 paradigm and fail to capture the full spectrum of eHL skills under the Web 3.0 era [–]. To address this gap, this study aimed to evaluate eHL and identify its sociodemographic determinants among adult inpatients using the Adult Inpatient eHealth Literacy Scale (AIPeHLS), which was previously developed and validated for this population []. Without addressing this gap, patients may have fewer opportunities to enhance their self-management capabilities and quality of life in increasingly digitalized care environments, which may in turn hinder efforts to optimize the overall efficiency and effectiveness of healthcare delivery systems