Artificial Intelligence Literacy and E-Health Literacy in Rheumatic Diseases

This study aims to evaluate digital health competencies in individuals with rheumatic and degenerative joint diseases. Specifically, it assesses e-health literacy and artificial intelligence literacy, which refer to individuals' ability to access, understand, and utilize online health information and AI-based health technologies. Participants include patients with rheumatoid arthritis, ankylosing spondylitis, psoriatic arthritis, knee osteoarthritis, and healthy volunteers. The study also examines how these competencies are associated with demographic variables, anxiety, depression, and functional status. Findings may contribute to improving digital health strategies for patients with chronic musculoskeletal conditions.

Digital technologies and artificial intelligence (AI) are becoming increasingly integrated into healthcare systems. However, the ability of patients to effectively access and use these technologies varies depending on multiple factors such as education level, health status, and psychological well-being. This cross-sectional study aims to measure two key competencies: e-health literacy (the ability to seek, find, understand, and appraise online health information) and artificial intelligence literacy (understanding and engaging with AI-supported health tools). The study will recruit three groups: individuals with inflammatory rheumatic diseases (rheumatoid arthritis, ankylosing spondylitis, psoriatic arthritis), individuals with degenerative joint disease (knee osteoarthritis), and healthy controls. All participants will complete standardized self-report questionnaires, including the E-Health Literacy Scale (eHEALS), the Artificial Intelligence Literacy Scale (AILS), the Beck Depression Inventory (BDI), the Beck Anxiety Inventory (BAI), and the Health Assessment Questionnaire (HAQ). The primary aim is to compare digital literacy levels across groups and examine correlations with socio-demographic characteristics and mental health indicators. The results are expected to inform clinical strategies and patient education programs aimed at improving engagement with digital health services, particularly in patients with chronic rheumatic conditions.