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.
Study Type
OBSERVATIONAL
Enrollment
201
Yozgat Bozok University Faculty of Medicine, Department of Physical Medicine and Rehabilitation
Yozgat, Yozgat, Turkey (Türkiye)
E-Health Literacy Scale (eHEALS) - Total Score
The primary outcome is the total score on the E-Health Literacy Scale (eHEALS), which assesses individuals' ability to seek, find, understand, and evaluate health information from electronic sources. The eHEALS consists of 8 items, each rated on a 5-point Likert scale. Total scores range from 8 to 40, with higher scores indicating greater e-health literacy.
Time frame: At baseline
Artificial Intelligence Literacy Scale (AILS) Total Score
This outcome measures participants' knowledge, skills, and attitudes related to understanding and using artificial intelligence technologies in healthcare. The Artificial Intelligence Literacy Scale (AILS) includes 12 items scored on a 7-point Likert scale. Total scores range from 12 to 84, with higher scores reflecting greater AI literacy.
Time frame: At baseline
Beck Depression Inventory (BDI) Total Score
The Beck Depression Inventory (BDI) is used to assess the severity of depressive symptoms. It includes 21 items, each scored on a 0 to 3 scale. Total scores range from 0 to 63, with higher scores indicating more severe depression.
Time frame: At baseline
Beck Anxiety Inventory (BAI) Total Score
The Beck Anxiety Inventory (BAI) measures the severity of anxiety symptoms. It includes 21 self-reported items, each scored from 0 to 3. Total scores range from 0 to 63, with higher scores reflecting greater anxiety.
Time frame: At baseline
Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) Total Score
The Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) is used to evaluate pain, stiffness, and physical function in patients with knee osteoarthritis. It consists of 24 items scored on a 5-point Likert scale (0 = none to 4 = extreme). Total scores range from 0 to 96, with higher scores indicating greater symptom severity and functional impairment.
Time frame: At baseline
Disease Activity Score 28 (DAS28) - Total Score
The Disease Activity Score 28 (DAS28) is used to assess disease activity in patients with rheumatoid arthritis. It incorporates counts of 28 tender and swollen joints, a patient global health assessment, and either erythrocyte sedimentation rate (ESR) or C-reactive protein (CRP) as inflammatory markers. Scores range from 0 to 10, with higher scores indicating more active disease.
Time frame: At baseline
Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) - Total Score
The Bath Ankylosing Spondylitis Disease Activity Index (BASDAI) is used to assess disease activity in patients with ankylosing spondylitis. It includes six questions related to fatigue, spinal and peripheral joint pain, localized tenderness, and morning stiffness. Each item is scored on a 0 to 10 scale, and the final BASDAI score is the average of the items. Total scores range from 0 to 10, with higher scores indicating greater disease activity and more severe symptoms.
Time frame: At baseline
Disease Activity Index for Psoriatic Arthritis (DAPSA)
The Disease Activity index for Psoriatic Arthritis (DAPSA) is used to evaluate disease activity in patients with psoriatic arthritis. It is calculated using the sum of the tender joint count (TJC, 68 joints), swollen joint count (SJC, 66 joints), patient global assessment (0-10 scale), patient pain assessment (0-10 scale), and C-reactive protein (CRP, mg/dL). Total scores range from 0 to approximately 150, with higher scores indicating greater disease activity.
Time frame: At baseline
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