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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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Patient group | Inclusion criteria for the Rheumatoid arthritis group were: meeting the 2010 American College of Rheumatology (ACR) classification criteria for Rheumatoid arthritis , aged 18-65 years, preserved cognitive function, literacy, and willingness to participate. The ankylosing spondylitis group included individuals who met the Modified New York criteria for ankylosing spondylitis and fulfilled the same cognitive, literacy, and age requirements. Similarly, the psoriatic arthritis group consisted of patients meeting the the Classification of Psoriatic Arthritis (CASPAR) criteria classification criteria, aged 18-65, with adequate cognition and literacy, and who consented to participate. | ||
| The knee osteoarthritis control group | The knee osteoarthritis control group included individuals who presented to the same clinic with chronic knee pain (≥6 months), were diagnosed with knee OA based on clinical and radiological findings, and matched the IRD group by age and gender using frequency matching. They also had adequate cognitive and literacy levels and provided consent. | ||
| The healthy control group | The healthy control group was composed of community-dwelling individuals without any diagnosed chronic disease or complaints, matched to the patient group in terms of age and gender, with preserved cognitive function, literacy, and voluntary participation. |
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| Measure | Description | Time Frame |
|---|---|---|
| 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. | 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. | At baseline |
| Measure | Description | Time Frame |
|---|---|---|
| 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. | At baseline |
| Beck Anxiety Inventory (BAI) Total Score |
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Inclusion Criteria:
Age between 18 and 65 years
Adequate cognitive function and literacy
Ability to provide written informed consent
For RA group: Diagnosis of rheumatoid arthritis based on ACR 2010 criteria
For AS group: Diagnosis of ankylosing spondylitis based on Modified New York criteria
For PSA group: Diagnosis of psoriatic arthritis based on CASPAR criteria
For OA group: Clinical and radiological diagnosis of knee osteoarthritis with symptoms ≥6 months
For healthy controls: No known chronic diseases or complaints
Exclusion Criteria:
Cognitive impairment or illiteracy
Unwillingness to participate
Presence of multiple rheumatic diseases
Major psychiatric disorder or neurodegenerative disease
Use of assistive digital devices that influence e-health literacy independently
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The study population consists of adult patients diagnosed with inflammatory rheumatic diseases (RA, AS, PSA), knee osteoarthritis, and age- and gender-matched healthy individuals recruited from a university hospital and the local community in Yozgat, Turkey.
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Yozgat Bozok University Faculty of Medicine, Department of Physical Medicine and Rehabilitation | Yozgat | Yozgat | 66100 | Turkey (Türkiye) |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| Background | Çelebi, C., et al., Artificial intelligence literacy: An adaptation study. Instructional Technology and Lifelong Learning, 2023. 4(2): p. 291-306. | ||
| Background | Wang, B., P.-L.P. Rau, and T. Yuan, Measuring user competence in using artificial intelligence: validity and reliability of artificial intelligence literacy scale. Behaviour & information technology, 2023. 42(9): p. 1324-1337. | ||
| Background | TAMER GENCER, Z., Analysis of validity and reliability of Norman and Skinner's e-Health scale literacy for cultural adaptation. Istanbul Universitesi Iletisim Fakultesi Dergisi, | ||
| 16867972 | Background | Norman CD, Skinner HA. eHealth Literacy: Essential Skills for Consumer Health in a Networked World. J Med Internet Res. 2006 Jun 16;8(2):e9. doi: 10.2196/jmir.8.2.e9. |
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Individual participant data (IPD) that underlie the results reported in this article (including text, tables, and figures) will be shared after deidentification. Data will be available upon reasonable request from the corresponding author
IPD and supporting documents will be available beginning 6 months after publication of the primary results and will remain available for up to 5 years.
"Qualified researchers with a methodologically sound proposal will be able to access de-identified individual participant data and supporting documents upon reasonable request to the corresponding author. Proposals will be evaluated for scientific merit and data will be shared through secure data transfer methods.
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| ID | Term |
|---|---|
| D001172 | Arthritis, Rheumatoid |
| D013167 | Spondylitis, Ankylosing |
| D015535 | Arthritis, Psoriatic |
| D020370 | Osteoarthritis, Knee |
| ID | Term |
|---|---|
| D001168 | Arthritis |
| D007592 | Joint Diseases |
| D009140 | Musculoskeletal Diseases |
| D012216 | Rheumatic Diseases |
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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. |
| 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. | 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. | 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. | 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. | At baseline |
| Background | 49. Ulusoy, M., N.H. Sahin, and H. Erkmen, Turkish version of the Beck Anxiety Inventory: psychometric properties. Journal of cognitive psychotherapy, 1998. 12(2): p. 163. |
| Background | Hisli, N., A reliability and validity study of Beck Depression Inventory in a university student sample). J. Psychol., 1989. 7: p. 3-13. |
| 15639634 | Background | Tuzun EH, Eker L, Aytar A, Daskapan A, Bayramoglu M. Acceptability, reliability, validity and responsiveness of the Turkish version of WOMAC osteoarthritis index. Osteoarthritis Cartilage. 2005 Jan;13(1):28-33. doi: 10.1016/j.joca.2004.10.010. |
| 20525844 | Background | Schoels M, Aletaha D, Funovits J, Kavanaugh A, Baker D, Smolen JS. Application of the DAREA/DAPSA score for assessment of disease activity in psoriatic arthritis. Ann Rheum Dis. 2010 Aug;69(8):1441-7. doi: 10.1136/ard.2009.122259. Epub 2010 Jun 4. |
| 14730386 | Background | Akkoc Y, Karatepe AG, Akar S, Kirazli Y, Akkoc N. A Turkish version of the Bath Ankylosing Spondylitis Disease Activity Index: reliability and validity. Rheumatol Int. 2005 May;25(4):280-4. doi: 10.1007/s00296-003-0432-y. Epub 2004 Jan 17. |
| 18490431 | Background | Wells G, Becker JC, Teng J, Dougados M, Schiff M, Smolen J, Aletaha D, van Riel PL. Validation of the 28-joint Disease Activity Score (DAS28) and European League Against Rheumatism response criteria based on C-reactive protein against disease progression in patients with rheumatoid arthritis, and comparison with the DAS28 based on erythrocyte sedimentation rate. Ann Rheum Dis. 2009 Jun;68(6):954-60. doi: 10.1136/ard.2007.084459. Epub 2008 May 19. |
| 41866024 | Derived | Karakilic GD, Balbaloglu O, Gocer S. Digital and artificial intelligence literacy in inflammatory rheumatic and degenerative joint diseases. Adv Med Sci. 2026 Mar;71(1):114-121. doi: 10.1016/j.advms.2026.03.004. Epub 2026 Mar 20. |
| D003240 |
| Connective Tissue Diseases |
| D017437 | Skin and Connective Tissue Diseases |
| D001327 | Autoimmune Diseases |
| D007154 | Immune System Diseases |
| D000089183 | Axial Spondyloarthritis |
| D025242 | Spondylarthropathies |
| D025241 | Spondylarthritis |
| D013166 | Spondylitis |
| D013122 | Spinal Diseases |
| D001847 | Bone Diseases |
| D000844 | Ankylosis |
| D011565 | Psoriasis |
| D017444 | Skin Diseases, Papulosquamous |
| D012871 | Skin Diseases |
| D010003 | Osteoarthritis |