Factors influencing eHealth adoption among healthcare users in Türkiye: A stepwise logistic regression analysis
Health Policy, cilt.165, 2026 (SCI-Expanded, SSCI, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 165
- Basım Tarihi: 2026
- Doi Numarası: 10.1016/j.healthpol.2025.105539
- Dergi Adı: Health Policy
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Periodicals Index Online, CINAHL, EMBASE, MEDLINE, Public Affairs Index
- Anahtar Kelimeler: Digital technology, Healthcare, Information science, Population characteristic
- Ankara Yıldırım Beyazıt Üniversitesi Adresli: Evet
Özet
Background: eHealth services can improve healthcare access in Türkiye, yet disparities remain across socio-demographic groups. Despite major investments, quantitative evidence on user experiences with national eHealth platforms is limited. Objective: To identify factors influencing eHealth use, focusing on three nationally available applications: Central Physician Appointment System (CPAS), Personal Medical Record System (PMR) and a self-diagnostic/referral system (e-diagnosis). Methods: A cross-sectional survey of 450 participants collected data on socio-demographics, health status, internet access, and eHealth use. Stepwise logistic regression and mediation analysis were applied. Results: Higher educational attainment was consistently associated with greater eHealth use (university vs. primary, odds ratio [OR]=1.76, 95% confidence interval [CI]:0.54–2.98, p < 0.001); gender, household size, income, and residence were not significant. Age-related differences were mediated by internet access and user engagement, including perceived ease of use (OR=3.12, 95% CI:2.25–3.98, p < 0.001), prior evaluations of doctors/hospitals (OR=2.51, 95% CI: 0.38–4.64, p < 0.01), and unsuccessful CPAS attempts (OR=0.36, 95% CI:0.14–0.91, p < 0.01). Chronic disease status had no effect after adjusting for internet access and eHealth engagement. Higher education was linked to greater use of CPAS and PMR, and these platforms partly explained the overall association between education and eHealth use (indirect effects p ≤ 0.01). Conclusion: Educational attainment emerged as the strongest predictor of eHealth adoption, partly mediated through CPAS and PMR use. Engagement and usability factors outweighed age and structural characteristics. These highlight the importance of user-centered design, digital literacy support, and targeted interventions to reduce disparities and may inform strategies in countries seeking to optimize eHealth initiatives.