OpenAlex · Aktualisierung stündlich · Letzte Aktualisierung: 23.03.2026, 10:23

Dies ist eine Übersichtsseite mit Metadaten zu dieser wissenschaftlichen Arbeit. Der vollständige Artikel ist beim Verlag verfügbar.

Health Literacy and Acceptance of AI/XR-Enabled Telemedicine Among Romanian Medical Students: A Cross-Sectional Survey

2026·0 Zitationen·HealthcareOpen Access
Volltext beim Verlag öffnen

0

Zitationen

6

Autoren

2026

Jahr

Abstract

<b>Background and Objectives</b>: AI- and extended reality (XR)-enabled telemedicine is increasingly relevant to clinical training, yet evidence from Central and Eastern Europe is limited. We assessed Romanian medical students' acceptance of AI/XR-enabled telemedicine and examined whether health literacy moderates the association between AI/XR knowledge and acceptance. <b>Methods</b>: We conducted an anonymous cross-sectional online survey of 212 medical students (years 1-6) at a single Romanian university (March 2024-June 2025). Acceptance was measured using a study-specific Acceptance Index (mean of three 4-point items: trust in AI-assisted recommendations, perceived improvement in telemedicine quality with AI/XR, and willingness to participate in AI/XR-enabled teleconsultations; internal consistency acceptable, Cronbach's α ≈ 0.8). Health literacy was assessed with the validated Romanian version of the European Health Literacy Survey Questionnaire (HLS-EU-Q16). We performed group comparisons, Spearman correlations, multivariable and hierarchical regression with a Knowledge × Health Literacy interaction, and k-means clustering. <b>Results</b>: Participants had a mean age of 22.5 ± 1.9 years; 66.0% were female. Overall acceptance was high (2.9 ± 0.6). Acceptance was higher in clinical vs. preclinical years (3.1 ± 0.6 vs. 2.8 ± 0.5; <i>p</i> < 0.001; Cohen's d ≈ 0.55) and in prior AI/XR users vs. non-users (3.2 ± 0.5 vs. 2.7 ± 0.6; <i>p</i> < 0.001; d ≈ 0.89). Knowledge correlated strongly with acceptance (ρ = 0.68; <i>p</i> < 0.001). In multivariable models (R<sup>2</sup> = 0.61), knowledge, perceived educational value, prior AI/XR use, and clinical stage independently predicted acceptance, whereas privacy concern and gender did not. Health literacy was sufficient in 64.2% and significantly moderated the knowledge-acceptance link (interaction <i>p</i> = 0.012). <b>Conclusions</b>: Romanian medical students report favorable acceptance of AI/XR-enabled telemedicine. Findings support curriculum integration that combines structured AI/XR teaching with literacy-sensitive scaffolding to ensure knowledge translates into informed, critical acceptance across student subgroups.

Ähnliche Arbeiten

Autoren

Institutionen

Themen

Artificial Intelligence in Healthcare and EducationTelemedicine and Telehealth ImplementationMobile Health and mHealth Applications
Volltext beim Verlag öffnen