Clinician Acceptance of Artificial Intelligence- and Extended Reality-Enabled Telemedicine: A Cross-Sectional Vignette Survey of Residents and Nurses in Romania.

Background and

Objectives

Artificial intelligence (AI) and extended reality (XR) are increasingly being integrated into telemedicine, yet clinician adoption depends not only on perceived utility but also on digital preparedness and technology-related burden. This study compared clinician acceptance of AI-only, XR-only, and combined AI+XR telemedicine scenarios and examined whether AI literacy, health literacy, technostress, age, and sex explained variability in acceptance. Materials and

Methods

We conducted a cross-sectional, anonymous online vignette survey among 117 resident physicians and nurses from a tertiary-care hospital and affiliated outpatient clinics in Western Romania. Participants evaluated three randomized telemedicine scenarios (AI-only, XR-only, and AI+XR) using a 3-item Acceptance Index scored from 1 to 4. Additional measures included a study-developed AI literacy quiz, the Romanian-validated HLS-EU-Q16, an adapted brief technostress scale, prior AI/XR exposure, perceived accessibility, perceived value, privacy concern, and demographic variables.

Results

Acceptance was highest for the combined AI+XR scenario (3.74 ± 0.49), followed by AI-only (3.64 ± 0.56) and XR-only (3.49 ± 0.64). AI+XR acceptance was significantly higher than AI-only and XR-only acceptance (both p < 0.001), although the absolute between-scenario differences were modest. Residents reported consistently higher acceptance than nurses across all scenarios, whereas sex differences were small and non-significant; younger age showed only weak inverse associations with acceptance. AI+XR acceptance correlated positively with AI literacy (ρ = 0.60) and health literacy (ρ = 0.23), and negatively with technostress (ρ = -0.47). In multivariable analysis, higher AI literacy (β = 0.603, p < 0.001) and health literacy (β = 0.241, p < 0.001) independently predicted higher AI+XR acceptance, whereas technostress was inversely associated (β = -0.212, p < 0.001).

Conclusions

In this sample, clinicians rated the integrated AI+XR vignette most favorably, but the observed differences between scenarios should be interpreted cautiously and as hypothesis-generating rather than definitive evidence of superiority. Acceptance appeared to depend more on digital readiness and technostress than on age or sex, supporting implementation strategies focused on literacy-building, workflow fit, and burden reduction.