{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T10:13:54Z","timestamp":1778148834721,"version":"3.51.4"},"reference-count":32,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T00:00:00Z","timestamp":1778112000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"abstract":"<jats:p>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 \u00b1 0.49), followed by AI-only (3.64 \u00b1 0.56) and XR-only (3.49 \u00b1 0.64). AI+XR acceptance was significantly higher than AI-only and XR-only acceptance (both p &lt; 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 (\u03c1 = 0.60) and health literacy (\u03c1 = 0.23), and negatively with technostress (\u03c1 = \u22120.47). In multivariable analysis, higher AI literacy (\u03b2 = 0.603, p &lt; 0.001) and health literacy (\u03b2 = 0.241, p &lt; 0.001) independently predicted higher AI+XR acceptance, whereas technostress was inversely associated (\u03b2 = \u22120.212, p &lt; 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.<\/jats:p>","DOI":"10.3390\/jcm15103565","type":"journal-article","created":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T09:03:37Z","timestamp":1778144617000},"page":"3565","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Clinician Acceptance of Artificial Intelligence- and Extended Reality-Enabled Telemedicine: A Cross-Sectional Vignette Survey of Residents and Nurses in Romania"],"prefix":"10.3390","volume":"15","author":[{"given":"Codrina Mihaela","family":"Levai","sequence":"first","affiliation":[{"name":"Doctoral School, \u201cVictor Babes\u201d University of Medicine and Pharmacy, 300041 Timisoara, Romania"},{"name":"Research Center for Medical Communication, \u201cVictor Babes\u201d University of Medicine and Pharmacy, 300041 Timisoara, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Livia","family":"Stanga","sequence":"additional","affiliation":[{"name":"Discipline of Microbiology, Faculty of Medicine, \u201cVictor Babes\u201d University of Medicine and Pharmacy, 300041 Timisoara, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Laura Alexandra","family":"Nussbaum","sequence":"additional","affiliation":[{"name":"Department of Neurosciences, \u201cVictor Babes\u201d University of Medicine and Pharmacy, 300041 Timisoara, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4032-0899","authenticated-orcid":false,"given":"Adelina Marioara","family":"Gherman","sequence":"additional","affiliation":[{"name":"Faculty of Nursing, \u201cVictor Babes\u201d University of Medicine and Pharmacy, 300041 Timisoara, Romania"},{"name":"Multidisciplinary Heart Research Center, \u201cVictor Babes\u201d University of Medicine and Pharmacy, 300041 Timisoara, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-1728-3552","authenticated-orcid":false,"given":"Daian-Ionel","family":"Popa","sequence":"additional","affiliation":[{"name":"Doctoral School, \u201cVictor Babes\u201d University of Medicine and Pharmacy, 300041 Timisoara, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2242-5301","authenticated-orcid":false,"given":"Camelia","family":"Fizedean","sequence":"additional","affiliation":[{"name":"Department of Neurosciences, \u201cVictor Babes\u201d University of Medicine and Pharmacy, 300041 Timisoara, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,5,7]]},"reference":[{"key":"ref_1","unstructured":"World Health Organization (2021). 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