ArticleHealthcare (Basel, Switzerland)2025
Assessing Medical Students' Perceptions of AI-Integrated Telemedicine: A Cross-Sectional Study in Romania.
Article in Healthcare (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Medical Students' Attitudes, Perceptions, and Self-Reported Familiarity With AI in Health Care: Systematic Review and Meta-Analysis.JMIR medical education · 2026Pooled it
- From Assistance to Autonomy: Acceptability of Progressive Artificial Intelligence Integration in Facial Reconstructive Surgery-Protocol for Within-Subjects Vignette Experiment Among Romanian Adults.Healthcare (Basel, Switzerland) · 2026Article
- The Unfinished Ecosystem: Why Remote Patient Monitoring Has Matured Unevenly, and What Closing the Gap Will Require.Healthcare (Basel, Switzerland) · 2026Article
- Attitude, Awareness and Knowledge of Telemedicine Among Romanian Medical Students: A Cross-Sectional Study.Health science reports · 2026Article
- Telemedicine and digital literacy across medical training: a multicentric analysis of behavioral and educational determinants of readiness.BMC medical education · 2026Article
- Ethical Responsibility in Medical AI: A Semi-Systematic Thematic Review and Multilevel Governance Model.Healthcare (Basel, Switzerland) · 2026Review
- Exploring medical students' attitudes and perceptions toward artificial intelligence in medicine in Shandong Province, China.BMC medical education · 2025Article
- Knowledge Attitudes and Ethical Concerns About Artificial Intelligence Among Medical Students at Taibah University: A Cross-Sectional Study.Advances in medical education and practice · 2025Article
- Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectivesThe rapid advancement of Artificial Intelligence (AI) has driven the expansion of telemedicine solutions worldwide, enabling remote diagnosis, patient monitoring, and treatment support. This study aimed to explore medical students' perceptions of AI in telemedicine, focusing on how these future physicians view AI's potential, benefits, and challenges.
methodsA cross-sectional survey was conducted among 161 Romanian medical students spanning Years 1 through 6. Participants completed a 15-item questionnaire covering demographic factors, prior exposure to AI, attitudes toward telemedicine, perceived benefits, and concerns related to ethical and data privacy issues. A questionnaire on digital health acceptance was conceived and integrated into the survey instrument.
resultsOut of 161 respondents, 70 (43.5%) reported prior telemedicine use, and 66 (41.0%) indicated high familiarity (Likert scores ≥ 4) with AI-based tools. Fifth- and sixth-year students showed significantly greater acceptance of AI-driven telemedicine compared to first- and second-year students (
conclusionsOverall, Romanian medical students view AI-enhanced telemedicine favorably, particularly those in advanced academic years. Familiarity with AI technologies is a key driver of acceptance, though privacy and ethical considerations remain barriers. These findings underline the need for targeted curricular interventions to bolster AI literacy and address concerns regarding data security and clinical responsibility. By proactively integrating AI-related competencies, medical faculties can better prepare students for a healthcare landscape increasingly shaped by telemedicine.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.