ReviewMedical education2026
Medical students' and faculty members' perceptions and experiences of AI integration in health care practice and in medical curricula: A meta-ethnographic review.
Review in Medical education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the increasing adoption of artificial intelligence (AI), health care systems and medical education are undergoing significant changes. This review examines how medical students and faculty members perceive the opportunities and challenges of AI integration in both health care practice and medical curricula. A meta-ethnographic approach, following the eMERGe guidelines, was used to synthesise qualitative research that focuses on perceptions and experiences among students and faculty members. Systematic searches were conducted across ERIC, Embase, PsycINFO, Web of Science and Medline databases, resulting in 1087 articles. Following an assessment of methodological robustness, 26 articles that met the inclusion criteria were included. The synthesis incorporated insights from 4380 students and 75 faculty members from at least 48 countries. There were differing experiences and perceptions of AI in health care and its integration in medical curricula. Four third-order constructs were developed. "Implications on clinical practice" demonstrates how these participants view AI as a decision support tool and its impact on humanistic relationships and efficiency. "AI integrity" considers their perspectives on trust, accountability, inequity and the ethical use of AI technologies. "Educational implications and preparedness" examines preparation for the future workforce and approaches and barriers to integration in medical curricula. "Future workforce" considers participants' perspectives related to the evolving roles of health care professionals in an AI-driven landscape. This review discusses the complex interactions between AI integration in health care practice and in medical curricula, revealing challenges and opportunities as perceived by students and faculty members. Although AI has the potential to revolutionise health care practices, significant educational gaps still hinder its effective implementation. This review advocates for curricula to better tailor to the specific needs of students and faculty members. It also emphasises the importance of incorporating ethical considerations and cross-disciplinary collaboration to ensure readiness for an AI-driven future in health care.
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What OpenQuestion holds
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.