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TRUVACE RECORD VERSION
record: TRV-2026-2780
version: 1
kind: certified
reason: Certified into the record
timestamp: 2026-11-12T17:23:02.547305Z
status: published
lens: p_space
sector: health
headline: Undergraduate medical students and artificial intelligence: A global systematic review and meta-analysis using a knowledge–attitude–practice framework
dek: BACKGROUND: Artificial intelligence (AI), including deep learning and large language models, is increasingly reshaping healthcare and medical education. Since the public release of generative AI tools such as ChatGPT, medical students have become a particularly exposed group, often engaging with these technologies without standardized curricular guidance. Although previous reviews have explored readiness, acceptance, or anxiety, the relationship between students' knowledge, attitudes, and practical engagement wi…
gain_title: (none)
problem_title: A systematic review of 43 studies, with 11 pooled, found undergraduate medical students scored only moderate on AI knowledge (0.55; 95% CI 0.49-0.61) even though attitudes were more positive (0.64).
trace_subject: (none)
gain_reading: (none)
gain_evidence: (none)
problem_reading: A systematic review of 43 studies, with 11 pooled, found undergraduate medical students scored only moderate on AI knowledge (0.55; 95% CI 0.49-0.61) even though attitudes were more positive (0.64).
problem_evidence: pooled estimates showed moderate knowledge (0.55; 95% CI: 0.49-0.61), positive attitudes (0.64; 95% CI: 0.59-0.69)
quick_read: A systematic review and meta-analysis of 43 studies, 37 cross-sectional and 6 psychometric validation studies, examined how undergraduate medical students engage with AI. Pooling 11 studies that used the MAIRS-MS scale, it found moderate knowledge (0.55), positive attitudes (0.64) and practice levels of 0.63.

The authors conclude that medical students are receptive to AI but that their knowledge is only moderate and their practical engagement reflects limited preparation. They say this supports structured undergraduate AI curricula covering theoretical, applied and ethical-legal competencies.

Attitudes were the most studied dimension, followed by knowledge and practice. Heterogeneity across the pooled studies stayed high, so the estimates cover a varied set of student groups and settings.
limitation: Only 11 of the 43 studies could be pooled because of differences in instruments and reporting, and heterogeneity among them remained high.
tag: Evidence-backed problem
key_points: The review searched PubMed, Scopus and Web of Science up to September 30, 2025 and followed PRISMA 2020 reporting. | Forty-three studies met the inclusion criteria: 37 cross-sectional and 6 psychometric validation studies. | Only 11 studies using the MAIRS-MS scale with comparable percentage outcomes were pooled, because instruments and reporting varied widely. | Pooled knowledge was 0.55 (95% CI 0.49-0.61), attitudes 0.64 (0.59-0.69) and practice 0.63 (0.59-0.67). | Egger's test showed no significant small-study effects. | Authors call for curricula combining theoretical, applied and ethical-legal AI competencies.
rundown: The review used a Knowledge-Attitude-Practice framework to link what medical students know about AI, how they feel about it and how they use it. It was motivated by the spread of generative tools such as ChatGPT, which students often use without standardized curricular guidance.

Study quality was assessed with the AXIS tool and the research question was structured with the PCC framework. Because instruments and reporting differed substantially, only 11 of the 43 studies entered the quantitative synthesis, using a random-effects DerSimonian-Laird model with Freeman-Tukey double arcsine transformation.

Pooled results put knowledge lowest at 0.55, with attitudes at 0.64 and practice at 0.63. The authors read this as receptive students whose practical engagement reflects limited preparation, and recommend structured undergraduate AI teaching.
sources:
- peer_reviewed | Medical Teacher | https://doi.org/10.1080/0142159x.2026.2663855 | 2026-05-31
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