ArticleBMC medical education2026
Medical students' knowledge and attitude towards using artificial intelligence in medical education and practice: a pre-post study.
Article in BMC medical education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThis study aims to evaluate the knowledge and attitudes of Mansoura medical students towards artificial intelligence (AI) use in medical education and practice before and after an educational intervention as to the best of authors' knowledge, all studies conducted in Egypt in this concern are observational.
methodsThis is a Pre-post study conducted in the Faculty of Medicine, Mansoura University, Egypt, during the academic year 2024-2025. Study participants were medical students enrolled in the integrated modular-based education. Two hundred and twenty students completed the questionnaires before the intervention; however, only 189 of them completed the questionnaires after the intervention.
resultsOnly 15.9% of students had previous education about AI during medical study. The most frequent source of previous education was social media platforms as well as AI courses (10.6%). Unfortunately, the least frequent sources were undergraduate curriculum (1.1%) and literature reviews as well as published research articles (0.5%). More than half of students had moderate knowledge and attitude towards AI use in medical education (53.4%) before the intervention, while after intervention, more than half of students had good knowledge and attitude (50.8%). Poor knowledge and attitude decreased from 17.3% to 8.5% after intervention. Regarding medical practice, good knowledge and attitude increased from 17.5% to 36.5% after the intervention. Poor knowledge and attitude decreased from 13.8% to only 5.3% after the intervention with statistically significant difference between the results before and after the intervention (p < 0.001).
conclusionThe intervention was associated with improved students' knowledge and attitude towards AI use in both medical education and practice. The intervention was also associated with an increase in the familiarity of medical students with the different AI tools used in both medical education and practice. The intervention was also associated with an increase in the passion of students to learn more. However, it had less impact on increasing their confidence in their ability to use AI or willing to be operated upon by an AI machine. Therefore, students need a more comprehensive program to increase their confidence.
Indexed as
Identifiers
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.