Evidence map›Paper›PMID 42016397›Full record

ArticleJournal of education and health promotion2026

Understanding AI adoption in medical education: Insights from students and faculty members in Indonesian medical schools.

Lantip Rujito, Amalia Muhaimin, Mackenzie Alma Pergodi, Aya Sofya Darmawan, Miko Ferine, Wahyudin Wahyudin

Abstract read
In one paragraph

Article in Journal of education and health promotion, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Lantip RujitoDepartment of Genetics dan Molecular Medicine, Universitas Jenderal Soedirman, Purwokerto, Indonesia.
Amalia MuhaiminDepartment of Bioethics, Universitas Jenderal Soedirman, Purwokerto, Indonesia.
Mackenzie Alma PergodiDepartment of Bioethics, Universitas Jenderal Soedirman, Purwokerto, Indonesia.
Aya Sofya DarmawanDepartment of Medical Education, Universitas Jenderal Soedirman, Purwokerto, Indonesia.
Miko FerineDepartment of Medical Education, Universitas Jenderal Soedirman, Purwokerto, Indonesia.
Wahyudin WahyudinDepartment of Pharmacology, Universitas Jenderal Soedirman, Purwokerto, Indonesia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial Intelligence (AI) implementation in medical education has changed the learning process, with new forms of diagnosis, treatment planning, and patient care. Biases in AI adoption among Indonesian medical schools' students and teachers, however, are still to be explained. This article seeks to determine the level of knowledge, attitude, and behavior of the medical students and faculty members towards the adoption of AI in medical education. MATERIALS AND

methodsAnalytical observational design with a cross-sectional design is utilized in this study. Questionnaires were used to collect data from medical students and medical lecturers of several Indonesian medical schools. Consecutive and purposive sampling methods were used to determine the sample. Statistical analysis involved using the Spearman correlation test to examine the correlation between AI adoption, knowledge, attitudes, and behavior.

resultsAmong the students, 62.3% had good knowledge about AI, while 52.6% fell in the neutral attitude range and 64% of them showed a moderate behavior in implementing AI. The faculty members, however, were found to be divided in terms of their extent of knowledge, among which 34.7% fell into the good knowledge range, 71.4% showed a positive attitude, and 46.9% illustrated low interaction in implementing AI. The correlation test did not show any meaningful relationship between behavior and knowledge in either group (students:

conclusionThough both students and teachers have an idea about the possibilities of AI in medical education, they are still far from adopting AI-based tools at their behavioral level.

Indexed as

Artificial intelligencecurriculumdigital healtheducation medicalfacultyhealth knowledge attitudes practiceIndonesiastudents medical

Identifiers

PMID42016397
PMCPMC13094931

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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.