Evidence map›Paper›PMID 39776442›Full record

ArticleJournal of CME2025

Artificial Intelligence and ChatGPT in Medical Education: A Cross-Sectional Questionnaire on students' Competence.

L Maaß, C Grab-Kroll, J Koerner, W Öchsner, M Schön, Dac Messerer, T M Böckers, Anja Böckers

Abstract read
In one paragraph

Article in Journal of CME, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

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.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

8 authors.

L MaaßInstitute for Anatomy and Cell Biology, Faculty of Medicine, Ulm University, Ulm, Germany.
C Grab-KrollOffice of the Dean of Studies, Faculty of Medicine, Ulm University, Ulm, Germany.ORCID https://orcid.org/0000-0002-6688-2144
J KoernerOffice of the Dean of Studies, Faculty of Medicine, Ulm University, Ulm, Germany.ORCID https://orcid.org/0009-0004-1281-3356
W ÖchsnerOffice of the Dean of Studies, Faculty of Medicine, Ulm University, Ulm, Germany.ORCID https://orcid.org/0000-0001-7545-4777
M SchönInstitute for Anatomy and Cell Biology, Faculty of Medicine, Ulm University, Ulm, Germany.ORCID https://orcid.org/0000-0002-8905-1810
Dac MessererInstitute of Transfusion Medicine, University of Ulm, Ulm, Germany.
T M BöckersInstitute for Anatomy and Cell Biology, Faculty of Medicine, Ulm University, Ulm, Germany.ORCID https://orcid.org/0000-0002-1486-8535
Anja BöckersInstitute for Anatomy and Cell Biology, Faculty of Medicine, Ulm University, Ulm, Germany.ORCID https://orcid.org/0000-0002-2579-8632

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence is rapidly transforming the field of health science and medical education, but less is known about the students´ competencies related to knowledge, skills and attitudes towards the application of AI tools like ChatGPT. Therefore, a unicentric questionnaire-based cross-sectional study was applied to students in the medical field (

Indexed as

AI literacyArtificial intelligenceattitudesChatGPTdigital competencehealth educationmedical education

Identifiers

PMID39776442
PMCPMC11703531

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.