Evidence map›Paper›PMID 42428959›Full record

ArticleJournal of the colleges of medicine of South Africa2026

Reflection: AI as a catalyst for change in postgraduate medical education.

Sumaiya Adam, Vanessa C Burch

Abstract read
In one paragraph

Article in Journal of the colleges of medicine of South Africa, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

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

2 authors.

Sumaiya AdamDepartment of Obstetrics and Gynaecology, School of Medicine, Faculty of Health Sciences, University of Pretoria, Pretoria, South Africa.ORCID https://orcid.org/0000-0001-8769-3273
Vanessa C BurchColleges of Medicine of South Africa, Cape Town, South Africa.ORCID https://orcid.org/0000-0001-7304-4424

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence (AI) presents a timely opportunity to modernise postgraduate medical education, which has remained largely unchanged despite rapid technological advancements. AI can streamline administrative tasks, personalise learning and support critical thinking, allowing educators to refocus on mentorship and bedside teaching. However, if used uncritically or introduced too early as a substitute for clinical reasoning, AI may contribute to the risk of 'never-skilling', where students fail to develop the foundational clinical skills and independent judgement needed for safe practice. Integrating AI and other digital tools into clinical environments fosters authentic, technology-enabled learning while promoting digital professionalism. A collaborative, environmentally conscious approach across disciplines and institutions is essential to ensure equitable, sustainable adoption. The thoughtful use of AI can transform postgraduate medical education into a more efficient, student-centred system, aligned with the realities of modern healthcare.

Indexed as

artificial intelligencebedside teachingcritical thinkingmedical educationnever-skillingstudent-centred

Identifiers

PMID42428959
PMCPMC13347682

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.