Evidence map›Paper›PMID 41731499›Full record

ArticleBMC medical education2026

Understanding the ideal resources to study the UKMLA.

Parth Ankur Tagdiwala, Christina Anna Petmeza, Sanskritti Dubey, Inez Murray, Arisma Arora, Nikki Kerdegari

Abstract read
In one paragraph

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.

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

6 authors.

Parth Ankur TagdiwalaUniversity College London Medical School, Gower St, London, WC1E 6BT, UK. zchatag@ucl.ac.uk.
Christina Anna PetmezaQueen Mary University of London, 327 Mile End Road, London, E1 4NS, UK.
Sanskritti DubeyThe University of Nottingham, Nottingham, NG7 2RD, UK.
Inez MurrayQueen's University Belfast, University Road, Belfast, BT7 1NN, Northern Ireland, UK.
Arisma AroraKings College London, King's College London Strand, London, WC2R 2LS, UK.
Nikki KerdegariKings College London, King's College London Strand, London, WC2R 2LS, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe United Kingdom Medical Licensing Assessment (UKMLA) is a new national examination being introduced for all final-year medical students graduating from the academic year commencing in 2024. The examination will be a national initiative to standardize medical school exams. In this paper, we aim to understand which resources can be developed in the future to help clinical-year medical students studying for the UKMLA.

methodsWe organised a novel 25-lecture series delivered by post-CCT doctors using an online platform. A form was created and distributed amongst the lecture audience to understand which resources medical students find useful for studying clinical medicine. The form was created using Google Forms©.

resultsOur form was completed by 71 participants. The three most used resources were free online resources, paid question banks, and clinical placements. More than half of the participants reported that the single most useful resource was paid online question banks. The form was completed by participants from a wide range of UK medical schools, with most students being in their clinical years of study.

conclusionDigital resources are widely used by medical students, and to further support clinical students in their learning, the Society should develop such resources.

Indexed as

Educational MeasurementEducation, Medical, UndergraduateLicensure, MedicalStudents, MedicalDigital MediaHumansInternetUnited KingdomE-learningLearning resourcesQuestion banks

Identifiers

PMID41731499
PMCPMC13036964

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.