Evidence map›Paper›PMID 40390661›Full record

ArticleMedical education2026

Cheating 2.0: A reprofiling of the 10 most wanted test cheaters in the digital age.

Alison M Sturrock, Gil Myers, Eliot L Rees

Abstract read
In one paragraph

Article in Medical education, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Alison M SturrockUniversity College London School of Life and Medical Sciences, London, UK.ORCID 0000-0003-3531-159X
Gil MyersUniversity College London School of Life and Medical Sciences, London, UK.ORCID 0000-0001-5026-6227
Eliot L ReesSt George's University of London Institute for Medical & Biomedical Education, Cranmer Terrace, London, UK.ORCID 0000-0002-6458-5808

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the last issue of Medical Education Unleashed, Royal et al (2016) introduced the "Ten Most Wanted" test cheaters. Almost a decade later, significant changes in assessment format and delivery have altered the landscape of academic dishonesty. This paper revisits the original 10 cheaters, updates their statuses and identifies new contenders. Cheating remains a pervasive issue in medical education, exacerbated by the shift to online assessments during the COVID-19 pandemic. In medical education, cheating threatens assessment validity, patient safety and institutional reputation, and may correlate with future unprofessional behaviour. The motivations behind cheating are multifaceted. We use the 'fraud triangle' of motivation, opportunity and rationalisation as a framework to conceptualise some of these. This paper profiles the evolution of cheating methods, highlighting new digital-age strategies. An approach which combines authentic assessments, technological integration and promotion of academic integrity is essential to combat this enduring issue.

Indexed as

DeceptionEducational MeasurementEducation, MedicalCOVID-19HumansMotivationPandemicsSARS-CoV-2

Identifiers

PMID40390661
PMCPMC12717500

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.