ArticleBMC medical education2018
Investigating the existence of social networks in cheating behaviors in medical students.
Article in BMC medical education, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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.
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Who cites it
6 citing papers in PubMed, 21 citations in OpenAlex.
- Cheating 2.0: A reprofiling of the 10 most wanted test cheaters in the digital age.Medical education · 2026Article
- Validation of the academic misconduct questionnaire: exploring predictors of student misconduct.Medical education online · 2025Article
- Identifying HEXACO personality types: what do type characteristics tell us about student misconduct?BMC medical education · 2025Article
- Automated Item Generation: impact of item variants on performance and standard setting.BMC medical education · 2023Article
- A Mixed-Methods Exploration of the Effect of Disabling Backward Navigation on Calculations-Focused Computerized Examinations.American journal of pharmaceutical education · 2022Article
- Machiavellian Medical Students Report More Academic Misconduct: A Cocktail Fuelled by Psychological and Contextual Factors.Psychology research and behavior management · 2022Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMost studies on academic cheating rely on self-reported questionnaires and focus on the individual, overlooking cheating as a group activity. The aim of this study is to estimate the true prevalence of cheating/anomalies among medical students using a statistical index developed for this purpose, and to explore the existence of social networks between anomalies in students' results.
methodsAngoff's A index was applied to a sample of 30 written examinations, with a total of 1487 students and 7403 examinations taken, from the 2014/2015 academic year of the Faculty of Medicine of the University of Porto to detect anomaly pairs. All analyses are within the same academic year and not across years. Through simulations, the sensitivity and specificity of the statistical method was determined, and the true prevalence of anomalies/cheating was estimated. Networks of anomaly pairs were created to search for patterns and to calculate their density.
resultsThe percentage of students who cheated at least once increased with the year of medical school, being lowest in the first year (3.4%) and highest in the fifth (17.3%). The year of medical school was associated with anomalies (p < 0.05). The network's density was also lowest in the first year (1.12E-04) and highest in the fifth (8.20E-04). The true prevalence of anomalies was estimated to be 1.85% (95%CI: 1.07-3.20%).
conclusionsThese findings suggest that some students are involved in social networks of cheating, which grow over time, resulting in an increase of anomalies/cheating in later academic years.
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Registered trials
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.