Evidence map›Paper›PMID 41146155›Full record

ArticleBMC medical education2025

Academic misconduct and artificial intelligence use by medical students, interns and PhD students in Ukraine: a cross-sectional study.

Lesya Lymar, Iurii Kuchyn, Kateryna Bielka, Livia Puljak

Abstract read
In one paragraph

Article in BMC medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Whose Voice is it Anyway?Perspectives on medical education · 2026
    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

4 authors.

Lesya LymarBogomolets National Medical University, T. Shevchenko boulevard, 13, Kyiv, 01601, Ukraine. lesyalymar@nmu.ua.ORCID http://orcid.org/0000-0002-9407-1066
Iurii KuchynBogomolets National Medical University, T. Shevchenko boulevard, 13, Kyiv, 01601, Ukraine.ORCID http://orcid.org/0000-0002-9667-1911
Kateryna BielkaBogomolets National Medical University, T. Shevchenko boulevard, 13, Kyiv, 01601, Ukraine.ORCID http://orcid.org/0000-0003-1185-6835
Livia PuljakCentre for Evidence-Based Medicine and Health Care, Catholic University of Croatia, Ilica 244, Zagreb, 10000, Croatia. livia.puljak@unicath.hr.ORCID http://orcid.org/0000-0002-8467-6061

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe issues regarding the use of artificial intelligence (AI) and academic integrity are important contemporary topics. There are no clear regulations governing the use of AI in academic institutions in Ukraine. This study aimed to explore the perceptions of medical students, interns, and PhD candidates about academic misconduct and AI use.

methodsThe cross-sectional study was conducted online via survey in October-December 2024. The participants were medical students, interns, and medical PhD students of the Bogomolets National Medical University in Kyiv, Ukraine.

resultsAmong 244 study participants, the majority (84%) reported using AI for academic purposes, with ChatGPT being the most commonly used tool. AI was primarily employed for information searches (70%), while a smaller proportion admitted using it for academic dishonesty, such as writing essays (14%) or submitting pre-written assignments (9%). Nearly half (51%) of participants reported having cheated on tests previously. Opinions on AI's impact on academic integrity were divided, with 36% considering AI use as misconduct, 26% perceiving it as acceptable, and 38% undecided. Most participants viewed AI as beneficial for learning and work, with 37% indicating they would continue using AI professionally. Perceived AI's advantages included time efficiency, enhanced learning, and accessibility, while concerns were raised about errors, lack of critical thinking, over-dependence, and ethical risks.

conclusionThese results highlight the widespread adoption of AI among medical students, interns, and PhD candidates for academic purposes, with both notable advantages and significant ethical and practical concerns. Considering the prevalent use of AI for academic work among medical students, interns and PhD students in Ukraine, national rules are needed to define which uses of AI constitute academic dishonesty and academic misconduct.

Indexed as

Artificial IntelligenceInternship and ResidencyStudents, MedicalAdultCross-Sectional StudiesFemaleHumansMaleSurveys and QuestionnairesUkraineYoung AdultAcademic misconductArtificial intelligencePhD students, medical students, interns

Identifiers

PMID41146155
PMCPMC12557969

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.