Widespread use of ChatGPT and other Artificial Intelligence tools among medical students in Uganda: A cross-sectional study

Elizabeth Ajalo; David Mukunya; Ritah Nantale; Frank Kayemba; Kennedy Pangholi; Jonathan Babuya; Suzan Langoya Akuu; Amelia Margaret Namiiro; Yakobo Baddokwaya Nsubuga; Joseph Luwaga Mpagi; Milton W Musaba; Faith Oguttu; Job Kuteesa; Aloysius Gonzaga Mubuuke; Ian Guyton Munabi; Sarah Kiguli

doi:10.1371/journal.pone.0313776

Widespread use of ChatGPT and other Artificial Intelligence tools among medical students in Uganda: A cross-sectional study

PLoS One. 2025 Jan 9;20(1):e0313776. doi: 10.1371/journal.pone.0313776. eCollection 2025.

Authors

Elizabeth Ajalo¹, David Mukunya¹, Ritah Nantale¹, Frank Kayemba¹, Kennedy Pangholi¹, Jonathan Babuya¹, Suzan Langoya Akuu², Amelia Margaret Namiiro³, Yakobo Baddokwaya Nsubuga⁴, Joseph Luwaga Mpagi⁵, Milton W Musaba⁶, Faith Oguttu¹, Job Kuteesa⁷, Aloysius Gonzaga Mubuuke⁸, Ian Guyton Munabi⁹, Sarah Kiguli³

Affiliations

¹ Department of Community and Public Health, Busitema University, Mbale, Uganda.
² Mbarara University of Science and Technology, Mbarara, Uganda.
³ Department of Pediatrics and Child Health, Makerere University, College of Health Sciences, Kampala, Uganda.
⁴ Faculty of Health Sciences, Gulu University, Gulu, Uganda.
⁵ Department of Microbiology and Immunology, Busitema University Faculty of Health Sciences, Mbale, Uganda.
⁶ Department of Obstetrics and Gynaecology, Busitema University Faculty of Health Sciences, Mbale, Uganda.
⁷ Department of Surgery, Mulago Hospital, College of Surgeons of East Central and Southern Africa, Uganda.
⁸ Department of Radiology, School of Medicine, College of Health Sciences, Makerere University, Kampala, Uganda.
⁹ Department of Human Anatomy, School of Biomedical Sciences, Makerere University, College of Health Sciences, Kampala, Uganda.

Abstract

Background: Chat Generative Pre-trained Transformer (ChatGPT) is a 175-billion-parameter natural language processing model that uses deep learning algorithms trained on vast amounts of data to generate human-like texts such as essays. Consequently, it has introduced new challenges and threats to medical education. We assessed the use of ChatGPT and other AI tools among medical students in Uganda.

Methods: We conducted a descriptive cross-sectional study among medical students at four public universities in Uganda from 1st November 2023 to 20th December 2023. Participants were recruited by stratified random sampling. We used a semi-structured questionnaire to collect data on participants' socio-demographics and use of AI tools such as ChatGPT. Our outcome variable was use of AI tools. Data were analyzed descriptively in Stata version 17.0. We conducted a modified Poisson regression to explore the association between use of AI tools and various exposures.

Results: A total of 564 students participated. Almost all (93%) had heard about AI tools and more than two-thirds (75.7%) had ever used AI tools. Regarding the AI tools used, majority (72.2%) had ever used ChatGPT, followed by SnapChat AI (14.9%), Bing AI (11.5%), and Bard AI (6.9%). Most students use AI tools to complete assignments (55.5%), preparing for tutorials (39.9%), preparing for exams (34.8%) and research writing (24.8%). Students also reported the use of AI tools for nonacademic purposes including emotional support, recreation, and spiritual growth. Older students were 31% less likely to use AI tools compared to younger ones (Adjusted Prevalence Ratio (aPR):0.69; 95% CI: [0.62, 0.76]). Students at Makerere University were 66% more likely to use AI tools compared to students in Gulu University (aPR:1.66; 95% CI:[1.64, 1.69]).

Conclusion: The use of ChatGPT and other AI tools was widespread among medical students in Uganda. AI tools were used for both academic and non-academic purposes. Younger students were more likely to use AI tools compared to older students. There is a need to promote AI literacy in institutions to empower older students with essential skills for the digital age. Further, educators should assume students are using AI and adjust their way of teaching and setting exams to suit this new reality. Our research adds further evidence to existing voices calling for regulatory frameworks for AI in medical education.

Copyright: © 2025 Ajalo et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

MeSH terms

Adolescent
Adult
Artificial Intelligence
Cross-Sectional Studies
Deep Learning
Female
Humans
Male
Natural Language Processing*
Students, Medical* / psychology
Surveys and Questionnaires
Uganda
Universities
Young Adult

Grants and funding

This study was conducted with support from Fogarty International Center of the National Institutes of Health, U.S. Department of State’s Office of the U.S. Global AIDS Coordinator and Health Diplomacy (S/GAC), and President’s Emergency Plan for AIDS Relief (PEPFAR) under Award Number 1R25TW011213. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.