Evidence map›Paper›PMID 41053766›Full record

ArticleBMC medical education2025

"I can no longer give take-home exams": Health professionals educators' experiences and perceptions regarding the use of artificial intelligence in health professions education in Uganda.

David Mukunya, Ritah Nantale, Kennedy Paungholi, Joshua Epuitai, Frank Kayemba, Brian Jemba, Elizabeth Ajalo, Adam Afodun, Milton W Musaba, Ian G Munabi and 2 more

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 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

12 authors.

David MukunyaFaculty of Health Sciences, Busitema University, P.O. Box 1460, Mbale, Uganda.
Ritah NantaleFaculty of Health Sciences, Busitema University, P.O. Box 1460, Mbale, Uganda.
Kennedy PaungholiFaculty of Health Sciences, Busitema University, P.O. Box 1460, Mbale, Uganda.
Joshua EpuitaiFaculty of Health Sciences, Busitema University, P.O. Box 1460, Mbale, Uganda. joshuaepuitai@gmail.com.
Frank KayembaFaculty of Health Sciences, Busitema University, P.O. Box 1460, Mbale, Uganda.
Brian JembaFaculty of Health Sciences, Busitema University, P.O. Box 1460, Mbale, Uganda.
Elizabeth AjaloFaculty of Health Sciences, Busitema University, P.O. Box 1460, Mbale, Uganda.
Adam AfodunFaculty of Health Sciences, Busitema University, P.O. Box 1460, Mbale, Uganda.
Milton W MusabaFaculty of Health Sciences, Busitema University, P.O. Box 1460, Mbale, Uganda.
Ian G MunabiCollege of Health Sciences, Makerere University, P.O. Box 7072, Kampala, Uganda.
Sarah KiguliCollege of Health Sciences, Makerere University, P.O. Box 7072, Kampala, Uganda.
A G MubuukeCollege of Health Sciences, Makerere University, P.O. Box 7072, Kampala, Uganda.

Funding

Health Professions Education and training for strengthening the health system and services in UgandaR25TW011213 · FIC · MAKERERE UNIVERSITY COLLEGE OF HEALTH SCIENCES · PI KIGULI, SARAH · 2018 to 2022
$3.4M
FIC NIH HHS R25 TW011213The 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, 1R25TW011213 1R25TW011213
6 · The paper itself

Abstract

introductionArtificial intelligence (AI) tools offer immense opportunities and challenges for medical education. However, there is limited information about the use of AI among health professional educators, particularly in low- and middle-income countries. We aimed to explore the experiences and perceptions regarding AI use in health professional education. METHODS AND MATERIALS: We collected qualitative data using in-depth interviews with 19 health professional educators. The interviews were audio-recorded and transcribed verbatim. We used Atlas Ti version 9.1 to organise the data. We used Braun and Clarke's six-step thematic analysis for data analysis. The study was approved by the Busitema University Research and Ethics Committee (BUFHS-2023-79).

resultsThree major themes were identified from the data: uptake and use of AI, perceived benefits of AI in health professional education, and concerns regarding AI use. We noted initial reluctance to support AI use, while its use varied from no or infrequent use to frequent use. Health professional educators used AI for various reasons, such as for teaching, student assessment, research, and personal work. AI was perceived to be beneficial in improving the clarity of writing, providing access to individual-tailored information, teaching, learning, and assessment, and research purposes. The barriers to AI use included a lack of institutional policies to guide AI use, limited capacity to afford paid AI versions, and reluctance to use AI. AI was seen to have inherent limitations, which included inaccurate information and a lack of contextual information for resource-limited settings. The fears of AI use included the risk of over-reliance on AI, academic misconduct, examination malpractice, ethical conflicts, and integrity.

conclusionAI use in health professional education was perceived to have some benefits, amidst concerns that may derail its use in health professional education. The lack of policy and guidelines to govern the use of AI in health professions education underscores the need to develop policies and guidelines that safeguard and promote responsible and ethical use of AI.

Indexed as

Artificial IntelligenceAttitude of Health PersonnelEducational MeasurementEducation, MedicalHealth OccupationsHealth PersonnelAdultFemaleHumansInterviews as TopicMaleQualitative ResearchUgandaArtificial intelligenceEducatorsHealth professional educationUganda

Identifiers

PMID41053766
PMCPMC12502576

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.