Ethical review of AI health research
An exploratory qualitative study on experiences and challenges of research ethics committees in Uganda
Bibliographic Data
| ID | 21787666 |
|---|---|
| Authors | Sylvia Nabukenya (0000-0001-5868-7376, Makerere University, corresponding author), William Wasswa (0000-0002-0202-1230, Mbarara University of Science and Technology), Adelline Twimukye (0000-0002-5053-0574, Makerere University), Erisa Mwaka (0000-0003-1672-9608, Makerere University) |
| Year | 2026 |
| Volume | 22 |
| Issue | 2 |
| Pages | 292-303 |
| Publication date | 2026-04-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Research Ethics (JOURNAL) |
| Journal identifiers | ISSN: 1747-0161 • E-ISSN: 2047-6094 |
| Publisher | SAGE Publications (PUBLISHER • US) |
| DOI | 10.1177/17470161251370400 |
| OpenAlex | W4414026524 |
| Language | EN |
| References cited | 26 |
The use of artificial intelligence (AI) in health research of both communicable and non-communicable diseases has shown an improvement in diagnosis, reduced researchers’ workload, and facilitated real-time data analysis. However, several ethical concerns on public trust, privacy, accountability and fairness regarding access to AI have been pointed out to expose the users of AI to harm. Whereas AI technologies continue to grow rapidly in health research, there is limited knowledge on research ethics committees’ (REC) current practices and challenges experienced when reviewing AI health research in low resource settings like Uganda. This study examined the current practices and challenges experienced by ethics committees during the review of AI health research. We adopted a qualitative exploratory approach, where in-depth interviews were conducted with 12 REC members and 6 REC administrators between May and September 2024. A thematic approach was used to analyze the results. Three themes merged from this data including current practices of RECs, challenges experienced by REC members when reviewing AI health research proposals, and the proposed solutions to the mentioned challenges. Of interest, respondents expressed concerns of limited training and expertise in field of AI, inadequate guiding and reference tools, and unreasonable demands from researchers. Therefore, it is essential to build capacity for REC members and develop comprehensive guidelines, and standard operating procedures for efficient and constructive feedback to researchers
Engineering ethics · Exploratory research · Political science · Qualitative research · Research ethics · Social science · Sociology · Artificial Intelligence in Healthcare and Education · Engineering · Ethics and Social Impacts of AI · Ethics in Clinical Research · Psychology
Qualitative methods in research on healthcare quality
Principles alone cannot guarantee ethical AI
Principled Artificial Intelligence
Qualitative research in health care
Consolidated criteria for reporting qualitative research (Coreq)
Leveraging artificial intelligence to detect ethical concerns in medical research
Public interest in health data research
Composition and capacity of Institutional Review Boards, and challenges experienced by members in ethics review processes in Addis Ababa, Ethiopia
Using the Emanuel et al. Framework to Assess Ethical Issues Raised by a Biomedical Research Ethics Committee in South Africa
The Challenges of Big Data for Research Ethics Committees
Working Through Ethics Review of Big Data Research Projects
Boundaries Between Research Ethics and Ethical Research Use in Artificial Intelligence Health Research
Ethics Regulation in Social Computing Research
Using thematic analysis in psychology
Predictive privacy
Demonstrating Rigor Using Thematic Analysis
| Highly cited | No |
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