Journal Article
Published 2025
Spotlighting healthcare frontline workers´ perceptions on artificial intelligence across the globe
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Dr. Amelia Taylor
Co-author
Computer Science & Information Systems (CSIS)
30 total publications
Amelia Taylor is a lecturer in Artificial Intelligence at the Malawi University of Business and Applied Sciences, former the University of Malawi, the Polytechnic. She teaches Artificial Intelligence, Computational Intelligence and programming module...
UN Sustainable Development Goals
Global Impact
Research Fields & Tags
Primary Author
Henrique A. Lima
Co-Authors
Dr. Amelia Taylor
Abstract
We sought to define healthcare workers’ (HCW) views on the integration of generative artificial intelligence (AI) into healthcare delivery and to explore the associated challenges, opportunities, and ethical considerations in low- and middle-income countries (LMICs). We analysed unified data from selected 2023 Gates Foundation AI Grand Challenges projects using a mixed-methods, cross-sectional survey evaluated by an international panel across eight countries. Perceptions were rated on a simplified three-point Likert scale (sceptical, practical, enthusiastic). Among 191 frontline HCWs who interacted with AI tools, 617 responses were assessed by nine evaluators. Enthusiastic responses accounted for the majority (75.4%), while 21.6% were practical and only 3.0% were sceptical. The overall interclass correlation coefficient of 0.93 (95%CI: 0.91–0.94, with an average rating k = 9) indicated excellent inter-rater reliability. While quantitative data underscored a generally positive attitude towards AI, qualitative findings revealed recurring cultural and linguistic barriers and ethical concerns. This is a unique study analysing data from the first applications of generative AI in health in LMICs. these findings offer early insights into generative AI implementation in LMIC healthcare settings and highlights both its transformative potential and the need for careful policy and contextual adaptation.
Year of Publication
2025
External Digital Object URL
Access Publisher / External Source
Journal Name
npj Health Syst.
Volume
28
Issue
2
Page Numbers
28
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