Evaluation of cognition, perception, and opinion among faculties and postgraduate medical students regarding artificial intelligence tools in health education and research. A cross-sectional survey.
DOI:
https://doi.org/10.51168/sjhrafrica.v7i3.2484Keywords:
Artificial Intelligence, Attitude of Health Personnel, Cross-Sectional Studies, Education, Medical, Graduate, Facult, Health Education, Medical Education, Medical Research, Perception, Postgraduate Education, Questionnaires, StudentsAbstract
Introduction
Artificial intelligence (AI) has substantial transformative potential in enhancing diagnostics, treatment, disease monitoring, health-care delivery, education, and research. Despite these advantages, AI has not yet been formally integrated into the medical curriculum. Therefore, the present study aimed to evaluate the cognition, perception, and opinion of medical teaching faculty members and postgraduate (PG) students regarding the application of AI in medical education and research.
Methods
This cross-sectional survey was conducted among faculty members and PG residents of MKCG Medical College and Hospital, Berhampur, from September 2024 to December 2024. A structured questionnaire comprising 20 items covering cognition, perception, and opinion was administered. A total score of 100 was allotted, with 5 points assigned to each correct response. Analytical statistics were performed using the Chi-square test to assess associations between scores and sociodemographic variables. A p-value <0.05 was considered statistically significant.
Results
Most participants were aged 25–40 years (87%) with male predominance (57%). The Department of Pharmacology contributed the largest share (30%), while only 30% had prior exposure to AI-related CME. Cognition item 6 showed the highest correct response rate (71.6%). In the perception domain, 40% strongly agreed across items, and opinion responses demonstrated agreement ranging from 30% to 80%. The mean cognition score was low (22.46 ± 8.63/50), whereas perception (19.44 ± 3.15) and opinion (20.70 ± 2.21) scores were satisfactory. Significant associations were observed only with designation (PGs vs faculty; p = 0.02) and prior AI exposure (p = 0.04).
Conclusion:
At present, faculty members and postgraduate students have limited knowledge of artificial intelligence but show favourable perceptions toward its integration into medical education and healthcare practice.
Recommendation:
Integrating artificial intelligence education into the postgraduate medical curriculum through structured programs and workshops will enhance knowledge and promote responsible AI use in clinical practice, research, and medical training.
References
Lockey S, Gillespie N, Curtis C. Trust in Artificial Intelligence: Australian Insights. [Internet] The University of Queensland and KPMG Australia; 2020. Available from: https://home.kpmg/ au/en/home/insights/2020/10/artificial-intelligence-trust-ai.html
Kolachalama VB, Garg PS. Machine learning and medical education. NPJ Digit Med. 2018;1:54. doi:10.1038/s41746-018-0061-1
Singh RP, Hom GL, Abramoff MD, Campbell JP, Chiang MF. Current challenges and barriers to real-world artificial intelligence adoption for the healthcare system, provider, and the patient. Transl Vis Sci Technol. 2020;9(2):45. doi:10.1167/tvst.9.2.45
van Teijlingen A, Tuttle T, Bouchachia H, Sathian B, van Teijlingen E. Artificial intelligence and health in Nepal. Nepal J Epidemiol. 2020;10 (3):915–918. doi:10.3126/nje.v10i3.31649
Pinto dos Santos D, Giese D, Brodehl S, Chon SH, Staab W, Kleinert R, et al. Medical students’ attitude towards artificial intelligence: a multicentre survey. Eur Radiol. 2019 Apr; 29(4):1640–6. https://doi.org/ 10.1007/s00330-018-5601-1 PMID: 29980928
Sit C, Srinivasan R, Amlani A, Muthuswamy K, Azam A, Monzon L, et al. Attitudes and perceptions of UK medical students towards artificial intelligence and radiology: a multicentre survey. Insights Imaging. 2020 Dec; 11(1):14. https://doi.org/10.1186/s13244-019-0830-7 PMID: 3202595
Cho SI, Han B, Hur K, Mun JH. Perceptions and attitudes of medical students regarding artificial intelligence in dermatology. J Eur Acad Dermatol Venereol. 2021 Jan; 35(1):e72–3. https://doi.org/10.1111/ jdv.16812 PMID: 32852856
Buabbas, A.J.; Miskin, B.;Alnaqi, A.A.; Ayed, A.K.; Shehab,A.A.; Syed-Abdul, S.; Uddin, M. Investigating Students’ Perceptions towards Artificial Intelligence in Medical Education. Healthcare 2023,11, 1298. https://doi.org/10.3390/healthcare11091298
Stewart J, Lu J, Gahungu N, Goudie A,Fegan PG, Bennamoun M, et al. (2023) WesternAustralian medical students’ attitudes towards artificial intelligence in healthcare. PLoS ONE 18(8): e0290642. https://doi.org/10.1371/journal.pone.0290642
Ahmed Z, Bhinder KK, Tariq A, Tahir MJ, Mehmood Q, Tabassum MS, et al. Knowledge, attitude, and practice of artificial intelligence among doctors and medical students in Pakistan: A cross-sectional online survey. Ann Med Surg (Lond). 2022;76: 103493.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Dr. Adyasha Anindita Panda, Dr. Adyasha Anindita Panda, Dr. Snehasini Dash, Dr. Jayanti Prava Behera

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
















