The Integration of Artificial Intelligence in Healthcare: A Cross-Sectional Study on the Knowledge, Perception, and Readiness of Medical Students at a Tertiary Institution in Nigeria
Background and Aims: The integration of artificial intelligence (AI) is expected to revolutionise healthcare, compelling forthcoming healthcare professionals to arm themselves with essential knowledge and skills. Given this, understanding medical students’ (future healthcare providers’) perspectives and readiness is vital for achieving full integration. This study aimed to assess the knowledge, perspectives, and readiness perceived by medical students at Nnamdi Azikiwe University. Methods: This cross-sectional study conveniently recruited 340 medical students. A pretest self-structured questionnaire was utilised for data collection among students who were already in the clinical phase of their study programme. The Statistical Package for Social Science (SPSS) was used for the analysis of the results. Results: The vast majority of the respondents (99.4%) had heard of AI, but only 3.2% were very familiar with its real-world applications. Most participants (96.8%) lacked formal education or training in AI, and few (7.4%) regularly followed AI-related news. Concerns about AI integration included data privacy (39.4%) and the potential loss of human touch in patient care (70.9%). Job displacement (72.1%) and misuse of AI (55.9%) were common fears. Despite these concerns, more than half of the respondents (55.6%) were interested in AI research, and many expressed openness to collaborating with AI systems (34.1%) and acquiring additional AI-related skills (67.9%). Conclusion: There was a lack of AI knowledge among the respondents, coupled with widespread scepticism about its integration. However, there is a notable interest in AI-related research and projects, indicating a willingness to explore its potential benefits.
Authors
- Cutting B. Favour
- Gabriel Chidera Edeh (ORCID: https://orcid.org/0000-0002-2212-7083)
- Sochima Johnmark Obiekwe (ORCID: https://orcid.org/0000-0001-7869-264X)
- Samuel Ifedioranma Ogenyi (ORCID: https://orcid.org/0000-0002-1556-1623)
- Ejeatuluchukwu Obi (ORCID: https://orcid.org/0000-0003-4745-239X)
- Ikechukwu Benjamin Omaga
- Mmesoma Miriam Ukadike
- Chinyere Esther Iheanyi
- Promise Ugochuku Anisiobi
Institutions
- Nnamdi Azikiwe University (NG)
Publication Details
- Journal
- Apollo Medicine
- Published
- 2024-11-06
- DOI
- https://doi.org/10.1177/09760016241287301
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.12