Artificial Intelligence in Health Education and Practice: A Systematic Review of Health Students’ and Academics’ Knowledge, Perceptions and Experiences
Abstract
ABSTRACT Background/objective Artificial intelligence (AI) is embedded in healthcare education and practice. Pre‐service training on AI technologies allows health professionals to identify the best use of AI. This systematic review explores health students'/academics' perception of using AI in their practice. The authors aimed to identify any gaps in the health curriculum related to AI training that may need to be addressed. Methods Medline (EBSCO), Web of Science, CINAHL (EBSCO), ERIC, Google Scholar, and Scopus were searched using key terms including health students, health academics, AI, and higher education. Quantitative and qualitative studies published in the last seven years were reviewed. JBI SUMARI was used to facilitate study selection, data extraction, and quality assessment of included articles. Thematic and descriptive data analyses were used to retrieve data. This systematic review has been registered in PROSPERO (CRD42023448005). Results Twelve studies, including seven quantitative and five mixed‐method studies, provided novel insights into health students’ perceptions of using AI in health education or practice. Quantitative findings reported significant variations in attitudes and literacy levels regarding AI across different disciplines and demographics. Senior students and those with doctoral degrees exhibited more favourable outlooks compared with their less experienced counterparts (p < 0.001). Students intending to pursue careers in research…
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