Medical, dental, and nursing students’ attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis
Abstract
Nowadays, Artificial intelligence (AI) is one of the most popular topics that can be integrated into healthcare activities. Currently, AI is used in specialized fields such as radiology, pathology, and ophthalmology. Despite the advantages of AI, the fear of human labor being replaced by this technology makes some students reluctant to choose specific fields. This meta-analysis aims to investigate the knowledge and attitude of medical, dental, and nursing students and experts in this field about AI and its application. This study was designed based on PRISMA guidelines. PubMed, Scopus, and Google Scholar databases were searched with relevant keywords. After study selection according to inclusion criteria, data of knowledge and attitude were extracted for meta-analysis. Twenty-two studies included 8491 participants were included in this meta-analysis. The pooled analysis revealed a proportion of 0.44 (95%CI = [0.34, 0.54], P < 0.01, I2 = 98.95%) for knowledge. Moreover, the proportion of attitude was 0.65 (95%CI = [0.55, 0.75], P < 0.01, I2 = 99.47%). The studies did not show any publication bias with a symmetrical funnel plot. Average levels of knowledge indicate the necessity of including relevant educational programs in the student’s academic curriculum. The positive attitude of students promises the acceptance of AI technology. However, dealing with ethics education in AI and the aspects of human-AI cooperation are discussed. Future longitudinal studies could follow…
How strong is the evidence?
Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid. Reported size: 8,491 participants or records.
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