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Medical, Dental, and Nursing Students’ Attitudes and Knowledge Towards Artificial Intelligence: A Systematic Review and Meta-Analysis Publisher Pubmed



Amiri H1 ; Peiravi S2 ; Rezazadeh Shojaee SS3 ; Rouhparvarzamin M4 ; Nateghi MN5 ; Etemadi MH6 ; Shojaeibaghini M7 ; Musaie F8 ; Anvari MH9 ; Asadi Anar M10
Authors
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Authors Affiliations
  1. 1. Student Research Committee, Arak University of Medical Sciences, Arak, Iran
  2. 2. Department of Emergency Medicine, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
  3. 3. Department of Nursing, Faculty of Nursing and Midwifery, Mashhad Medical Sciences, Islamic Azad University, Mashhad, Iran
  4. 4. Student Research Committee, School of Nursing and Midwifery, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
  5. 5. Student Research Committee, Faculty of Nursing and Midwifery, Mashhad University of Medical Sciences, Mashhad, Iran
  6. 6. Students Research Committee, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
  7. 7. Medical Informatics Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
  8. 8. Dentistry Student, Dental Branch, Islamic Azad University, Tehran, Iran
  9. 9. Master of Health Science, Faculty of Health Sciences, Universiti Kebangsaan Malaysia (UKM), Kuala Lumpur, Malaysia
  10. 10. Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, SBUMS, Arabi Ave, Daneshjoo Blvd, Velenjak, Tehran, 19839-63113, Iran

Source: BMC Medical Education Published:2024


Abstract

Background: 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. Method: 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. Result: 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. Conclusion: 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 students to provide more data to guide how AI can be incorporated into education. © The Author(s) 2024.