Medical, dental, and nursing students’ attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis
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 rep...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2024-04-01
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| Series: | BMC Medical Education |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12909-024-05406-1 |
| _version_ | 1797199306560634880 |
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| author | Hamidreza Amiri Samira Peiravi Seyedeh sara rezazadeh shojaee Motahareh Rouhparvarzamin Mohammad Naser Nateghi Mohammad Hossein Etemadi Mahdie ShojaeiBaghini Farhan Musaie Mohammad Hossein Anvari Mahsa Asadi Anar |
| author_facet | Hamidreza Amiri Samira Peiravi Seyedeh sara rezazadeh shojaee Motahareh Rouhparvarzamin Mohammad Naser Nateghi Mohammad Hossein Etemadi Mahdie ShojaeiBaghini Farhan Musaie Mohammad Hossein Anvari Mahsa Asadi Anar |
| author_sort | Hamidreza Amiri |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-24T07:13:40Z |
| format | Article |
| id | doaj.art-00b13e1548274c608e01813b4bf72c68 |
| institution | Directory Open Access Journal |
| issn | 1472-6920 |
| language | English |
| last_indexed | 2024-04-24T07:13:40Z |
| publishDate | 2024-04-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Education |
| spelling | doaj.art-00b13e1548274c608e01813b4bf72c682024-04-21T11:22:14ZengBMCBMC Medical Education1472-69202024-04-0124111210.1186/s12909-024-05406-1Medical, dental, and nursing students’ attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysisHamidreza Amiri0Samira Peiravi1Seyedeh sara rezazadeh shojaee2Motahareh Rouhparvarzamin3Mohammad Naser Nateghi4Mohammad Hossein Etemadi5Mahdie ShojaeiBaghini6Farhan Musaie7Mohammad Hossein Anvari8Mahsa Asadi Anar9Student Research Committee, Arak University of Medical SciencesDepartment of Emergency Medicine, Faculty of Medicine, Mashhad University of Medical SciencesDepartment of Nursing, Faculty of Nursing and Midwifery, Mashhad Medical Sciences, Islamic Azad UniversityStudent Research Committee, School of Nursing and Midwifery, Shahid Sadoughi University of Medical SciencesStudent Research Committee, Faculty of Nursing and Midwifery, Mashhad University of Medical SciencesStudents Research Committee, School of Medicine, Isfahan University of Medical SciencesMedical Informatics Research Center, Institute for Futures Studies in Health, Kerman University of Medical SciencesDentistry Student, Dental Branch, Islamic Azad UniversityMaster of Health Science, Faculty of Health Sciences, Universiti Kebangsaan Malaysia (UKM)Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, SBUMSAbstract 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.https://doi.org/10.1186/s12909-024-05406-1Artificial intelligenceAIMedical studentsDental studentsNursing studentsMeta-analysis |
| spellingShingle | Hamidreza Amiri Samira Peiravi Seyedeh sara rezazadeh shojaee Motahareh Rouhparvarzamin Mohammad Naser Nateghi Mohammad Hossein Etemadi Mahdie ShojaeiBaghini Farhan Musaie Mohammad Hossein Anvari Mahsa Asadi Anar Medical, dental, and nursing students’ attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis BMC Medical Education Artificial intelligence AI Medical students Dental students Nursing students Meta-analysis |
| title | Medical, dental, and nursing students’ attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis |
| title_full | Medical, dental, and nursing students’ attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis |
| title_fullStr | Medical, dental, and nursing students’ attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis |
| title_full_unstemmed | Medical, dental, and nursing students’ attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis |
| title_short | Medical, dental, and nursing students’ attitudes and knowledge towards artificial intelligence: a systematic review and meta-analysis |
| title_sort | medical dental and nursing students attitudes and knowledge towards artificial intelligence a systematic review and meta analysis |
| topic | Artificial intelligence AI Medical students Dental students Nursing students Meta-analysis |
| url | https://doi.org/10.1186/s12909-024-05406-1 |
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