Mahmoud Abdallat, Jehad Feras AlSamhori, Abdel Rahman Feras AlSamhori, Maya Jamal Kawwa, Sarah Hani Labadi, Ahmad Feras AlSamhori, Hala Hayel Shnekat, Shahem Abdallat, Rand Murshidi
{"title":"影响医学和牙科学生采用人工智能的因素:约旦大学的一项横断面研究。","authors":"Mahmoud Abdallat, Jehad Feras AlSamhori, Abdel Rahman Feras AlSamhori, Maya Jamal Kawwa, Sarah Hani Labadi, Ahmad Feras AlSamhori, Hala Hayel Shnekat, Shahem Abdallat, Rand Murshidi","doi":"10.2147/AMEP.S517110","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Artificial intelligence (AI) is being rapidly adapted in the medical fields due to its ability in enhancing diagnosis and patient care. Recent data reported that students showed positive attitude and moderate knowledge while some had concerns regarding ethical perspective. Therefore, the goal of this study is to examine the variables affecting attitudes, awareness, and comprehension of AI.</p><p><strong>Methods: </strong>A cross-sectional investigation between November 2022 and March 2023 was performed. It utilized survey with five sections that addressed demographics, technological background, attitude, awareness, and AI comprehension. SPSS was utilized to run descriptive analysis, the Mann-Whitney <i>U</i>-test, the chi-square test, Spearman correlation. Further, general linear regression was applied to investigate the factors influencing these scales.</p><p><strong>Results: </strong>The questionnaire was completed by 517 medical and 283 dental students. Pre-clinical students were the most in both groups (84.1%). Medical students were significantly more likely to have taken AI-related courses before (OR: 1.436, 95% CI: 1.007-2.046). The multivariate analysis showed that AI-related courses and prior programming experience were significantly positive factors for the medical students' awareness and understanding of AI among the medical group. While prior programming experience was also significantly a positive factor for the dental students' awareness and understanding of AI among the medical group.</p><p><strong>Conclusion: </strong>As the role of AI in healthcare is improving, there is an obvious call to prepare students for adopting integration with AI technology equipped with both technical competencies and the ethical considerations that are tied to AI applications.</p>","PeriodicalId":47404,"journal":{"name":"Advances in Medical Education and Practice","volume":"16 ","pages":"993-1005"},"PeriodicalIF":1.7000,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12151079/pdf/","citationCount":"0","resultStr":"{\"title\":\"Factors Influencing the Adoption of Artificial Intelligence Among Medical and Dental Students: A Cross-Sectional Study at the University of Jordan.\",\"authors\":\"Mahmoud Abdallat, Jehad Feras AlSamhori, Abdel Rahman Feras AlSamhori, Maya Jamal Kawwa, Sarah Hani Labadi, Ahmad Feras AlSamhori, Hala Hayel Shnekat, Shahem Abdallat, Rand Murshidi\",\"doi\":\"10.2147/AMEP.S517110\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Artificial intelligence (AI) is being rapidly adapted in the medical fields due to its ability in enhancing diagnosis and patient care. Recent data reported that students showed positive attitude and moderate knowledge while some had concerns regarding ethical perspective. Therefore, the goal of this study is to examine the variables affecting attitudes, awareness, and comprehension of AI.</p><p><strong>Methods: </strong>A cross-sectional investigation between November 2022 and March 2023 was performed. It utilized survey with five sections that addressed demographics, technological background, attitude, awareness, and AI comprehension. SPSS was utilized to run descriptive analysis, the Mann-Whitney <i>U</i>-test, the chi-square test, Spearman correlation. Further, general linear regression was applied to investigate the factors influencing these scales.</p><p><strong>Results: </strong>The questionnaire was completed by 517 medical and 283 dental students. Pre-clinical students were the most in both groups (84.1%). Medical students were significantly more likely to have taken AI-related courses before (OR: 1.436, 95% CI: 1.007-2.046). The multivariate analysis showed that AI-related courses and prior programming experience were significantly positive factors for the medical students' awareness and understanding of AI among the medical group. While prior programming experience was also significantly a positive factor for the dental students' awareness and understanding of AI among the medical group.</p><p><strong>Conclusion: </strong>As the role of AI in healthcare is improving, there is an obvious call to prepare students for adopting integration with AI technology equipped with both technical competencies and the ethical considerations that are tied to AI applications.</p>\",\"PeriodicalId\":47404,\"journal\":{\"name\":\"Advances in Medical Education and Practice\",\"volume\":\"16 \",\"pages\":\"993-1005\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2025-06-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12151079/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Medical Education and Practice\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2147/AMEP.S517110\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"EDUCATION, SCIENTIFIC DISCIPLINES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Medical Education and Practice","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2147/AMEP.S517110","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"EDUCATION, SCIENTIFIC DISCIPLINES","Score":null,"Total":0}
Factors Influencing the Adoption of Artificial Intelligence Among Medical and Dental Students: A Cross-Sectional Study at the University of Jordan.
Background: Artificial intelligence (AI) is being rapidly adapted in the medical fields due to its ability in enhancing diagnosis and patient care. Recent data reported that students showed positive attitude and moderate knowledge while some had concerns regarding ethical perspective. Therefore, the goal of this study is to examine the variables affecting attitudes, awareness, and comprehension of AI.
Methods: A cross-sectional investigation between November 2022 and March 2023 was performed. It utilized survey with five sections that addressed demographics, technological background, attitude, awareness, and AI comprehension. SPSS was utilized to run descriptive analysis, the Mann-Whitney U-test, the chi-square test, Spearman correlation. Further, general linear regression was applied to investigate the factors influencing these scales.
Results: The questionnaire was completed by 517 medical and 283 dental students. Pre-clinical students were the most in both groups (84.1%). Medical students were significantly more likely to have taken AI-related courses before (OR: 1.436, 95% CI: 1.007-2.046). The multivariate analysis showed that AI-related courses and prior programming experience were significantly positive factors for the medical students' awareness and understanding of AI among the medical group. While prior programming experience was also significantly a positive factor for the dental students' awareness and understanding of AI among the medical group.
Conclusion: As the role of AI in healthcare is improving, there is an obvious call to prepare students for adopting integration with AI technology equipped with both technical competencies and the ethical considerations that are tied to AI applications.