Factors Influencing the Adoption of Artificial Intelligence Among Medical and Dental Students: A Cross-Sectional Study at the University of Jordan

被引:0
作者
Abdallat, Mahmoud [1 ]
AlSamhori, Jehad Feras [2 ]
AlSamhori, Abdel Rahman Feras [2 ]
Kawwa, Maya Jamal [3 ]
Labadi, Sarah Hani [2 ]
AlSamhori, Ahmad Feras [2 ]
Shnekat, Hala Hayel [4 ]
Abdallat, Shahem [5 ]
Murshidi, Rand [6 ]
机构
[1] Univ Jordan, Dept Neurosurg, Amman, Jordan
[2] Univ Jordan, Fac Med, Amman 11942, Jordan
[3] European Univ, Fac Med, Tbilisi, Georgia
[4] Univ Jordan, Fac Dent, Amman 11942, Jordan
[5] Xavier Univ, Fac Med, Cincinnati, OH USA
[6] Univ Jordan, Sch Med, Dept Dermatol, Amman, Jordan
关键词
artificial intelligence; AI adoption; attitude; medical education; dental education; University of Jordan;
D O I
10.2147/AMEP.S517110
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
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.
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页码:993 / 1005
页数:13
相关论文
共 26 条
[1]   Medical and Dental Professionals Readiness for Artificial Intelligence for Saudi Arabia Vision 2030 [J].
Aboalshamat, Khalid ;
Alhuzali, Rahaf ;
Alalyani, Afnan ;
Alsharif, Sarah ;
Qadhi, Hala ;
Almatrafi, Renad ;
Ammash, Dhuha ;
Alotaibi, Shymaa .
INTERNATIONAL JOURNAL OF PHARMACEUTICAL RESEARCH AND ALLIED SCIENCES, 2022, 11 (04) :52-59
[2]   Artificial Intelligence in Dentistry: Past, Present, and Future [J].
Agrawal, Paridhi ;
Nikhade, Pradnya .
CUREUS JOURNAL OF MEDICAL SCIENCE, 2022, 14 (07)
[3]   Evaluating the understanding of the ethical and moral challenges of Big Data and AI among Jordanian medical students, physicians in training, and senior practitioners: a cross-sectional study [J].
Al-Ani, Abdallah ;
Rayyan, Abdallah ;
Maswadeh, Ahmad ;
Sultan, Hala ;
Alhammouri, Ahmad ;
Asfour, Hadeel ;
Alrawajih, Tariq ;
Al Sharie, Sarah ;
Al Karmi, Fahed ;
Azzam, Ahmad ;
Mansour, Asem ;
Al-Hussaini, Maysa .
BMC MEDICAL ETHICS, 2024, 25 (01)
[4]   Exploring knowledge, attitudes, and practices towards artificial intelligence among health professions' students in Jordan [J].
Al-Qerem, Walid ;
Eberhardt, Judith ;
Jarab, Anan ;
Al Bawab, Abdel Qader ;
Hammad, Alaa ;
Alasmari, Fawaz ;
Alazab, Badi'ah ;
Husein, Daoud Abu ;
Alazab, Jumana ;
Al-Beool, Saed .
BMC MEDICAL INFORMATICS AND DECISION MAKING, 2023, 23 (01)
[5]   Knowledge, attitude, and perception of Arab medical students towards artificial intelligence in medicine and radiology: A multi-national cross-sectional study [J].
Allam, Ahmed Hafez ;
Eltewacy, Nael Kamel ;
Alabdallat, Yasmeen Jamal ;
Owais, Tarek A. ;
Salman, Saif ;
Ebada, Mahmoud A. .
EUROPEAN RADIOLOGY, 2024, 34 (07) :1-14
[6]   Implication of artificial intelligence on astrocytoma detection and treatment [J].
AlSamhori, Ahmad Feras ;
AlSamhori, Jehad Feras ;
Dib, Christie ;
AlSamhori, Abdel Rahman Feras ;
Shehadeh, Mohammed Wael ;
Rihani, Jude ;
Saadeh, Ahmad ;
Al-sabbagh, Maryam Qussay ;
Almajali, Hala .
AVICENNA, 2025, 2025 (01)
[7]  
AlSamhori ARF, 2023, High Yield Med Rev., V1, DOI [10.59707/hymrTFFP5435, DOI 10.59707/HYMRTFFP5435]
[8]   Transforming depression care with artificial intelligence [J].
AlSamhori, Jehad Feras ;
Alsamhori, Abdel Rahman Feras ;
Kakish, Diala Ra'Ed Kamal ;
Nashwan, Abdulqadir J. .
ASIAN JOURNAL OF PSYCHIATRY, 2024, 101
[9]   Are physicians and medical students ready for artificial intelligence applications in healthcare? [J].
AlZaabi, Adhari ;
AlMaskari, Saleh ;
AalAbdulsalam, Abdulrahman .
DIGITAL HEALTH, 2023, 9
[10]   Ethical Dilemmas of Using Artificial Intelligence in Medicine [J].
Astarastoae, Vasile ;
Rogozea, Liliana M. ;
Leasu, Florin ;
Ioan, Beatrice Gabriela .
AMERICAN JOURNAL OF THERAPEUTICS, 2024, 31 (04) :e388-e397