TY - JOUR
T1 - Exploring Knowledge, Attitudes, and Practices Towards Artificial Intelligence among Health Professions’ Students in Jordan
AU - Al-Qerem, Walid
AU - Eberhardt, Judith
AU - Jarab, Anan
AU - Al Bawab, Abdel Qader
AU - Hammad, Alaa
AU - Alasmari, Fawaz
AU - Alazab, Badi’ah
AU - Husein, Daoud Abu
AU - Alazab, Jumana
AU - Al-Beool, Saed
N1 - Publisher Copyright:
© 2023, The Author(s).
PY - 2023/12/14
Y1 - 2023/12/14
N2 - The integration of Artificial Intelligence (AI) in medical education and practice is a significant development. This study examined the Knowledge, Attitudes, and Practices (KAP) of health professions' students in Jordan concerning AI, providing insights into their preparedness and perceptions. An online questionnaire was distributed to 483 Jordanian health professions' students via social media. Demographic data, AI-related KAP, and barriers were collected. Quantile regression models analyzed associations between variables and KAP scores. Moderate AI knowledge was observed among participants, with specific understanding of data requirements and barriers. Attitudes varied, combining skepticism about AI replacing human teachers with recognition of its value. While AI tools were used for specific tasks, broader integration in medical education and practice was limited. Barriers included lack of knowledge, access, time constraints, and curriculum gaps. This study highlights the need to enhance medical education with AI topics and address barriers. Students need to be better prepared for AI integration, in order to enable medical education to harness AI's potential for improved patient care and training. [Abstract copyright: © 2023. The Author(s).]
AB - The integration of Artificial Intelligence (AI) in medical education and practice is a significant development. This study examined the Knowledge, Attitudes, and Practices (KAP) of health professions' students in Jordan concerning AI, providing insights into their preparedness and perceptions. An online questionnaire was distributed to 483 Jordanian health professions' students via social media. Demographic data, AI-related KAP, and barriers were collected. Quantile regression models analyzed associations between variables and KAP scores. Moderate AI knowledge was observed among participants, with specific understanding of data requirements and barriers. Attitudes varied, combining skepticism about AI replacing human teachers with recognition of its value. While AI tools were used for specific tasks, broader integration in medical education and practice was limited. Barriers included lack of knowledge, access, time constraints, and curriculum gaps. This study highlights the need to enhance medical education with AI topics and address barriers. Students need to be better prepared for AI integration, in order to enable medical education to harness AI's potential for improved patient care and training. [Abstract copyright: © 2023. The Author(s).]
UR - http://www.scopus.com/inward/record.url?scp=85179669284&partnerID=8YFLogxK
U2 - 10.1186/s12911-023-02403-0
DO - 10.1186/s12911-023-02403-0
M3 - Article
C2 - 38098095
AN - SCOPUS:85179669284
SN - 1472-6947
VL - 23
JO - BMC Medical Informatics and Decision Making
JF - BMC Medical Informatics and Decision Making
M1 - 288
ER -