Exploring knowledge, attitudes, and practices towards artificial intelligence among health professions’ students in Jordan

Autor: Walid Al-Qerem, Judith Eberhardt, Anan Jarab, Abdel Qader Al Bawab, Alaa Hammad, Fawaz Alasmari, Badi’ah Alazab, Daoud Abu Husein, Jumana Alazab, Saed Al-Beool
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: BMC Medical Informatics and Decision Making, Vol 23, Iss 1, Pp 1-7 (2023)
Druh dokumentu: article
ISSN: 1472-6947
DOI: 10.1186/s12911-023-02403-0
Popis: Abstract Introduction 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. Methods 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. Results 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. Conclusions 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.
Databáze: Directory of Open Access Journals
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