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

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.

Pre-service teachers’ attitudes towards artificial intelligence and its integration into EFL teaching and learning

“…These results were confirmed by the reported total lack of understanding (63.50%) or poor knowledge (18.98%) of the limitations of AI. These results are consistent with those published in previous studies on the knowledge of AI among teachers or pre-service teachers (Álvarez-Herrero, 2024;Chounta, Bardone, Raudsep, & Pedaste (2021) or university students from other disciplines (Ahmed, Bhinder, Tariq et al, 2022;Al Hadithy, Al Lawati, Al-Zadjali, & Al Sinawi, 2023;Al-Qerem, Eberhardt, Jarab et al, 2023;Truong, Vo et al, 2023;Al Saad, Shehadeh, Alanazi et al, 2022;Asmatahasin, Pratap et al, 2021;Baigi, Sarbaz, Ghaddaripouri, et al 2023;Doumat, Daher, Ghanem, & Khater, 2022;Fernandes, Bafna, Patel, & Parmar, 2022;Keleş & Aydın, 2021;Pinto Dos Santos, Giese, Brodehl et al 2019;Teng, Singla, Yau et al 2022;van Hoek, Huber, Leichtle et al 2019).…”

“…• In all studies, the responding students had no (Ahmed, Bhinder, Tariq et al, 2022;Al Hadithy, Al Lawati, Al-Zadjali, & Al Sinawi, 2023;Al-Qerem, Eberhardt, Jarab et al, 2023;Truong, Vo et al, 2023) or only basic knowledge of AI and its functionalities (Al Saad, Shehadeh, Alanazi et al, 2022;Asmatahasin, Pratap et al, 2021;Baigi, Sarbaz, Ghaddaripouri, et al, 2023;Doumat, Daher, Ghanem, & Khater, 2022;Fernandes, Bafna, Patel, & Parmar, 2022;Keleş & Aydın, 2021;Pinto Dos Santos, Giese, Brodehl et al, 2019;Teng, Singla, Yau et al, 2022;van Hoek, Huber, Leichtle et al, 2019).…”

“…• Barriers to their AI knowledge were identified by respondents as lack of knowledge, access, time constraints and curriculum gaps (Al-Qerem, Eberhardt, Jarab, et al (2023); Doumat, Daher, Ghanem, & Khater, 2022;Fernandes, Bafna, Patel, & Parmar, 2022;Truong, Vo et al, 2023).…”

Exploring Allied Health Professionals' Perceptions and Knowledge of Artificial Intelligence in Healthcare

“…Foundational education may cover general AI principles, while specialized education allows students to delve deeper into specific applications relevant to their allied health disciplines. 15 Basic vs Advanced (21%): Twenty-one percent of respondents chose the Basic vs Advanced framework for categorizing AI education. This suggests a preference for a tiered approach, where students start with fundamental concepts and gradually progress to more advanced topics.…”

Transforming Hospital Quality Improvement Through Harnessing the Power of Artificial Intelligence

“…Perspectives on using AI applications have been extensively explored from the viewpoints of healthcare professionals, such as managers, physicians, nurses, and technicians. [ 54 ] However, there has been a notable absence of studies assessing the perceptions of quality professionals. Additionally, our FMEA case study suggests the need for further exploration to expand AI’s capabilities beyond the construction of quality tool components and extend it to the creation of visual tools.…”