Assessment of Knowledge, Attitude, and Practice Among Healthcare Providers and Medical Students of Artificial Intelligence in Saudi Arabia

Background: AI holds significant promise in revolutionizing healthcare delivery by augmenting diagnostic accuracy, treatment planning, and patient care. The objective of this study was to evaluate the knowledge, attitudes, and practices regarding AI among healthcare providers and medical students in Saudi Arabia, and to identify any distinctions among different qualification levels. This study was approved by Batterjee Medical College’s Ethics Committee. Methods: A cross-sectional research design was adopted, with a survey being administered to individuals representing various academic levels, including undergraduate, graduate, and postgraduate students. The survey tool assessed participants’ familiarity with AI concepts, their attitudes towards integrating AI in healthcare, and the extent of AI utilization in their practice or studies. The analysis of the data was conducted using Kruskal Wallis test and pairwise comparison was done. Results: Results showed a significant variation in knowledge and attitudes towards AI among the different qualification levels. Undergraduate participants showed a moderate understanding of AI concepts, with a median knowledge score of 3 (IQR = 2). In contrast, graduate and postgraduate participants exhibited significantly higher median knowledge scores of 6 (IQR = 2), reflecting a more comprehensive grasp of AI principles and applications (P-value of .02). Attitudes towards AI also varied significantly among qualification levels, with undergraduate participants displaying a median attitude score of 6 (IQR = 2), indicating a generally positive perception of AI’s potential in healthcare (P-value of .032). No significant differences were observed in practice scores across qualification levels, suggesting consistent utilization of AI in practice or studies, regardless of knowledge and attitude levels. Also, regional wise comparison showed the Middle region exhibited the highest AI adoption rate (42.9%), followed by the Southern (21.3%), Northern (11.8%), Western (13.3%), and Eastern (10.7%) regions of KSA. Conclusions: Targeted educational interventions are necessary to improve AI literacy among healthcare providers and medical students, particularly at the undergraduate level. By providing future healthcare professionals with a solid understanding of AI principles and fostering positive attitudes towards AI integration, stakeholders can harness the full potential of AI to enhance healthcare delivery and improve patient outcomes in Saudi Arabia.Qualification level Knowledge scoreAttitude scorePractice scoreQualification levelMedianIQRp valueMedianIQRp valueMedianIQRp valueUndergraduate320.018620.032330.061Graduate620.018620.032530.061Post-graduate620.018620.032530.061

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Publication Details

Journal
Respiratory Care
Published
2024-10-01
DOI
https://doi.org/10.4187/respcare.20244138061
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
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0.00
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article

Assessment of Knowledge, Attitude, and Practice Among Healthcare Providers and Medical Students of Artificial Intelligence in Saudi Arabia

G Gokul, Layan Fahad Saaty, Renad Alofi, Raghad Ashiri et al.
Respiratory Care
Artificial Intelligence in Healthcare and Education
article

Assessment of Knowledge, Attitude, and Practice Among Healthcare Providers and Medical Students of Artificial Intelligence in Saudi Arabia

G Gokul, Layan Fahad Saaty, Renad Alofi, Raghad Ashiri, Nuran Albatati, Mazen Homoud, Moroug Sabbagh, Dr. Ayedh Dhafer Ali Al-ahmari
article en

Abstract

Background: AI holds significant promise in revolutionizing healthcare delivery by augmenting diagnostic accuracy, treatment planning, and patient care. The objective of this study was to evaluate the knowledge, attitudes, and practices regarding AI among healthcare providers and medical students in Saudi Arabia, and to identify any distinctions among different qualification levels. This study was approved by Batterjee Medical College’s Ethics Committee. Methods: A cross-sectional research design was adopted, with a survey being administered to individuals representing various academic levels, including undergraduate, graduate, and postgraduate students. The survey tool assessed participants’ familiarity with AI concepts, their attitudes towards integrating AI in healthcare, and the extent of AI utilization in their practice or studies. The analysis of the data was conducted using Kruskal Wallis test and pairwise comparison was done. Results: Results showed a significant variation in knowledge and attitudes towards AI among the different qualification levels. Undergraduate participants showed a moderate understanding of AI concepts, with a median knowledge score of 3 (IQR = 2). In contrast, graduate and postgraduate participants exhibited significantly higher median knowledge scores of 6 (IQR = 2), reflecting a more comprehensive grasp of AI principles and applications (P-value of .02). Attitudes towards AI also varied significantly among qualification levels, with undergraduate participants displaying a median attitude score of 6 (IQR = 2), indicating a generally positive perception of AI’s potential in healthcare (P-value of .032). No significant differences were observed in practice scores across qualification levels, suggesting consistent utilization of AI in practice or studies, regardless of knowledge and attitude levels. Also, regional wise comparison showed the Middle region exhibited the highest AI adoption rate (42.9%), followed by the Southern (21.3%), Northern (11.8%), Western (13.3%), and Eastern (10.7%) regions of KSA. Conclusions: Targeted educational interventions are necessary to improve AI literacy among healthcare providers and medical students, particularly at the undergraduate level. By providing future healthcare professionals with a solid understanding of AI principles and fostering positive attitudes towards AI integration, stakeholders can harness the full potential of AI to enhance healthcare delivery and improve patient outcomes in Saudi Arabia.Qualification level Knowledge scoreAttitude scorePractice scoreQualification levelMedianIQRp valueMedianIQRp valueMedianIQRp valueUndergraduate320.018620.032330.061Graduate620.018620.032530.061Post-graduate620.018620.032530.061

Respiratory CareVol. 69(10_suppl)
King Abdulaziz University (SA), King Abdulaziz Hospital (SA), University of Business and Technology (SA)
Quality Education
Openalex Percentile: Top 54%
Artificial Intelligence in Healthcare and Education
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