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Systematic reviews (SR) provide the highest level of evidence in research. Medical students are encouraged to learn how to conduct SR, yet barriers to engaging in these reviews need to be identified to enhance their implementation. This study aimed to assess the knowledge, practices, and perceived barriers to conducting SR among undergraduate medical students from Arab countries. A cross-sectional study was conducted involving undergraduate medical students from nine Arab countries enrolled in public and private medical schools. Sociodemographic information, as well as data on knowledge and barriers to conducting SR, were collected from participants through an online survey. The level of knowledge regarding SR was measured using a set of questions, with a total score of 19. Adjusted odds ratio (AOR) were used to find the associated factors with good knowledge of SR. With a response rate of 89.7%, 13,060 participants were enrolled, of whom 58.9% were female and 77.0% were studying at public universities. Additionally, 49.0% were in their clinical years. Approximately 31% had heard about SR, and 3,275 participants (25.1%) had attended training on SR. Overall, only 4.3% of participants demonstrated good knowledge of SRs. Multivariate logistic regression analysis revealed that age (AOR = 1.111, 95% CI: 1.069-1.154) and participation in research-related activities (AOR = 4.501, 95% CI: 3.650-5.551) were significantly associated with good knowledge of SR. The most identified barriers to conducting SRs included a lack of knowledge about SR (47.0%) and a lack of research exposure and opportunities (28.8%). Regarding engagement in secondary research, only 1,567 participants (12.0%) had participated in a secondary research project, and of those, only 471 (30.1%) had published their work. The types of enrolled research projects included SR (62.3%), systematic reviews with meta-analysis (43.3%), and network meta-analysis (33.4%). The findings indicate a poor level of knowledge regarding SR among participants and highlight several barriers preventing undergraduate medical students from engaging in this research. There is a pressing need for further training on SR to enhance the knowledge and practice of SR among undergraduate medical students.

Objectives We aimed to assess undergraduate medical students’ knowledge, attitude, and perception regarding artificial intelligence (AI) in medicine. Methods A multi-national, multi-center cross-sectional study was conducted from March to April 2022, targeting undergraduate medical students in nine Arab countries. The study utilized a web-based questionnaire, with data collection carried out with the help of national leaders and local collaborators. Logistic regression analysis was performed to identify predictors of knowledge, attitude, and perception among the participants. Additionally, cluster analysis was employed to identify shared patterns within their responses. Results Of the 4492 students surveyed, 92.4% had not received formal AI training. Regarding AI and deep learning (DL), 87.1% exhibited a low level of knowledge. Most students (84.9%) believed AI would revolutionize medicine and radiology, with 48.9% agreeing that it could reduce the need for radiologists. Students with high/moderate AI knowledge and training had higher odds of agreeing to endorse AI replacing radiologists, reducing their numbers, and being less likely to consider radiology as a career compared to those with low knowledge/no AI training. Additionally, the majority agreed that AI would aid in the automated detection and diagnosis of pathologies. Conclusions Arab medical students exhibit a notable deficit in their knowledge and training pertaining to AI. Despite this, they hold a positive perception of AI implementation in medicine and radiology, demonstrating a clear understanding of its significance for the healthcare system and medical curriculum. Clinical relevance statement This study highlights the need for widespread education and training in artificial intelligence for Arab medical students, indicating its significance for healthcare systems and medical curricula. Key Points • Arab medical students demonstrate a significant knowledge and training gap when it comes to using AI in the fields of medicine and radiology . • Arab medical students recognize the importance of integrating AI into the medical curriculum. Students with a deeper understanding of AI were more likely to agree that all medical students should receive AI education. However, those with previous AI training were less supportive of this idea . • Students with moderate/high AI knowledge and training displayed increased odds of agreeing that AI has the potential to replace radiologists, reduce the demand for their services, and were less inclined to pursue a career in radiology, when compared to students with low knowledge/no AI training .

ObjectivesWe aimed to assess undergraduate medical students’ knowledge, attitude, and perception regarding artificial intelligence (AI) in medicine.MethodsA multi-national, multi-center cross-sectional study was conducted from March to April 2022, targeting undergraduate medical students in nine Arab countries. The study utilized a web-based questionnaire, with data collection carried out with the help of national leaders and local collaborators. Logistic regression analysis was performed to identify predictors of knowledge, attitude, and perception among the participants. Additionally, cluster analysis was employed to identify shared patterns within their responses.ResultsOf the 4492 students surveyed, 92.4% had not received formal AI training. Regarding AI and deep learning (DL), 87.1% exhibited a low level of knowledge. Most students (84.9%) believed AI would revolutionize medicine and radiology, with 48.9% agreeing that it could reduce the need for radiologists. Students with high/moderate AI knowledge and training had higher odds of agreeing to endorse AI replacing radiologists, reducing their numbers, and being less likely to consider radiology as a career compared to those with low knowledge/no AI training. Additionally, the majority agreed that AI would aid in the automated detection and diagnosis of pathologies.ConclusionsArab medical students exhibit a notable deficit in their knowledge and training pertaining to AI. Despite this, they hold a positive perception of AI implementation in medicine and radiology, demonstrating a clear understanding of its significance for the healthcare system and medical curriculum.Clinical relevance statementThis study highlights the need for widespread education and training in artificial intelligence for Arab medical students, indicating its significance for healthcare systems and medical curricula.Key Points• Arab medical students demonstrate a significant knowledge and training gap when it comes to using AI in the fields of medicine and radiology.• Arab medical students recognize the importance of integrating AI into the medical curriculum. Students with a deeper understanding of AI were more likely to agree that all medical students should receive AI education. However, those with previous AI training were less supportive of this idea.• Students with moderate/high AI knowledge and training displayed increased odds of agreeing that AI has the potential to replace radiologists, reduce the demand for their services, and were less inclined to pursue a career in radiology, when compared to students with low knowledge/no AI training.