Shaping the future: perspectives on the Integration of Artificial Intelligence in health profession education: a multi-country survey.

Artificial intelligence (AI) is transforming health profession education (HPE) through personalized learning technologies. HPE students must also learn about AI to understand its impact on healthcare delivery. We examined HPE students' AI-related knowledge and attitudes, and perceived challenges in integrating AI in HPE. This cross-sectional included medical, nursing, physiotherapy, and clinical nutrition students from four public universities in Jordan, the Kingdom of Saudi Arabia (KSA), the United Arab Emirates (UAE), and Egypt. Data were collected between February and October 2023 via an online survey that covered five main domains: benefits of AI in healthcare, negative impact on patient trust, negative impact on the future of healthcare professionals, inclusion of AI in HPE curricula, and challenges hindering integration of AI in HPE. Of 642 participants, 66.4% reported low AI knowledge levels. The UAE had the largest proportion of students with low knowledge (72.7%). The majority (54.4%) of participants had learned about AI outside their curriculum, mainly through social media (66%). Overall, 51.2% expressed positive attitudes toward AI, with Egypt showing the largest proportion of positive attitudes (59.1%). Although most participants viewed AI in healthcare positively (91%), significant variations were observed in other domains. The majority (77.6%) supported integrating AI in HPE, especially in Egypt (82.3%). A perceived negative impact of AI on patient trust was expressed by 43.5% of participants, particularly in Egypt (54.7%). Only 18.1% of participants were concerned about the impact of AI on future healthcare professionals, with the largest proportion from Egypt (33.0%). Some participants (34.4%) perceived AI integration as challenging, notably in the UAE (47.6%). Common barriers included lack of expert training (53%), awareness (50%), and interest in AI (41%). This study clarified key considerations when integrating AI in HPE. Enhancing students' awareness and fostering innovation in an AI-driven medical landscape are crucial for effectively incorporating AI in HPE curricula.

Issa WB ，Shorbagi A ，Al-Sharman A ，Rababa M ，Al-Majeed K ，Radwan H ，Refaat Ahmed F ，Al-Yateem N ，Mottershead R ，Abdelrahim DN ，Hijazi H ，Khasawneh W ，Ali I ，Abbas N ，Fakhry R ... -  《BMC Medical Education》

Knowledge, attitude, and perception of Arab medical students towards artificial intelligence in medicine and radiology: A multi-national cross-sectional study.

Allam AH ，Eltewacy NK ，Alabdallat YJ ，Owais TA ，Salman S ，Ebada MA ，EARG Group ... -  《-》

Artificial intelligence in medical education - perception among medical students.

As Artificial Intelligence (AI) becomes pervasive in healthcare, including applications like robotic surgery and image analysis, the World Medical Association emphasises integrating AI education into medical curricula. This study evaluates medical students' perceptions of 'AI in medicine', their preferences for AI training in education, and their grasp of AI's ethical implications in healthcare. A cross-sectional study was conducted among 325 medical students in Kerala using a pre-validated, semi structured questionnaire. The survey collected demographic data, any past educational experience about AI, participants' self-evaluation of their knowledge and evaluated self-perceived understanding of applications of AI in medicine. Participants responded to twelve Likert-scale questions targeting perceptions and ethical aspects and their opinions on suggested topics on AI to be included in their curriculum. AI was viewed as an assistive technology for reducing medical errors by 57.2% students and 54.2% believed AI could enhance medical decision accuracy. About 49% agreed that AI could potentially improve accessibility to healthcare. Concerns about AI replacing physicians were reported by 37.6% and 69.2% feared a reduction in the humanistic aspect of medicine. Students were worried about challenges to trust (52.9%), patient-physician relationships (54.5%) and breach of professional confidentiality (53.5%). Only 3.7% felttotally competent in informing patients about features and risks associated with AI applications. Strong demand for structured AI training was expressed, particularly on reducing medical errors (76.9%) and ethical issues (79.4%). This study highlights medical students' demand for structured AI training in undergraduate curricula, emphasising its importance in addressing evolving healthcare needs and ethical considerations. Despite widespread ethical concerns, the majority perceive AI as an assistive technology in healthcare. These findings provide valuable insights for curriculum development and defining learning outcomes in AI education for medical students.

Jackson P ，Ponath Sukumaran G ，Babu C ，Tony MC ，Jack DS ，Reshma VR ，Davis D ，Kurian N ，John A ... -  《BMC Medical Education》

Perceptions of undergraduate medical students on artificial intelligence in medicine: mixed-methods survey study from Palestine.

The current applications of artificial intelligence (AI) in medicine continue to attract the attention of medical students. This study aimed to identify undergraduate medical students' attitudes toward AI in medicine, explore present AI-related training opportunities, investigate the need for AI inclusion in medical curricula, and determine preferred methods for teaching AI curricula. This study uses a mixed-method cross-sectional design, including a quantitative study and a qualitative study, targeting Palestinian undergraduate medical students in the academic year 2022-2023. In the quantitative part, we recruited a convenience sample of undergraduate medical students from universities in Palestine from June 15, 2022, to May 30, 2023. We collected data by using an online, well-structured, and self-administered questionnaire with 49 items. In the qualitative part, 15 undergraduate medical students were interviewed by trained researchers. Descriptive statistics and an inductive content analysis approach were used to analyze quantitative and qualitative data, respectively. From a total of 371 invitations sent, 362 responses were received (response rate = 97.5%), and 349 were included in the analysis. The mean age of participants was 20.38 ± 1.97, with 40.11% (140) in their second year of medical school. Most participants (268, 76.79%) did not receive formal education on AI before or during medical study. About two-thirds of students strongly agreed or agreed that AI would become common in the future (67.9%, 237) and would revolutionize medical fields (68.7%, 240). Participants stated that they had not previously acquired training in the use of AI in medicine during formal medical education (260, 74.5%), confirming a dire need to include AI training in medical curricula (247, 70.8%). Most participants (264, 75.7%) think that learning opportunities for AI in medicine have not been adequate; therefore, it is very important to study more about employing AI in medicine (228, 65.3%). Male students (3.15 ± 0.87) had higher perception scores than female students (2.81 ± 0.86) (p < 0.001). The main themes that resulted from the qualitative analysis of the interview questions were an absence of AI learning opportunities, the necessity of including AI in medical curricula, optimism towards the future of AI in medicine, and expected challenges related to AI in medical fields. Medical students lack access to educational opportunities for AI in medicine; therefore, AI should be included in formal medical curricula in Palestine.

Jebreen K ，Radwan E ，Kammoun-Rebai W ，Alattar E ，Radwan A ，Safi W ，Radwan W ，Alajez M ... -  《BMC Medical Education》

Global cross-sectional student survey on AI in medical, dental, and veterinary education and practice at 192 faculties.

The successful integration of artificial intelligence (AI) in healthcare depends on the global perspectives of all stakeholders. This study aims to answer the research question: What are the attitudes of medical, dental, and veterinary students towards AI in education and practice, and what are the regional differences in these perceptions? An anonymous online survey was developed based on a literature review and expert panel discussions. The survey assessed students' AI knowledge, attitudes towards AI in healthcare, current state of AI education, and preferences for AI teaching. It consisted of 16 multiple-choice items, eight demographic queries, and one free-field comment section. Medical, dental, and veterinary students from various countries were invited to participate via faculty newsletters and courses. The survey measured technological literacy, AI knowledge, current state of AI education, preferences for AI teaching, and attitudes towards AI in healthcare using Likert scales. Data were analyzed using descriptive statistics, Mann-Whitney U-test, Kruskal-Wallis test, and Dunn-Bonferroni post hoc test. The survey included 4313 medical, 205 dentistry, and 78 veterinary students from 192 faculties and 48 countries. Most participants were from Europe (51.1%), followed by North/South America (23.3%) and Asia (21.3%). Students reported positive attitudes towards AI in healthcare (median: 4, IQR: 3-4) and a desire for more AI teaching (median: 4, IQR: 4-5). However, they had limited AI knowledge (median: 2, IQR: 2-2), lack of AI courses (76.3%), and felt unprepared to use AI in their careers (median: 2, IQR: 1-3). Subgroup analyses revealed significant differences between the Global North and South (r = 0.025 to 0.185, all P < .001) and across continents (r = 0.301 to 0.531, all P < .001), with generally small effect sizes. This large-scale international survey highlights medical, dental, and veterinary students' positive perceptions of AI in healthcare, their strong desire for AI education, and the current lack of AI teaching in medical curricula worldwide. The study identifies a need for integrating AI education into medical curricula, considering regional differences in perceptions and educational needs. Not applicable (no clinical trial).

Busch F ，Hoffmann L ，Truhn D ，Ortiz-Prado E ，Makowski MR ，Bressem KK ，Adams LC ，COMFORT Consortium ... -  《BMC Medical Education》