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Background: During the coronavirus disease of 2019 (COVID-19) pandemic, in-person interviews for the recruitment of family medicine residents shifted to online (virtual) interviews. The purpose of this study was twofold: (1) to gather the ideas about virtual interviews of family medicine applicants (interviewees), and faculty and staff who interviewed these applicants (interviewers), and (2) to describe interviewers' and interviewees' opinions of use of emerging technologies such as artificial intelligence (AI) and virtual reality (VR) in the recruitment process as well as during clinical practice. Methods: This was a cross-sectional survey study. Participants were both interviewers and candidates who applied to the McGill University Family Medicine Residency Program for the 2020–2021 and 2021–2022 cycles. Results: The study population was constituted by N = 132 applicants and N = 60 interviewers. The response rate was 91.7% (55/60) for interviewers and 43.2% (57/132) for interviewees. Both interviewers (43.7%) and interviewees (68.5%) were satisfied with connecting through virtual interviews. Interviewers (43.75%) and interviewees (55.5%) would prefer for both options to be available. Both interviewers (50%) and interviewees (72%) were interested in emerging technologies. Almost all interviewees (95.8%) were interested in learning about AI and VR and its application in clinical practice with the majority (60.8%) agreeing that it should be taught within medical training. Conclusion: Although experience of virtual interviewing during the COVID-19 pandemic has been positive for both interviewees and interviewers, the findings of this study suggest that it will be unlikely that virtual interviews completely replace in-person interviews for selecting candidates for family medicine residency programs in the long term as participants value aspects of in-person interviews and would want a choice in format. Since incoming family medicine physicians seem to be eager to learn and utilize emerging technologies such as AI and VR, educators and institutions should consider family physicians' needs due to the changing technological landscape in family medicine education. [ABSTRACT FROM AUTHOR]

Background: The successful integration of artificial intelligence (AI) into clinical practice is contingent upon physicians' comprehension of AI principles and its applications. Therefore, it is essential for medical education curricula to incorporate AI topics and concepts, providing future physicians with the foundational knowledge and skills needed. However, there is a knowledge gap in the current understanding and availability of structured AI curriculum frameworks tailored for medical education, which serve as vital guides for instructing and facilitating the learning process., Objective: The overall aim of this study is to synthesize knowledge from the literature on curriculum frameworks and current educational programs that focus on the teaching and learning of AI for medical students, residents, and practicing physicians., Methods: We followed a validated framework and the Joanna Briggs Institute methodological guidance for scoping reviews. An information specialist performed a comprehensive search from 2000 to May 2023 in the following bibliographic databases: MEDLINE (Ovid), Embase (Ovid), CENTRAL (Cochrane Library), CINAHL (EBSCOhost), and Scopus as well as the gray literature. Papers were limited to English and French languages. This review included papers that describe curriculum frameworks for teaching and learning AI in medicine, irrespective of country. All types of papers and study designs were included, except conference abstracts and protocols. Two reviewers independently screened the titles and abstracts, read the full texts, and extracted data using a validated data extraction form. Disagreements were resolved by consensus, and if this was not possible, the opinion of a third reviewer was sought. We adhered to the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist for reporting the results., Results: Of the 5104 papers screened, 21 papers relevant to our eligibility criteria were identified. In total, 90% (19/21) of the papers altogether described 30 current or previously offered educational programs, and 10% (2/21) of the papers described elements of a curriculum framework. One framework describes a general approach to integrating AI curricula throughout the medical learning continuum and another describes a core curriculum for AI in ophthalmology. No papers described a theory, pedagogy, or framework that guided the educational programs., Conclusions: This review synthesizes recent advancements in AI curriculum frameworks and educational programs within the domain of medical education. To build on this foundation, future researchers are encouraged to engage in a multidisciplinary approach to curriculum redesign. In addition, it is encouraged to initiate dialogues on the integration of AI into medical curriculum planning and to investigate the development, deployment, and appraisal of these innovative educational programs., International Registered Report Identifier (irrid): RR2-10.11124/JBIES-22-00374., (©Raymond Tolentino, Ashkan Baradaran, Genevieve Gore, Pierre Pluye, Samira Abbasgholizadeh-Rahimi. Originally published in JMIR Medical Education (https://mededu.jmir.org), 18.07.2024.)