Wagner, GeritGeritWagner0000-0003-3926-7717Paré, GuyGuyParéRaymond, LouisLouisRaymondCastonguay, AlexandreAlexandreCastonguay2023-05-092023-05-092023978-0-9981331-6-4https://fis.uni-bamberg.de/handle/uniba/59354Artificial intelligence (AI) drives transformation across medical specialities, requiring current and future generations of physicians to navigate ever-changing digital environments. In this context, prospective physicians will play a key role in adopting and applying AI-based health technologies, underlining the importance of understanding their knowledge, attitudes, and intentions toward AI. To dissociate corresponding profiles, we adopted a configurational perspective and conducted a two-stage survey study of 184 (t_0) and 138 (t_1) medical students at a Canadian medical school. Our principal findings corroborate the existence of distinct clusters in respondents’ AI profiles. We refer to these profiles as the AI unfamiliar, the AI educated, and the AI positive, showing that each profile is associated with different intentions towards future AI use. These exploratory insights on the variety of AI profiles in prospective physicians underline the need for targeted and adaptive measures of education and outreach.engIT AdoptionDiffusionEvaluation in Healthcaremedical studentsartificial intelligenceintentionsattitudesknowledge.004150conferenceobjecthttps://hdl.handle.net/10125/103000