Qianfeng Lu, Elena Link, Eva Baumann, Peter J Schulz
Linking patient-centered communication with cancer information avoidance: The mediating roles of patient trust and literacy
Patient education and counseling
artificial intelligence ai potential revolutionize way medicine learned taught practiced medical education must prepare learners inevitable changes academic medicine however slow embrace recent ai advances since launch november 2022 chatgpt emerged fast userfriendly large language model assist health care professionals medical educators students trainees patients many studies focus technologys capabilities potential risks gap studying perspective end users aim study gauge experiences perspectives graduating medical students chatgpt ai training future careers crosssectional webbased survey recently graduated medical students conducted international academic medical center may 5 2023 june 13 2023 descriptive statistics used tabulate variable frequencies 325 applicants residency programs 265 completed survey 815 response rate vast majority respondents denied using chatgpt medical school 204 n54 using help complete written assessments 94 using technology clinical work n25 students planned use residency primarily exploring new medical topics research n168 634 exam preparation n151 57 male students significantly likely believe ai improve diagnostic accuracy n47 517 vs n69 397 p001 reduce medical error n53 582 vs n71 408 p002 improve patient care n60 659 vs n95 546 p007 previous experience ai significantly associated positive ai perception terms improving patient care decreasing medical errors misdiagnoses increasing accuracy diagnoses p001 p001 p008 respectively surveyed medical students minimal formal informal experience ai tools limited perceptions potential uses ai health care overall positive views chatgpt ai optimistic future ai medical education health care structured curricula formal policies guidelines needed adequately prepare medical learners forthcoming integration ai medicine