Department of Diagnostic Imaging (M.K.A., G.L.B., M.T.S., K.O., J.J.C.), Rhode Island Hospital, Warren Alpert School of Medicine of Brown University, 593 Eddy Street, Providence, RI 02903; Radiology Human Factors Laboratory, Department of Diagnostic Imaging (M.K.A., G.L.B.), Rhode Island Hospital, Warren Alpert School of Medicine of Brown University, Providence, Rhode Island.
Department of Diagnostic Imaging (M.K.A., G.L.B., M.T.S., K.O., J.J.C.), Rhode Island Hospital, Warren Alpert School of Medicine of Brown University, 593 Eddy Street, Providence, RI 02903; Radiology Human Factors Laboratory, Department of Diagnostic Imaging (M.K.A., G.L.B.), Rhode Island Hospital, Warren Alpert School of Medicine of Brown University, Providence, Rhode Island.
Acad Radiol. 2023 Jun;30(6):1181-1188. doi: 10.1016/j.acra.2022.07.003. Epub 2022 Sep 2.
We sought to determine the perceived impact of artificial intelligence (AI) and other emerging technologies (ET) on various specialties by medical students in both 2017 and 2021 and how this might affect their residency selections.
We conducted a brief, anonymous survey of all medical students at a single institution in 2017 and 2021. Survey questions evaluated (1) incentives motivating residency selection and career path, (2) degree of interest in each specialty, (3) perceived effect that ET will have on job prospects for each specialty, and (4) those specialties that students would not consider because of concerns regarding ET.
A total of 72% (384/532) and 54% (321/598) of medical students participated in the survey in 2017 and 2021, respectively, and results were largely stable. Students perceived ET would reduce job prospects for pathology, diagnostic radiology, and anesthesiology, and enhance prospects for all other specialties (p < 0.01) except dermatology. For both surveys, 23% of students would NOT consider diagnostic radiology because ET would make it obsolete, higher than all other specialties (p < 0.01). Regarding the one student class that was surveyed twice, 50% felt ET would reduce job prospects for radiology in 2017, increasing to 71% in 2021 (p < 0.01), and similar percentages-20% in 2017 and 23% in 2021-said they explicitly would not consider radiology because of concerns levied by ET.
Current perceptions of ET likely affect residency selection for a large proportion of medical students and may impact the future of various specialties, particularly diagnostic radiology.
我们旨在通过对 2017 年和 2021 年的医学生进行调查，了解他们对人工智能（AI）和其他新兴技术（ET）对不同专业的感知影响，以及这将如何影响他们的住院医师选择。
我们对一所机构的所有医学生进行了一次简短的匿名调查，调查问题评估了（1）激励住院医师选择和职业道路的因素，（2）对每个专业的兴趣程度，（3）对 ET 将对每个专业的就业前景产生的影响的看法，以及（4）学生因担心 ET 而不会考虑的专业。
共有 72%（384/532）和 54%（321/598）的医学生分别在 2017 年和 2021 年参与了调查，结果基本稳定。学生们认为 ET 将降低病理学、诊断放射学和麻醉学的就业前景，并提高所有其他专业（p<0.01）的前景，除了皮肤科。对于两次调查，都有 23%的学生不会考虑诊断放射科，因为 ET 会使其过时，高于所有其他专业（p<0.01）。对于两次调查都被调查的一个学生班级，50%的人认为 ET 将在 2017 年降低放射科的就业前景，到 2021 年增加到 71%（p<0.01），同样百分比-2017 年的 20%和 2021 年的 23%-表示他们明确不会考虑放射科，因为担心 ET 带来的影响。
当前对 ET 的看法可能会影响很大一部分医学生的住院医师选择，并可能影响未来的各种专业，特别是诊断放射学。
