Cureus, 2026/05, 18(5):e109675. doi: 10.7759/cureus.109675, type of study: cross sectional study

Free full text   (https://www.cureus.com/articles/494677-knowledge-utilization-and-perceptions-of-artificial-intelligence-in-medical-education-among-preclinical-osteopathic-medical-students-and-faculty-a-cross-sectional-study#!/)

Keywords:

AI [1994]
artificial intelligence [15]
cross sectional study [894]
faculty [42]
knowledge [67]
medical students [694]
osteopathic medicine [2109]
perception [146]
USA [1752]
utilization [28]

Abstract:

Introduction Artificial intelligence (AI), including generative large language models such as ChatGPT and Microsoft Copilot, is increasingly incorporated into medical education. However, empirical data describing AI knowledge, utilization, and perceptions within osteopathic medical education remain limited. This study aimed to assess AI literacy, usage patterns, perceived benefits and concerns, and future readiness among preclinical osteopathic medical students and faculty. Methods A cross-sectional, anonymous, web-based survey was administered to first- and second-year osteopathic medical students and preclinical faculty at Burrell College of Osteopathic Medicine across two campuses. Survey items assessed demographics, AI knowledge and training, educational and scholarly AI use, perceptions, attitudes toward verification and policy, and future perspectives. Descriptive statistics summarized responses, and chi-square tests compared faculty and student groups. Results Ninety‑four responses were received (26.0% response rate), with 58 complete responses (20 faculty and 38 students) included in analyses. Formal AI training was uncommon overall, but faculty were significantly more likely than students to have received any formal AI training (35.0% vs. 2.6%; p = 0.003). Students demonstrated significantly higher use of AI for studying or lecture preparation (76.3% vs. 45.0%; p = 0.036), generating exam questions (63.2% vs. 20.0%; p = 0.002), reviewing exam questions (71.1% vs. 10.0%; p < 0.001), completing written assignments (36.8% vs. 0%; p = 0.005), and writing patient notes (92.1% vs. 5.0%; p < 0.001). Students were also more likely to use AI‑driven digital anatomy platforms (81.6% vs. 35.0%; p = 0.001). Students more frequently identified treatment planning as an area that would benefit from AI integration (31.6% vs. 5.0%; p = 0.048). Conclusions This study provides preliminary institutional insights into AI knowledge, utilization, and perceptions among preclinical osteopathic medical students and faculty at a single osteopathic medical school. Respondents demonstrated moderate baseline AI knowledge and strong interest in future integration, with students showing substantially higher use of AI tools than faculty. These early patterns underscore a need for structured AI literacy education, targeted faculty development, and the establishment of institutional governance to guide responsible and pedagogically sound AI adoption within this educational context.