Unveiling the Artificial Intelligence (AI) Shift: Attitudes Toward and Utilization of AI Models Among Undergraduate...

Artificial intelligence (AI) tools like ChatGPT (OpenAI, San Francisco, USA) are increasingly influencing medical education, yet their use among undergraduate students in Western India remains underexplored. This study aimed to assess students' acceptance, usage patterns, and key factors influencing AI adoption to support effective curriculum integration.

This cross-sectional, questionnaire-based study evaluated attitudes toward and use of AI among undergraduate medical students from first year to final year. A structured 37-item English questionnaire was developed via Google Forms (Google LLC, Mountain View, USA) and distributed online using electronic channels, with informed consent obtained. Data were managed in Microsoft Excel 2013 (Microsoft Corp., Redmond, USA) and analyzed using GraphPad Prism version 10.6 (GraphPad Software, Boston, USA; www.graphpad.com), yielding key insights into perceptions and use of AI.

This study was conducted among 791 medical students, with a mean age of 19.92 ± 1.64 years. Of these, 701 (88.62%) participants engaged with AI, relying predominantly on social media (425 (53.72%)) and faculty lectures (199 (25.15%)) for information. Moreover, 784 (99.11%) participants showed high AI awareness. Multivariable logistic regression demonstrated that AI use was strongly associated with behavior (odds ratio (OR)=356.9; 95% confidence interval (CI): 77.83-6329), perceived usefulness (OR=18.5; 95% CI: 40.68-327), and inversely with perceived risk (OR=0.06; 95% CI: 0.003-0.31). Students more than 20 years of age, male participants, and consistent AI users showed significantly higher usefulness and strong positive attitudes. Notably, first-year students reported a higher perception of risk compared to their peers, underscoring significant variations in AI adoption and perception.

The use of AI models among Western Indian undergraduate medical students and their attitudes were investigated in this study. Although there was variation in students' comprehension of AI-related concepts, the majority of students reported being aware of and having previously used AI tools, mostly through social media platforms. The use of AI and opinions of AI models were correlated with age, gender, academic year, perceived utility, and behavior. The results demonstrate the potential value of responsible and ethical AI guidance in medical education and may offer initial institutional-level insights for future multicentric research and curriculum development.