17TH Medical Undergraduates' Annual Scientific Research Meeting (1)

Background and aims: Artificial intelligence (AI) chatbots have benefited students in many ways, but several issues have arisen with regard to ethical aspects and students' critical thinking skills.This study aims to provide insights into the prevalence and frequency of AI Chatbot usage among undergraduate students of the Faculty of Medicine, Universiti Kebangsaan Malaysia (FPER UKM), and to explore the factors contributing to AI Chatbot use and dependency. Materials and methods: This study employed a cross-sectional design. An online survey involvingA study involving 300 undergraduate students from FPER UKM, comprising students from medical, nursing, and emergency medicine courses, was conducted using questionnaires adapted and screened from the Bergen Facebook Addiction Scale (BFAS) and other relevant literature.Data analysis of the collected responses was then conducted using bivariable correlation and multivariable regression in SPSS version 29.Results: Our study included 300 students from FPER UKM, primarily consisting of Malaysian students, with only 4 non-Malaysian students.The prevalence of AI chatbot usage among all undergraduate courses is 100%.The factors with the highest impact on the AI dependency score were weekly usage of more than four hours (p < 0.001, β = 0.301) and academic stress (p = 0.001, β = 0.188).The final multiple regression model significantly predicted dependency on AI chatbot (p < 0.001) with R2 of 0.182.Most respondents used AI tools for one to three hours per week, primarily for studying or revision.Conclusion: All undergraduate students have used an AI chatbot previously, with its main benefit being for studying and revision.The dependency on AI chatbots is significantly associated with the duration of AI chatbot usage and the level of academic stress.Further studies are warranted to classify dependency on AI chatbots and explore other predictive factors that can contribute to over-reliance on AI chatbots.