Artificial Intelligence-assisted Exploration of Imposter Phenomenon in Medical Students of Eastern India

Abstract Background: Imposter phenomenon (IP) is a psychological phenomenon in which an individual, even when their abilities are demonstrated to be sufficient, continues to doubt them. Medical students are especially prone to IP. This study was conducted to explore the role of psychological and academic backgrounds in the development of imposter phenomenon among the medical students of a medical college in eastern India. Methodology: An explanatory sequential mixed methods study was conducted over 1 month, beginning with l quantitative study followed by an artificial intelligence-based qualitative interview. Clance IP scale was used to measure IP, and related factors were determined using a self-administered questionnaire. An in-depth interview (IDI) guide was prepared using the help of results obtained from 130 study participants. An interview chatbot was designed with the help of the IDI guide. The chatbot interviewed 6 UG students about the role of academic pressure, school performances, etc., on the development of IP. Results: Overall 91% of the study subjects were found to be suffering from IP. Female, middle-class socio-economic status, good school performance, and 2 nd semester students were found to be more prone to IP. After a qualitative study, 6 themes were found to be prominent for the development of IP. Pressure to be perfect, lack of coping strategies, dilemma between memorization and concept building, language barrier, peer comparison, and examination pattern were some recurring issues stated by the participants. Conclusion: The high prevalence of impostor syndrome among medical students needs to be solved addressing the academic and peer pressure contributing to it.