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Medical students’ perceptions of professional mission in an AI-driven healthcare future: a text mining analysis of reflective essays in Japan
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2025
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Abstract
Objective: As artificial intelligence (AI) technologies advance rapidly, their integration into healthcare is transforming the clinical practice landscape. This study aimed to evaluate how second-year medical students perceive their professional mission in an AI-integrated medical future, through a structured essay task, using text-mining analysis to identify emerging themes and attitudes. Methods: A total of 105 second-year medical students at Kagawa university in Japan completed an essay titled "What is your mission in the AI-driven medical world?". Responses were analyzed using KH Coder for frequency analysis, multidimensional scaling, and co-occurrence network mapping. Participants provided verbal informed consent and student anonymity was ensured. Results: The most frequently used terms were medical, consider, think, doctor, AI, human, and patient. Three thematic clusters emerged: (1) career design, (2) AI and medicine, and (3) AI and human. Co-occurrence analysis revealed strong associations between "medical" and both "consider" and "patient", while "patient" was linked to both "AI" and "human", indicating thoughtful reflection on technology's impact on patient care. Conclusion: Second-year medical students in Japan demonstrated critical engagement with the concept of mission formation in the context of AI in healthcare. Their essays reflected a balance between optimism for technological advancement and concern for preserving human-centered care. These findings highlight the importance of implementing systematic career education and future-oriented thinking that is aligned with the characteristics of Generation Z learners.
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