The Process of Content Analysis for Narrative Medicine: Methodological Exploration and AI Applications

This study investigates the application of AI in narrative medicine through content analysis, demonstrating how AI aids in identifying themes, emotions, key concepts, and structural patterns within medical narratives. A multi-stage, multi-tier analysis framework was employed, integrating natural language processing (NLP) for text preprocessing, including part-of-speech tagging. An iterative process of bilateral adjustments between human expertise and AI ensured methodological rigor, enhancing inter-rater reliability through noise removal. AI-assisted keyword extraction and semantic network analysis uncovered hidden patterns in patient-physician interactions. The findings highlight AI’s potential to advance qualitative research in narrative medicine while emphasizing the necessity of expert annotation for analytical precision.