From Traits to Configurations: An Artificial Intelligence Supported Methodology for Mapping Psychological Configurations Across Life Narratives

Background: Life narratives contain rich information about how psychological characteristics are expressed across different stages of a person's life. Translating this material into systematic psychological representations that can be compared within individuals across biographical stages remains a methodological challenge. Objective: This study examined an artificial intelligence-supported method for identifying psychological configurations in life narratives and comparing them across different stages within the same individual. Methods: We analyzed in-depth interviews with 13 former members of criminal organizations who subsequently became state witnesses. Each narrative was divided into 10 biographical stages, which were coded independently by a large language model using a predefined theoretical framework comprising the 25 personality facets of the Personality Inventory for the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (PID-5). The model was not given access to configurations generated from other stages. Configurations were compared within individuals across the peak of their criminal careers, subsequent crises, and the stage of crossing lines of loyalty. Results: Overlap between the peak-career configuration and configurations from earlier crisis stages varied considerably across participants. In contrast, at the stage of crossing lines of loyalty, all 13 participants showed low overlap with their peak-career configuration (Jaccard similarity coefficient <=0.25). Configurational composition also differed across stages. Grandiosity and Risk Taking were more frequently represented at the peak of the criminal career, whereas Anxiousness, Depressivity, and Suspiciousness were more frequently represented at the crossing stage. Conclusion: The findings demonstrate that a large language model operating within a predefined psychological framework can systematically code life narratives and generate multidimensional configurations for comparison across biographical stages. This approach extends artificial intelligence-supported psychological analysis beyond individual characteristics assessed at a single point in time to configurations represented across a biographical sequence. The findings reflect psychological characteristics as represented and coded in the narratives rather than directly measured changes in personality, providing a methodological basis for studying intraindividual variation in complex biographical processes.