Automated scoring of the autobiographical interview with natural language processing.

ABSTRACT: The autobiographical interview has been used in more than 200 studies to assess the content of autobiographical memories. In a typical experiment, participants recall memories, which are then scored manually for internal details (episodic details from the central event) and external details (largely non-episodic details). Scoring these narratives requires a significant amount of time. As a result, large studies with this procedure are often impractical, and even conducting small studies is time-consuming. To reduce scoring burden and enable larger studies, we developed an approach to automatically score responses with natural language processing. We fine-tuned an existing language model (distilBERT) to identify the amount of internal and external content in each sentence. These predictions

SUBMITTER: van Genugten RDI 

PROVIDER: S-EPMC10990986 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature