Exploring large language models for summarizing and interpreting an online brain tumor support forum.

ABSTRACT:

Objective

This study explored the capabilities of large language models (LLMs) GPT-3.5, GPT-4, and Llama 3 to summarize qualitative data from an online brain tumor support forum, assessing the differences between these methods and traditional thematic analysis.

Methods

Eight posts and responses were collected in September 2024 from the American Brain Tumor Association Brain Tumor Support Group, using the passive/unobtrusive method. The data were analyzed using two methods: (1) traditional thematic coding with Dedoose software and (2) summarization and interpretation using LLMs. Prompts guided the LLMs in generating summaries and identifying key challenges, with results evaluated using the metrics BLEU, ROUGE-1, ROUGE-2, ROUGE-L, METEOR, and BERTScore (f1). Flesch-Kincaid gra

SUBMITTER: Muasher-Kerwin C 

PROVIDER: S-EPMC12034948 | biostudies-literature | 2025 Jan-Dec

REPOSITORIES: biostudies-literature