Large Language Models vs. Professional Resources for Post-Treatment Quality-of-Life Questions in Head and Neck Cancer: A Cross-Sectional Comparison.

ABSTRACT:

Background

Recently, patients have been using large language models (LLMs) such as ChatGPT, Gemini, and Claude to address their concerns. However, it remains unclear whether the readability, understandability, actionability, and empathy meet the standard guidelines. In this study, we aim to address these concerns and compare the outcomes of the LLMS to those of professional resources.

Methods

We conducted a comparative cross-sectional study by following the relevant items of the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist for cross-sectional studies and using 14 patient-style questions. These questions were collected from the professional platforms to represent each domain. We derived the 14 domains from validated quality-of-life i

SUBMITTER: Alabdalhussein A 

PROVIDER: S-EPMC12731422 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature