Leveraging Large Language Models to Improve the Readability of German Online Medical Texts: Evaluation Study.

ABSTRACT:

Background

Patient education materials (PEMs) found online are often written at a complexity level too high for the average reader, which can hinder understanding and informed decision-making. Large language models (LLMs) may offer a solution by simplifying complex medical texts. To date, little is known about how well LLMs can handle simplification tasks for German-language PEMs.

Objective

The study aims to investigate whether LLMs can increase the readability of German online medical texts to a recommended level.

Methods

A sample of 60 German texts originating from online medical resources was compiled. To improve the readability of these texts, four LLMs were selected and used for text simplification: ChatGPT-3.5, ChatGPT-4o, Microsoft Copilot, and Le Chat. Next, r

SUBMITTER: Miftaroski A 

PROVIDER: S-EPMC12829587 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature