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Artificial intelligence in patient education: evaluating large language models for understanding rheumatology literature
1
Zitationen
7
Autoren
2025
Jahr
Abstract
Background: Inadequate health literacy hinders positive health outcomes, yet medical literature often exceeds the general population's comprehension level. While health authorities recommend patient materials be at a sixth-grade reading level, scientific articles typically require college-level proficiency. Large language models (LLMs) like ChatGPT show potential for simplifying complex text, possibly bridging this gap. Objective: This study evaluated the effectiveness of ChatGPT 4.0 in enhancing the readability of peer-reviewed rheumatology articles for layperson comprehension. Methods: -tests. Results: = 0.047). Conclusions: ChatGPT effectively lowered the reading complexity of specialized rheumatology literature, making it more accessible than the original publications. However, the achieved 10th-grade reading level still exceeds the recommended sixth-grade level for patient education materials. While LLMs are a promising tool, their output may require further refinement or expert review to meet optimal health literacy standards and ensure equitable patient understanding in rheumatology.
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