ArticleOsteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA2025
Improving readability in AI-generated medical information on fragility fractures: the role of prompt wording on ChatGPT's responses.
Article in Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed.
- Accuracy, readability, and content coverage of AI-generated responses to questions on functional appliances.BMC oral health · 2026Article
- Optimizing Large Language Model Responses to Medical Queries: a Cross-sectional Study On the Effective Use of Chatgpt for Cancer-related Questions.Journal of medical systems · 2026Article
- ChatGPT-5.4 in health education: inter-generation stability and persistent readability challenges.Frontiers in public health · 2026Article
- Evaluating large language models for ADHD education: A comparative study of ChatGPT 5, DeepSeek V3, and Grok 4.PloS one · 2026Article
- AI-generated explanations in kidney transplantation: accuracy vs. readability and implications for patient education.Frontiers in artificial intelligence · 2026Article
- Evaluating the Performance of DeepSeek-R1 as a Patient Education Tool.Journal of medical systems · 2025Article
- Evaluating the readability and quality of AI-generated scoliosis education materials: a comparative analysis of five language models.Scientific reports · 2025Article
- Assessing the accuracy and readability of ChatGPT 4.0's original and simplified responses to common patient questions regarding periacetabular osteotomy.Journal of experimental orthopaedics · 2025Article
- Evaluation of large language model-generated medical information on idiopathic pulmonary fibrosis.Frontiers in artificial intelligence · 2025Article
- Comparative performance of large language models for patient-initiated ophthalmology consultations.Frontiers in public health · 2025Article
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Abstract
Understanding how the questions used when interacting with chatbots impact the readability of the generated text is essential for effective health communication. Using descriptive queries instead of just keywords during interaction with ChatGPT results in more readable and understandable answers about fragility fractures. PURPOSE: Large language models like ChatGPT can enhance patients' understanding of medical information, making health decisions more accessible. Complex terms, such as "fragility fracture," can confuse patients, so presenting its medical content in plain language is crucial. This study explored whether conversational prompts improve readability and understanding compared to keyword-based prompts when generating patient-centered health information on fragility fractures.
methodsThe 32 most frequently searched keywords related to "fragility fracture" and "osteoporotic fracture" were identified using Google Trends. From this set, 24 keywords were selected based on relevance and entered sequentially into ChatGPT. Each keyword was tested with two prompt types: (1) plain language with keywords embedded and (2) keywords alone. The readability and comprehensibility of the AI-generated responses were assessed using the Flesch-Kincaid reading ease (FKRE) and Flesch-Kincaid grade level (FKGL), respectively. The scores of the responses were compared using the Mann-Whitney U test.
resultsThe FKRE scores indicated significantly higher readability with plain language prompts (median 34.35) compared to keyword-only prompts (median 23.60). Similarly, the FKGL indicated a lower grade level for plain language prompts (median 12.05) versus keyword-only (median 14.50), with both differences achieving statistical significance.
conclusionOur findings suggest that using conversational prompts can enhance the readability of AI-generated medical information on fragility fractures. Clinicians and content creators should consider this approach when using AI for patient education to optimize comprehension.
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