ArticleArchives of osteoporosis2024
Artificial intelligence insights into osteoporosis: assessing ChatGPT's information quality and readability.
Article in Archives of osteoporosis, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 20 citations in OpenAlex.
- Evaluating the clinical safety of large language models in oral cancer-related patient communication: a repeated-prompt observational study.BMC oral health · 2026Observational
- Article
- 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
- Accuracy and Reliability of AI Models in Emergency Myocardial Infarction Education.Emergency medicine international · 2026Article
- Large Language model (LLM) in temporomandibular disorder education: a comparative study.BMC oral health · 2025Article
- What do the current popular artificial intelligence chatbots offer us regarding patient information? Comparison of responses from the ten most popular chatbots about bladder cancer.Journal of cancer survivorship : research and practice · 2025Article
- Evaluation of the Quality and Readability of ChatGPT Responses to Toothache Queries: A Study Based on Google Trends.Cureus · 2025Article
- Article
- Observational
- Multiple large language models versus clinical guidelines for postmenopausal osteoporosis: a comparative study of ChatGPT-3.5, ChatGPT-4.0, ChatGPT-4o, Google Gemini, Google Gemini Advanced, and Microsoft Copilot.Archives of osteoporosis · 2025Article
- What Large Language Models offer about Familial Mediterranean Fever: An Analysis of Quality, Readability, Completeness, and Accuracy.Mediterranean journal of rheumatology · 2025Article
- Improving readability in AI-generated medical information on fragility fractures: the role of prompt wording on ChatGPT's responses.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2025Article
- Artificial intelligence insights into osteoporosis: comment.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2025Article
- Author response to: OSIN-D-24-00381, artificial intelligence insights into osteoporosis.Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2025Article
- How Useful are Current Chatbots Regarding Urology Patient Information? Comparison of the Ten Most Popular Chatbots' Responses About Female Urinary Incontinence.Journal of medical systems · 2024Article
- Assessment of readability, reliability, and quality of ChatGPT®, BARD®, Gemini®, Copilot®, Perplexity® responses on palliative care.Medicine · 2024Observational
- Exploring the Role of ChatGPT-4, BingAI, and Gemini as Virtual Consultants to Educate Families about Retinopathy of Prematurity.Children (Basel, Switzerland) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Accessible, accurate information, and readability play crucial role in empowering individuals managing osteoporosis. This study showed that the responses generated by ChatGPT regarding osteoporosis had serious problems with quality and were at a level of complexity that that necessitates an educational background of approximately 17 years. PURPOSE: The use of artificial intelligence (AI) applications as a source of information in the field of health is increasing. Readable and accurate information plays a critical role in empowering patients to make decisions about their disease. The aim was to examine the quality and readability of responses provided by ChatGPT, an AI chatbot, to commonly asked questions regarding osteoporosis, representing a major public health problem.
methods"Osteoporosis," "female osteoporosis," and "male osteoporosis" were identified by using Google trends for the 25 most frequently searched keywords on Google. A selected set of 38 keywords was sequentially inputted into the chat interface of the ChatGPT. The responses were evaluated with tools of the Ensuring Quality Information for Patients (EQIP), the Flesch-Kincaid Grade Level (FKGL), and the Flesch-Kincaid Reading Ease (FKRE).
resultsThe EQIP score of the texts ranged from a minimum of 36.36 to a maximum of 61.76 with a mean value of 48.71 as having "serious problems with quality." The FKRE scores spanned from 13.71 to 56.06 with a mean value of 28.71 and the FKGL varied between 8.48 and 17.63, with a mean value of 13.25. There were no statistically significant correlations between the EQIP score and the FKGL or FKRE scores.
conclusionsAlthough ChatGPT is easily accessible for patients to obtain information about osteoporosis, its current quality and readability fall short of meeting comprehensive healthcare standards.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.