ArticleZeitschrift fur Rheumatologie2025
[What is the potential of ChatGPT for qualified patient information? : Attempt of a structured analysis on the basis of a survey regarding complementary and alternative medicine (CAM) in rheumatology].
Article in Zeitschrift fur Rheumatologie, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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
3 citing papers in PubMed.
- What Large Language Models offer about Familial Mediterranean Fever: An Analysis of Quality, Readability, Completeness, and Accuracy.Mediterranean journal of rheumatology · 2025Article
- Article
- Generative AI/LLMs for Plain Language Medical Information for Patients, Caregivers and General Public: Opportunities, Risks and Ethics.Patient preference and adherence · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionThe chatbot ChatGPT represents a milestone in the interaction between humans and large databases that are accessible via the internet. It facilitates the answering of complex questions by enabling a communication in everyday language. Therefore, it is a potential source of information for those who are affected by rheumatic diseases. The aim of our investigation was to find out whether ChatGPT (version 3.5) is capable of giving qualified answers regarding the application of specific methods of complementary and alternative medicine (CAM) in three rheumatic diseases: rheumatoid arthritis (RA), systemic lupus erythematosus (SLE) and granulomatosis with polyangiitis (GPA). In addition, it was investigated how the answers of the chatbot were influenced by the wording of the question.
methodsThe questioning of ChatGPT was performed in three parts. Part A consisted of an open question regarding the best way of treatment of the respective disease. In part B, the questions were directed towards possible indications for the application of CAM in general in one of the three disorders. In part C, the chatbot was asked for specific recommendations regarding one of three CAM methods: homeopathy, ayurvedic medicine and herbal medicine. Questions in parts B and C were expressed in two modifications: firstly, it was asked whether the specific CAM was applicable at all in certain rheumatic diseases. The second question asked which procedure of the respective CAM method worked best in the specific disease. The validity of the answers was checked by using the ChatGPT reliability score, a Likert scale ranging from 1 (lowest validity) to 7 (highest validity).
resultsThe answers to the open questions of part A had the highest validity. In parts B and C, ChatGPT suggested a variety of CAM applications that lacked scientific evidence. The validity of the answers depended on the wording of the questions. If the question suggested the inclination to apply a certain CAM, the answers often lacked the information of missing evidence and were graded with lower score values.
conclusionThe answers of ChatGPT (version 3.5) regarding the applicability of CAM in selected rheumatic diseases are not convincingly based on scientific evidence. In addition, the wording of the questions affects the validity of the information. Currently, an uncritical application of ChatGPT as an instrument for patient information cannot be recommended.
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