ArticleJMIR formative research2025
Evaluating ChatGPT's Utility in Biologic Therapy for Systemic Lupus Erythematosus: Comparative Study of ChatGPT and Google Web Search.
Article in JMIR formative research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Investigating the Readability and Quality of AI Systems to Trending Questions About Food Poisoning.Journal of food science · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Systemic lupus erythematosus (SLE) is a life-threatening, multisystem autoimmune disease. Biologic therapy is a promising treatment for SLE. However, public understanding of this therapy is still insufficient, and the quality of related information on the internet varies, which affects patients' acceptance of this treatment. The effectiveness of artificial intelligence technologies, such as ChatGPT (OpenAI), in knowledge dissemination within the health care field has attracted significant attention. Research on ChatGPT's utility in answering questions regarding biologic therapy for SLE could promote the dissemination of this treatment. Objective: This study aimed to evaluate ChatGPT's utility as a tool for users to obtain health information about biologic therapy for SLE. Methods: This study extracted 20 common questions related to biologic therapy for SLE, their corresponding answers, and the sources of these answers from both Google Web Search and ChatGPT-4o (OpenAI). Then, based on Rothwell's classification, the questions were categorized into 3 main types: fact, policy, and value. The sources of the answers were classified into 5 categories: commercial, academic, medical practice, government, and social media. The accuracy and completeness of the answers were assessed using Likert scales. The readability of the answers was evaluated using the Flesch Reading Ease and Flesch-Kincaid Grade Level (FKGL) scores. Results: The study found that, in terms of question types, ChatGPT-4o had the highest proportion of fact questions (10/20), followed by policy (7/20) and value (3/20). Google Web Search had the highest proportion of fact questions (12/20), followed by value (5/20) and policy (3/20). In terms of website sources, ChatGPT-4o's answers were sourced from 48 sources, with the majority coming from academic sources (29/48). Google Web Search provided answers from 20 sources, with an even distribution across all 5 categories. For accuracy, ChatGPT-4o's mean score of 5.83 (SD 0.49) was higher than that of Google Web Search (mean 4.75, SD 0.94), with a mean difference of 1.08 (95% CI 0.61-1.54). For completeness, ChatGPT-4o's mean score of 2.88 (SD 0.32) was higher than that of Google Web Search (mean 1.68, SD 0.69), with a mean difference of 1.2 (95% CI 0.96-1.44). For readability, the Flesch Reading Ease and Flesch-Kincaid Grade Level scores for ChatGPT-4o and Google Web Search were 11.7 and 14.9, and 16.2 and 20, respectively, indicating that both texts were of high reading difficulty, requiring readers to have a college graduate-level reading proficiency. When asking ChatGPT to respond at a sixth-grade level, the readability of the answers significantly improved. Conclusions: ChatGPT's answers are characterized by accuracy, rigor, comprehensiveness, and professional supporting materials, and demonstrate humanistic care. However, the readability of the provided text is low, requiring users to have a college education background. Given the study's limitations in question scope, comparison dimensions, research perspectives, and language types, further in-depth comparative research is recommended.
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.