ArticleCureus2025
The Reliability Gap: How Traditional Search Engines Outperform Artificial Intelligence (AI) Chatbots in Rosacea Public Health Information Quality.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Comparative Evaluation of ChatGPT-5.2, Claude Sonnet 4.5, and DeepSeek-V3.2 for Rosacea-Related Information: Accuracy, Reliability, Readability, and Reference Hallucinations.Diagnostics (Basel, Switzerland) · 2026Article
- Assessing Quality, Readability, and Transparency of Online and AI-Generated Information on Type 2 Diabetes Mellitus: Cross-Sectional Exploratory Study.JMIR diabetes · 2026Article
- Evaluating the quality, reliability and readability of digital and artificial intelligence resources for adults with cancer who have significant caregiving responsibilities for children.PLOS digital health · 2026Article
- AI chatbots for health information seeking among Chinese patients with precancerous ENT lesions: a descriptive qualitative study.BMJ open · 2026Article
- Can Artificial Intelligence Support Patient Education in Scabies? A Comparative Analysis of Large Language Model Responses.Healthcare (Basel, Switzerland) · 2026Article
- Generative AI vs web search for patient education: a comparative evaluation of OSA information quality.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 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
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe internet has become a primary source of health information for the public, with important implications for patient decision-making and public health outcomes. However, the quality and readability of this content vary widely. With the rise of generative artificial intelligence (AI) tools such as ChatGPT and Gemini, new challenges and opportunities have emerged in how patients access and interpret medical information.
objectiveTo evaluate and compare the quality, credibility, and readability of consumer health information provided by traditional search engines (Google, Bing) and generative AI platforms (ChatGPT, Gemini) using three validated instruments: DISCERN, JAMA Benchmark Criteria, and Flesch-Kincaid Readability Metrics. Methods: Twenty health-related webpages from each platform were collected using a standardized query across Google, Bing, Gemini, and ChatGPT. Each source was assessed independently by two reviewers using the DISCERN instrument and the adapted JAMA benchmark criteria. Readability was evaluated using the Flesch Reading Ease and Grade Level scores. One-way ANOVA with Bonferroni correction was used to compare platform performance, and Cohen's Kappa measured inter-rater reliability. Results: Google achieved the highest mean scores for both quality and credibility (DISCERN: 3.33 ± 0.53; JAMA: 3.70 ± 0.44), followed by Bing, Gemini, and ChatGPT. ChatGPT received the lowest scores across all quality measures. Readability analysis revealed no statistically significant differences between platforms; however, all content exceeded recommended reading levels for public health information. Cohen's Kappa indicated strong inter-rater agreement across DISCERN items. Conclusion: Google remains the most reliable source of high-quality, readable health information among the evaluated platforms. Generative AI tools such as ChatGPT and Gemini, while increasingly popular, exhibited significant limitations in accuracy, transparency, and complexity. These findings highlight the need for improved oversight, transparency, and user education regarding AI-generated health content.
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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.