ArticleJournal of obesity2026
Patient Education in Bariatric Surgery: Can Artificial Intelligence-Based Chatbots Bridge the Knowledge Gap?
Article in Journal of obesity, 2026. 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
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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.
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Who cites it
1 citing paper in PubMed.
- Patient Education in Bariatric Surgery: Can Artificial Intelligence-Based Chatbots Bridge the Knowledge Gap?Journal of obesity · 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
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The global obesity epidemic challenges health systems, driving people to seek metabolic and bariatric surgery (MBS), especially laparoscopic sleeve gastrectomy (LSG). Many MBS centers have limited resources for patient education, creating knowledge gaps that lead patients to search online. AI chatbots, such as ChatGPT, can provide reliable medical information, though concerns about accuracy and completeness remain. Methods: The study involved four fellowship-trained minimally invasive surgeons (MISs), nine fellows (MIFs), and two general practitioners (GPs) in the MBS multidisciplinary team from March 1, 2024, to March 30, 2024. Seven AI chatbots were selected, including ChatGPT 3.5 and 4, Bard, Bing, Claude, Llama, and Perplexity, based on their public availability on December 1, 2023. Forty patient questions regarding LSG were sourced from social media, MBS organizations, and online forums. Experts and chatbots answered these questions, with their responses evaluated for accuracy and comprehensiveness on a 5-point scale. Statistical analyses compared groups' performance. Results: Chatbots demonstrated a higher overall performance score (2.55 ± 0.95) compared to the expert group (1.92 ± 1.32, Conclusion: AI chatbots generated accurate and comprehensive answers to common bariatric patient questions, suggesting promise as a scalable aid for patient education. However, readability often exceeds recommended levels, performance varies by model, occasional inaccuracies occur, and medicolegal considerations remain unresolved. Accordingly, chatbots should complement clinician counseling, and future work should improve readability and reliability and evaluate real-world safety and impact.
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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 Socratic graph.