TruaceTracing the truth around AISunday, July 19, 2026
TRV-2026-0265Certified recordPeer-reviewed

Comparison of artificial intelligence-based chatbots and expert periodontists in responding to patient questions: a multi-dimensional analysis

Large Language Model (LLM) -based chatbots are increasingly used in patient information processes. The aim of this study was to compare the performance of ChatGPT (GPT-5.1), Gemini (2.5 Flash), and Claude (Sonnet 4.5) with expert periodontologists in responding to periodontal questions. Responses were evaluated in terms of scientific accuracy, completeness, conciseness & focus, empathy, and clarity, and differences among groups were investigated. The question pool was developed de novo based on clinical experien…

Health · The Trace — both readings · certified 2026-07-19 · v1 · article view · machine-readable

Current reading — gain

LLM chatbots answered periodontal patient questions with scientific accuracy comparable to expert periodontologists while scoring higher on completeness and empathy.

Current reading — problem

Some chatbot models showed lower conciseness & focus and clarity, producing longer less-focused answers that may make it harder for patients to maintain focus and perceive information in a structured manner.

What this doesn’t fix

Findings based on 20 de novo questions and first responses to a standardized prompt, with model differences affecting conciseness and clarity, requiring physician oversight before clinical use.

Evidence

Reader signal

How should this claim be treated?

Cite this record

Truvace Impact Record TRV-2026-0265, v1: “Comparison of artificial intelligence-based chatbots and expert periodontists in responding to patient questions: a multi-dimensional analysis.” Truvace, 2026-07-19. /record/TRV-2026-0265 (accessed at citation time). sha256 246b6e053f2fec6b

Calibration history

Every change to this record since certification, in the open. None yet — the reading has held since it entered the record.

  1. Certifiedv1246b6e053f2f

    Certified into the record

Verify this record
How to verify without trusting this page

Fetch the canonical text of any version from /api/record/TRV-2026-0265 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.