Evidence map›Paper›PMID 42180637›Full record

ArticleFrontiers in health services2026

Identification of quality and safety concerns in AI chatbot responses to procedural sedation: a comparative evaluation of ChatGPT, Gemini, and Copilot.

Hüseyin Babun, Fatih Oluş

Abstract read
In one paragraph

Article in Frontiers in health services, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Hüseyin BabunDepartment of Oral and Maxillofacial Surgery, Faculty of Dentistry, Akdeniz University, Antalya, Türkiye.
Fatih OluşDepartment of Oral and Maxillofacial Surgery, Faculty of Dentistry, Akdeniz University, Antalya, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Artificial intelligence-based chatbots are increasingly used by patients to obtain medical information before healthcare encounters. However, the reliability and safety of chatbot-generated responses remain uncertain, particularly for topics involving procedural sedation. Methods: This study evaluated the quality, safety, and confabulation risk of responses generated by ChatGPT, Gemini, and Copilot to common patient questions about procedural sedation. A set of standardized patient-oriented questions was submitted to each chatbot, and responses were independently evaluated by clinical experts using predefined criteria assessing informational quality, clinical safety, and the presence of confabulated or misleading content. Results: The results demonstrated variability in response quality across chatbots, with several answers containing incomplete information, safety omissions, or potentially misleading statements. Although many responses provided generally understandable explanations, important clinical details relevant to patient safety were inconsistently addressed. Discussion: These findings suggest that while AI chatbots may support patient education, their responses regarding procedural sedation may contain safety gaps and confabulated content that limit their reliability as standalone sources of medical information. Careful oversight and clinician-guided use of AI-generated health information may therefore be necessary to ensure safe and accurate patient communication.

Indexed as

artificial intelligencechatbotsconfabulationpatient educationprocedural sedation

Identifiers

PMID42180637
PMCPMC13194365

What OpenQuestion holds

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Registered trials

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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.