Evidence map›Paper›PMID 40747825›Full record

ArticleThe British journal of surgery2025

Reporting guideline for chatbot health advice studies: the Chatbot Assessment Reporting Tool (CHART) statement.

CHART Collaborative

Abstract readConsensus Statement
In one paragraph

Article in The British journal of surgery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Review
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

1 author.

CHART Collaborative

Funding

McMaster University
6 · The paper itself

Abstract

The Chatbot Assessment Reporting Tool (CHART) is a reporting guideline developed to provide reporting recommendations for studies evaluating the performance of generative artificial intelligence (AI)-driven chatbots when summarizing clinical evidence and providing health advice, referred to as chatbot health advice studies. CHART was developed in several phases after performing a comprehensive systematic review to identify variation in the conduct, reporting, and method in chatbot health advice studies. Findings from the review were used to develop a draft checklist that was revised through an international, multidisciplinary, modified, asynchronous Delphi consensus process of 531 stakeholders, three synchronous panel consensus meetings of 48 stakeholders, and subsequent pilot testing of the checklist. CHART includes 12 items and 39 subitems to promote transparent and comprehensive reporting of chatbot health advice studies. These include title (subitem 1a), abstract/summary (subitem 1b), background (subitems 2a,b), model identifiers (subitems 3a,b), model details (subitems 4a-c), prompt engineering (subitems 5a,b), query strategy (subitems 6a-d), performance evaluation (subitems 7a,b), sample size (subitem 8), data analysis subitem 9a), results (subitems 10a-c), discussion (subitems 11a-c), disclosures (subitem 12a), funding (subitem 12b), ethics (subitem 12c), protocol (subitem 12d), and data availability (subitem 12e). The CHART checklist and corresponding diagram of the method were designed to support key stakeholders including clinicians, researchers, editors, peer reviewers, and readers in reporting, understanding, and interpreting the findings of chatbot health advice studies.

Indexed as

Artificial IntelligenceResearch DesignChecklistDelphi TechniqueGenerative Artificial IntelligenceHumans

Identifiers

PMID40747825
PMCPMC12314741

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.