Evidence map›Paper›PMID 42721321›Full record

ArticleJournal of medical Internet research2026

Development and Usability Assessment of a Health Education Conversational Agent for Patients With Gastric Cancer: Action Research Study.

YiChen Kang, YaMin Yan, TianXiao Wang, ZhengHong Yu, Yan Hu, ZhiXun Wang, JiYang Zhang, Jos M Latour, YuXia Zhang

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

9 authors.

YiChen KangDepartment of Nursing, Zhongshan Hospital, Fudan University, Fenglin Road 180, Shanghai, China, 86 64041990.ORCID http://orcid.org/0009-0003-2216-3820
YaMin YanDepartment of Nursing, Zhongshan Hospital, Fudan University, Fenglin Road 180, Shanghai, China, 86 64041990.ORCID http://orcid.org/0000-0002-1778-5508
TianXiao WangPlanning and Management Center, Zhongshan Hospital, Fudan University, Shanghai, China.ORCID http://orcid.org/0009-0004-0242-2861
ZhengHong YuDepartment of Nursing, Zhongshan Hospital, Fudan University, Fenglin Road 180, Shanghai, China, 86 64041990.ORCID http://orcid.org/0009-0007-9455-2437
Yan HuDepartment of Nursing, Zhongshan Hospital, Fudan University, Fenglin Road 180, Shanghai, China, 86 64041990.ORCID http://orcid.org/0000-0002-6859-4349
ZhiXun WangPlanning and Management Center, Zhongshan Hospital, Fudan University, Shanghai, China.ORCID http://orcid.org/0009-0001-6089-9551
JiYang ZhangBig Data and Artificial Intelligence Center, Zhongshan Hospital, Fudan University, Shanghai, China.ORCID http://orcid.org/0000-0002-2019-8312
Jos M LatourDepartment of Nursing, Zhongshan Hospital, Fudan University, Fenglin Road 180, Shanghai, China, 86 64041990.ORCID http://orcid.org/0000-0002-8087-6461
YuXia ZhangDepartment of Nursing, Zhongshan Hospital, Fudan University, Fenglin Road 180, Shanghai, China, 86 64041990.ORCID http://orcid.org/0000-0003-4419-7004

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: To provide patients with gastric cancer with adequate health education information for effective overall management is crucial, while traditional manners exposed certain challenges. Conversational agents have increasingly been adopted for health care use to provide innovative solutions for patient education. Objective: This study aimed to develop a health education embodied conversational agent to focus on gastric cancer disease using an action research approach and test its accuracy, usability, and user experience among patients and other related stakeholders. Methods: The AI-guided conversational agent was developed based on the OpenMEDLab 2.0 foundation model and the Retrieval-Augmented Generation (RAG) architecture. A 4-phase action research approach was adopted to implement this system at a gastric cancer center in China. Diagnose and plan phase used participatory observation and in-depth interviews to explore current health education models and patients' needs for health education. Act and implement phase was used to develop and deploy the conversational agent. Evaluate phase comprised 3 rounds of alpha testing to assess accuracy and RAG knowledge hit rate, and 1 round of beta testing to assess the usability and relevance. Reflect phase conducted in-depth interviews to gain insights into users' experiences. Data collection was conducted from September 2023 through April 2025. Participants include patients, clinical nurses, nursing managers, surgeons, clinical psychologists, and dietitians. Thematic analysis and multiple-group chi-square tests were performed, respectively, for qualitative and quantitative data. A 2-sided Results: A total of 44 patients, 13 nurses, 3 nursing managers, 2 surgeons, 1 clinical psychologist, and 1 dietitian were recruited during the study procedure. Favorable outcomes in terms of accuracy and usability were achieved. The accuracy of the agent in 3 rounds was 67% (37/55), 71% (44/62), and 82% (31/38), respectively; RAG knowledge hit rates reached 86% (47/55), 98% (61/62), and 100% (38/38). Significant differences ( Conclusions: This study provided insights into how the action research approach can inform the development and usability assessment of a gastric cancer health education conversational agent, also illustrating the value of RAG technology. Additional assessments and improvements are warranted to confirm the effectiveness and safety.

Indexed as

Health EducationPatient Education as TopicStomach NeoplasmsChinaFemaleHealth Services ResearchHumansMaleMiddle Agedaction researchdigital healthgenerative artificial intelligencehealth educationuser-centered design

Identifiers

PMID42721321
PMCPMC13561191

What OpenQuestion holds

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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.