Evidence map›Paper›PMID 42620479›Full record

ArticleFrontiers in public health2026

Acceptance of generative AI-assisted medical decision-making among Chinese physicians and patients and its ethical determinants: a cross-sectional survey.

Zhen Qian, Xizheng Li, Yingxue Li, Lina Wang, Qian Xu, Feng Cao, Yuwen Lyu, Junrong Liu

Abstract read
In one paragraph

Article in Frontiers in public health, 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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0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

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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

8 authors.

Zhen QianInstitute of Humanities and Social Sciences, Guangzhou Medical University, Guangzhou, Guangdong, China.
Xizheng LiSchool of Health Management, Guangzhou Medical University, Guangzhou, Guangdong, China.
Yingxue LiDivision of Nephrology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China.
Lina WangMedical Ethics Office, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou, Guangdong, China.
Qian XuSchool of Medical Humanities, China Medical University, Shenyang, Liaoning, China.
Feng CaoSchool of Health Management, Guangzhou Medical University, Guangzhou, Guangdong, China.
Yuwen LyuSchool of Marxism, Guangzhou Medical University, Guangzhou, Guangdong, China.
Junrong LiuInstitute of Humanities and Social Sciences, Guangzhou Medical University, Guangzhou, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Generative artificial intelligence (GAI) is increasingly being integrated into medical decision-making, yet ethical challenges continue to hinder its widespread clinical implementation. Existing research has paid limited attention to the ethical determinants of acceptance and differences in perceptions among key stakeholder groups. This study examined acceptance of GAI-assisted medical decision-making among Chinese physicians, patients, and other healthcare stakeholders, identified its ethical determinants, and explored differences across stakeholder groups to inform ethical governance. Methods: A cross-sectional survey was conducted using a multistage sampling strategy across healthcare institutions in Henan and Guangdong provinces, China, between December 2025 and January 2026. A total of 533 participants, including healthcare professionals, patients, and other stakeholders, were recruited. A self-developed four-dimensional scale assessing perceived functional value, perceived ethical risk, acceptance intention, and ethical governance expectations was developed through literature review, expert consultation, and pilot testing. Multivariable linear regression analysis was performed using SPSS version 26.0 to identify factors associated with acceptance intention. Results: Participants reported a moderate level of acceptance of GAI-assisted medical decision-making (3.68 ± 0.70), while ethical governance expectations received the highest mean score (4.03 ± 0.76). Multivariable regression analysis showed that perceived functional value ( Conclusion: Acceptance of GAI-assisted medical decision-making among Chinese stakeholders is primarily driven by perceived functional value and ethical governance expectations, with significant differences in ethical perceptions across stakeholder groups. These findings provide empirical evidence for developing targeted ethical governance frameworks to facilitate responsible GAI integration into clinical practice.

Indexed as

Clinical Decision-MakingGenerative Artificial IntelligencePhysiciansAdultAttitude of Health PersonnelChinaCross-Sectional StudiesEast Asian PeopleFemaleHumansMaleMiddle AgedSurveys and Questionnairesacceptance intentionethical governancegenerative artificial intelligencehealthcare AImedical decision-makingphysician–patient perspectives

Identifiers

PMID42620479
PMCPMC13485889

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.