Evidence map›Paper›PMID 42727068›Full record

ArticleJournal of medical Internet research2026

Generative AI Use, Perceived Usefulness, Perceived Risk, and Physician Burnout and Fulfillment Among Chinese Physicians: Mixed Methods Multiregional Study.

Dan Guo, Yanan Zhao, Tingkun Yang, Xingyu Bao, Ping Huang

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

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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

5 authors.

Dan GuoDepartment of Scientific Research and Teaching, Beijing Genertec Aerospace Hospital, Beijing, China.ORCID https://orcid.org/0000-0002-4442-5663
Yanan ZhaoFaculty of Health and Wellness, City University of Macau, Macau, China.ORCID https://orcid.org/0000-0002-1532-3641
Tingkun YangFaculty of Health and Wellness, City University of Macau, Macau, China.ORCID https://orcid.org/0009-0000-1163-1738
Xingyu BaoFaculty of Health and Wellness, City University of Macau, Macau, China.ORCID https://orcid.org/0009-0001-7550-6052
Ping HuangDepartment of Child Health Care, Luzhou People's Hospital, Chengdu, China.ORCID https://orcid.org/0000-0002-3757-0432

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs generative AI (GenAI) becomes increasingly prevalent, its impact on physician mental health has garnered significant attention; yet, empirical evidence remains limited.

objectiveThis study aims to investigate the correlations between the usage frequency of GenAI, perceived usefulness (PU), and perceived risk (PR) of GenAI with physicians' burnout and professional fulfillment.

methodsA mixed methods design was used, integrating a quantitative survey of physicians across 4 regions in China with in-depth qualitative interviews to elucidate the underlying psychological mechanisms. The quantitative component involved a cross-sectional survey of 961 physicians, with the questionnaire collecting data on demographic and professional characteristics, socioeconomic status, GenAI usage frequency, PU, and PR. Semistructured interviews with 10 physicians were used for in-depth mining. Multivariable logistic and linear regression models with province-level fixed effects were fitted to examine the association between usage of GenAI, PU, PR, and physicians' burnout and fulfillment. Stratified analyses were further performed to explore the moderating effect of demographic and clinical characteristics.

resultsQuantitative analysis revealed no direct correlation between GenAI usage frequency and burnout. However, PU was positively associated with professional fulfillment (odds ratio [OR] 1.56, 95% CI 1.17-2.08; P=.003), whereas PR was associated with a higher likelihood of burnout (OR 1.80, 95% CI 1.46-2.21; P<.001). Stratified analyses showed that for physicians working ≥3 night shifts per week, GenAI usage was associated with higher odds of burnout, although the estimate was imprecise (OR 13.96, 95% CI 2.40-81.04; P=.003). The qualitative findings further suggested that the benefits of using GenAI may be offset by the additional burden. The PU of GenAI was perceived to enhance professional fulfillment by bolstering self-efficacy, whereas the PR of GenAI was linked to heightened burnout rooted in unclear boundaries of responsibilities and rights, as well as challenges to professional identity.

conclusionsThe GenAI revolution in medicine is as much a psychological transition as it is a technological one. GenAI use is not directly associated with improved psychological states among clinicians. The PU of GenAI relates to professional fulfillment, and the PR concerns correspond to elevated burnout. Sustaining clinician well-being during this digital shift thus parallels a dual requirement, balancing the potential for professional fulfillment tied to GenAI utility against the concurrent verification fatigue and legal uncertainty cluster around clinician burnout.

Indexed as

Burnout, ProfessionalPhysiciansAdultChinaCross-Sectional StudiesFemaleGenerative Artificial IntelligenceHumansMaleMiddle AgedSurveys and Questionnairesburnoutgenerative artificial intelligenceperceived riskperceived usefulnessprofessional fulfillment

Identifiers

PMID42727068
PMCPMC13615376

What Socratic 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 Socratic graph.