Evidence map›Paper›PMID 42270714›Full record

ArticleScientific reports2026

Psychological safety and perceived risk are associated with emergency nurses' intention to use AI-augmented triage systems.

Yuan Jiang, Minghao Kong, Taotao Feng, Shijie Wu

Abstract read
In one paragraph

Article in Scientific reports, 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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3 · Its place in the literature

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No citing paper in PubMed yet.

4 · The record

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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

4 authors.

Yuan JiangSchool of Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China. 2105066@tongji.edu.cn.
Minghao KongSchool of Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China.
Taotao FengSchool of Medicine, Shanghai Tenth People's Hospital, Tongji University, Shanghai, China.
Shijie WuTongji University School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Emergency department overcrowding places sustained pressure on triage workflows and patient prioritization. Artificial intelligence (AI)-augmented triage systems have been introduced to support emergency decision-making, but frontline adoption may depend on both technology-related perceptions and human-organizational conditions. This study examined factors associated with emergency nurses' attitudes and intention to use AI-augmented triage systems, with particular attention to psychological safety and perceived risk. A multi-hospital cross-sectional survey was conducted among 162 frontline triage nurses across nine pilot hospitals in Shanghai between June and August 2025. All participants had at least six months of emergency triage experience and at least three months of actual experience using the AI-augmented triage system. Partial least squares structural equation modelling was used to assess the measurement and structural models. The model explained 57.2% of the variance in attitude and 41.0% of the variance in intention to use. Task-technology fit (β = 0.483, 95% CI [0.387, 0.574]), perceived explainability (β = 0.385, 95% CI [0.280, 0.484]), and psychological safety (β = 0.401, 95% CI [0.294, 0.512]) were positively associated with attitude. Attitude was positively associated with intention to use (β = 0.629, 95% CI [0.526, 0.710]). Perceived risk showed a small negative moderating effect on the association between attitude and intention to use (β = - 0.139, p = 0.039, f

Indexed as

Artificial IntelligenceEmergency NursingNursesTriageAdultAttitude of Health PersonnelChinaCross-Sectional StudiesEmergency Service, HospitalFemaleHumansIntentionMaleMiddle AgedPsychological SafetySurveys and QuestionnairesArtificial intelligenceEmergency nursingHealth informaticsPerceived riskPsychological safetyTechnology adoption

Identifiers

PMID42270714
PMCPMC13500836

What OpenQuestion holds

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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.