Evidence map›Paper›PMID 42465649›Full record

ArticleFrontiers in public health2026

Clinical nursing interns' perceptions of artificial intelligence-assisted tools in human-AI collaboration: a qualitative persona-based study.

Liping Yao, Hang Wang, Jianping Liu, Chunmei Song

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

4 authors.

Liping YaoSchool of Nursing‌, Zhejiang Chinese Medical University, Hangzhou, China.
Hang WangSchool of Medicine, Shanghai East Hospital, Tongji University, Shanghai, China.
Jianping LiuDepartment of Neurology, Yancheng Third People's Hospital, Affiliated Yancheng Third People's Hospital of Jiangsu Medical College, Yancheng, China.
Chunmei SongDepartment of Disinfection Supply Center, Yancheng Third People's Hospital, Affiliated Yancheng Third People's Hospital of Jiangsu Medical College, Yancheng, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aims to explore the cognitive characteristics and group differences of clinical nursing interns regarding the use of artificial intelligence-assisted tools in a human-AI collaboration context through a persona-based approach, providing references for optimizing nursing internship teaching and the standardized application of AI-assisted tools. Methods: A descriptive qualitative research approach was adopted. From January to March 2026, 25 clinical nursing interns were selected through purposive sampling in three tertiary grade A hospitals in Zhejiang and Jiangsu provinces for semi-structured interviews. The interview data were analyzed using Colaizzi's seven-step method and managed and coded with NVivo 15.0 software. Based on the extraction of cognitive features and label dimensions, a cognitive profile of clinical nursing interns' use of artificial intelligence-assisted tools was constructed. Following thematic analysis, participants with similar cognitive characteristics, behaviors, and support needs were grouped to construct five distinct persona types. Results: A total of 25 clinical nursing interns were included. The cognitive profile dimensions of clinical nursing interns regarding artificial intelligence-assisted tools include motivation for use, behavior patterns, trust attitude, degree of dependence, risk awareness, and support needs, etc. Finally, five cognitive profile types were constructed: Active-Thinking type, Process-Adaptation type, Task-Dependent type, Passive-Burden type, and Doubtful-Defense type. Conclusion: This study is among the first qualitative investigations to apply persona construction to explore nursing interns' perceptions of AI-assisted tools. In the human-AI collaboration model, clinical nursing interns have significant heterogeneity in their perception of artificial intelligence-assisted tools. Nursing educators should provide personalized teaching guidance, process support, and risk management based on the cognitive characteristics and needs of different types of interns, helping them improve their learning and work efficiency while developing the ability to make independent judgments, use in a standardized manner, and collaborate prudently.

Indexed as

Artificial IntelligenceAttitude of Health PersonnelAdultChinaCooperative BehaviorFemaleHumansInterviews as TopicMaleQualitative Researchartificial intelligenceclinical nursing internshuman–AI collaborationnursing educationqualitative researchuser profiles

Identifiers

PMID42465649
PMCPMC13372906

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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.