Evidence map›Paper›PMID 41112660›Full record

ArticleFrontiers in public health2025

Behavioral drivers of AI nursing acceptance in the Greater Bay Area: a family-caregiver perspective on trust and risk.

Chenxi Ye, Zeyu Wang, Miaohui Wu, Runhao Kang, Fujiang Yuan, Chen Chen

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Identifying Measurement Dimensions of Users' Benefit-Risk Perceptions of AI in Healthcare: A Scoping Review.Inquiry : a journal of medical care organization, provision and financing
    Article
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

6 authors.

Chenxi Ye *School of Art and Design, Guangdong University of Technology, Guangzhou, China.
Zeyu Wang *School of Art and Design, Guangdong University of Technology, Guangzhou, China.
Miaohui WuSchool of Art and Design, Guangdong University of Technology, Guangzhou, China.
Runhao KangInstitute for Design, Hebei Academy of Fine Arts, Shijiazhuang, China.
Fujiang YuanSchool of Computer Science and Technology, Taiyuan Normal University, Taiyuan, China.
Chen ChenSchool of Art and Design, Guangdong University of Technology, Guangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid aging of the population in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) has increased demand for smart healthcare solutions. Artificial intelligence (AI)-based nursing technologies show promise in alleviating care burdens, yet family caregivers-often the primary decision-makers-exhibit low adoption rates due to trust issues and risk perception. This study investigated factors influencing caregivers' behavioral intention to adopt AI nursing technologies by developing an extended Unified Theory of Acceptance and Use of Technology (UTAUT) model incorporating trust and perceived risk. A cross-sectional survey was conducted across hospitals and care institutions in the GBA (

Indexed as

Artificial IntelligenceCaregiversFamilyTrustAdultAgedChinaCross-Sectional StudiesFemaleHumansMaleMiddle AgedSurveys and QuestionnairesAI nursing technologiesfamily caregiversperceived risktrustUTAUT

Identifiers

PMID41112660
PMCPMC12528075

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.