Evidence map›Paper›PMID 40731339›Full record

ArticleBMC nursing2025

The mediating effects of technology trust and perceived value in the relationship between eHealth literacy and attitude toward the usage of artificial intelligence in nursing: a cross-sectional study.

Zhi Chen, Tongxi Wu, Xingxing Wu, Jinjia Wang, Shufen Ke, Hong Li, Rong Lin

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In one paragraph

Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
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  9. Pharmacists' propensity to trust automated technologies: A demographic analysis.Journal of the American Pharmacists Association : JAPhA
    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

7 authors.

Zhi Chen *The School of Nursing, Fujian Medical University, No. 1 Xuefu North Road, Minhou County, Fuzhou, Fujian Province, 350122, China.
Tongxi Wu *The First Affiliated Hospital of Fujian Medical University, No. 20 Chazhong Road, Taijiang District, Fuzhou, Fujian Province, 350005, China.
Xingxing WuThe School of Nursing, Fujian Medical University, No. 1 Xuefu North Road, Minhou County, Fuzhou, Fujian Province, 350122, China.
Jinjia WangThe Second Affiliated Hospital of Fujian Medical University, No. 950 Donghai Street, Fengze District, Quanzhou, Fujian Province, 362000, China.
Shufen KeNursing Department, The Affiliated Hospital of Putian University, No. 999 Dongzhen East Road, Licheng District, Putian, Fujian Province, 351106, China.
Hong LiThe School of Nursing, Fujian Medical University, No. 1 Xuefu North Road, Minhou County, Fuzhou, Fujian Province, 350122, China. leehong99@126.com.
Rong LinThe School of Nursing, Fujian Medical University, No. 1 Xuefu North Road, Minhou County, Fuzhou, Fujian Province, 350122, China. linrong2015@126.com.

Funding

Fujian Province Science and Technology-Economy Integration Service Platform FJKX-2024XRH04National Natural Science Foundation of China 72104050
6 · The paper itself

Abstract

backgroundAttitude toward the usage of artificial intelligence in nursing directly affect nurses' technology adoption behavior. Positive attitude toward the usage of artificial intelligence can help nurses analyze large data sets and propose potential diagnoses, thereby improving diagnostic accuracy. Empirical studies have shown that there is a potential association between eHealth literacy, technology trust, perceived value, and attitude toward the usage of artificial intelligence. This study aims to explore the mediating role of technology trust and perceived value in the relationship between eHealth literacy and attitude toward the usage of artificial intelligence in nursing.

methodsThis study used a cross-sectional survey design and a self-administered online questionnaire collection platform to conduct an online survey of 564 registered nurses (clinical nurses) in Fuzhou, Fujian Province, China from March to April, 2025. The online survey was conducted in accordance with the Checklist for Reporting Results of Internet Electronic Surveys. Descriptive analysis, Harman univariate analysis, Pearson correlation test, structural equation model, and bootstrap method were used for data analysis.

resultsBivariate correlation analysis found that eHealth literacy, technology trust, perceived value and artificial intelligence were positively correlated (r = 0.399 ~ 0.637, P < 0.001). Perceived value played a partial mediating role in the relationship between eHealth literacy and attitude toward the usage of artificial intelligence. Technology trust and perceived value played a chain-mediation role between eHealth literacy and attitude toward the usage of artificial intelligence.

conclusioneHealth literacy was found to positively predict nurses' attitudes toward the use of AI, both directly and indirectly. These findings provide a theoretical foundation for the development of nursing AI training programs and the design of clinically applicable AI systems, contributing to a better alignment between technological innovation and the practical needs of nursing care. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Attitude toward the usage of artificial intelligenceeHealth literacyMediating effectNursingPerceived valueTechnology trust

Identifiers

PMID40731339
PMCPMC12309084

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.