Evidence map›Paper›PMID 40597054›Full record

ArticleBMC nursing2025

Validity and reliability of the Chinese translation of the attitude scale towards the use of artificial intelligence technologies in nursing (ASUAITIN)- a cross-sectional study.

Rong Hu, Yan-Fei Ma, Chun-Yan Wang, Xiao-Ya Li, Hua-Ping Huang

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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 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
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11citing papers in PubMed, 1 pooled it
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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

Who cites it

11 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Rong HuDepartment of Orthopedics, School of Medicine, Mianyang Central Hospital, University of Electronic Science and Technology of China, Mianyang, 621000, China.
Yan-Fei MaDepartment of Orthopedics, School of Medicine, Mianyang Central Hospital, University of Electronic Science and Technology of China, Mianyang, 621000, China.
Chun-Yan WangDepartment of Orthopedics, School of Medicine, Mianyang Central Hospital, University of Electronic Science and Technology of China, Mianyang, 621000, China. 703113936@qq.com.
Xiao-Ya LiDepartment of Orthopedics, School of Medicine, Mianyang Central Hospital, University of Electronic Science and Technology of China, Mianyang, 621000, China.
Hua-Ping HuangDepartment of Orthopedics, School of Medicine, Mianyang Central Hospital, University of Electronic Science and Technology of China, Mianyang, 621000, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimThis study aimed to test the psychometric properties of the Attitudes Toward Artificial Intelligence in Nursing Scale (ASUAITIN) in Chinese culture.

methodsA convenience sampling method was employed to recruit 499 clinical nurses from Sichuan Province, China. Following the Brislin model, the ASUAITIN scale underwent forward translation, synthesis, and back-translation. Cultural adaptation and revisions were conducted through expert consultation and pilot testing, resulting in the finalized ASUAITIN-C. The structural validity of the scale was evaluated using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Reliability was assessed through internal consistency and test-retest reliability.

resultsThe ASUAITIN-C consists of 15 items and two factors, which account for 73.278% of the total variance. The overall Cronbach's α coefficient of the ASUAITIN-C is 0.785, while the Cronbach's α values for the two subdimensions are 0.920 and 0.948, respectively. The test-retest reliability over two months, measured by the intraclass correlation coefficient (ICC), is 0.91.

conclusionStudies have shown that this questionnaire is a valid and reliable tool for assessing nurses' attitudes toward using artificial intelligence in the nursing field.

Indexed as

Artificial intelligence technologiesNursingPsychologicalScale

Identifiers

PMID40597054
PMCPMC12211220

What OpenQuestion 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 OpenQuestion graph.