Evidence map›Paper›PMID 41272773›Full record

ArticleBMC nursing2025

Nurses' attitudes toward artificial intelligence: AI literacy as a predictor and the mediating effect of AI anxiety.

Sai Liu, Yanchao Xiao, Manhua Nie, Xiaoqiong Yuan, Liping Wang, Mi Wang, Zhimei Wu

Abstract read
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 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

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3 · Its place in the literature

Who cites it

18 citing papers in PubMed.

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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

7 authors.

Sai Liu *Clinical Nursing Teaching and Research Section, Second Xiangya Hospital, Central South University, Changsha, 410011, China.
Yanchao Xiao *Clinical Nursing Teaching and Research Section, Second Xiangya Hospital, Central South University, Changsha, 410011, China.
Manhua NieClinical Nursing Teaching and Research Section, Second Xiangya Hospital, Central South University, Changsha, 410011, China.
Xiaoqiong YuanClinical Nursing Teaching and Research Section, Second Xiangya Hospital, Central South University, Changsha, 410011, China.
Liping WangClinical Nursing Teaching and Research Section, Second Xiangya Hospital, Central South University, Changsha, 410011, China. wanglp@csu.edu.cn.
Mi WangThe Seventh Affiliated Hospital of University of South, Changsha, 410006, China.
Zhimei WuAnxiang County People's Hospital, Changde, 415600, China.

Funding

the Natural Science Foundation of Hunan Province, China 2024JJ9201
6 · The paper itself

Abstract

aimsThis study examines the demographic factors affecting nurses’ attitudes toward artificial intelligence (AI), AI literacy and AI anxiety. Explore the correlations among nurses’ AI literacy, AI anxiety and attitudes toward AI, and determine the internal mechanisms of the correlations among the three.

methodsThis study investigated 478 nurses working in hospitals in Hunan Province, China. A battery of instruments was used for data collection: a Nurse Information Form for Demographics, and three standardized scales—the Artificial Intelligence Literacy Scale (AILS), the Artificial Intelligence Anxiety Scale (AIAS), and the General Attitudes Towards Artificial Intelligence Scale (GAAIS)—to assess the core constructs of this study. Aided by IBM SPSS Statistics (Version 26.0), the collected data were collated and subjected to statistical analysis. Multivariate analysis was performed to investigate the effects of different social demographic data on the study subjects’ attitudes toward AI, AI literacy and AI anxiety. We also analyzed the correlations among attitudes toward AI, AI literacy and AI anxiety, and conducted multiple linear regression analysis on the variables with statistically significant effects on attitudes toward AI in univariate analysis and correlation analysis, using the Hayes PROCESS 4.1 model in SPSS to explore the mediating effects among these variables.

resultsAmong the 478 questionnaires collected, 450 were valid, for an effective response rate of 94.14%. The attitudes toward AI, AI literacy, and AI anxiety scores were 55.10 ± 8.25, 63.86 ± 8.91, and 61.95 ± 24.92, respectively. The education, age and professional title of the nurses significantly differed in terms of their attitudes toward AI. Nurse gender is correlated with AI literacy levels. AI anxiety is significantly negatively correlated with AI literacy (r =-0.32, p ≤ 0.001) and attitudes toward AI (r =- 0.42, p ≤ 0.001), whereas AI literacy and attitudes toward AI are significantly positively correlated (r = 0.45, p ≤ 0.001). The percentage of the mediating effect attributable to AI anxiety was 22.22%.

conclusionsIn our research, nurses’ attitudes toward AI are closely linked to their AI literacy and AI anxiety, with AI anxiety acting as the underlying mechanism that explains the relationship between these two factors. Nursing administrators should focus on enhancing nurses’ AI literacy while monitoring their emotional states to strengthen their positive attitudes toward AI. To achieve this goal, nursing managers could adopt a dual approach: First, practical AI-related training could be provided to improve nurses’ AI literacy. Second, during this critical phase of digital transformation, individuals regularly assess their psychological well-being and implement supportive measures to alleviate AI anxiety.

Indexed as

AI anxietyAI literacyAttitudes toward AIMediation effectNurse

Identifiers

PMID41272773
PMCPMC12752257

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LicenceCC BY-NC-ND
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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.