Evidence map›Paper›PMID 42379874›Full record

ArticleJournal of nursing management2026

Change Fatigue and Attitudes Toward AI in County-Level Nurses: The Mediating Role of AI Literacy.

Ming Yu, Mengjia Zhou, Rong Yu, Xiaoli Fan, Ronghui Geng, Jing Ji, Suping Cai, Lili Jiang, Lingling Jiang

Abstract read
In one paragraph

Article in Journal of nursing management, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

9 authors.

Ming YuDepartment of Nursing, Affiliated Rudong Hospital of Xinglin College, Nantong University, Nantong, Jiangsu, 226001, China, ntu.edu.cn.ORCID https://orcid.org/0009-0008-3162-455X
Mengjia ZhouDepartment of Nursing, Affiliated Rudong Hospital of Xinglin College, Nantong University, Nantong, Jiangsu, 226001, China, ntu.edu.cn.ORCID https://orcid.org/0009-0008-7673-7232
Rong YuDepartment of Nursing, Affiliated Rudong Hospital of Xinglin College, Nantong University, Nantong, Jiangsu, 226001, China, ntu.edu.cn.ORCID https://orcid.org/0009-0000-9796-7338
Xiaoli FanDepartment of Nursing, Affiliated Rudong Hospital of Xinglin College, Nantong University, Nantong, Jiangsu, 226001, China, ntu.edu.cn.ORCID https://orcid.org/0009-0007-8383-6151
Ronghui GengDepartment of Nursing, Affiliated Rudong Hospital of Xinglin College, Nantong University, Nantong, Jiangsu, 226001, China, ntu.edu.cn.ORCID https://orcid.org/0009-0001-0843-8942
Jing JiDepartment of Nursing, Affiliated Rudong Hospital of Xinglin College, Nantong University, Nantong, Jiangsu, 226001, China, ntu.edu.cn.ORCID https://orcid.org/0009-0004-9998-3234
Suping CaiDepartment of Nursing, Affiliated Rudong Hospital of Xinglin College, Nantong University, Nantong, Jiangsu, 226001, China, ntu.edu.cn.ORCID https://orcid.org/0009-0005-8707-9683
Lili JiangDepartment of Nursing, Affiliated Rudong Hospital of Xinglin College, Nantong University, Nantong, Jiangsu, 226001, China, ntu.edu.cn.ORCID https://orcid.org/0009-0004-4605-4829
Lingling JiangDepartment of Nursing, Affiliated Rudong Hospital of Xinglin College, Nantong University, Nantong, Jiangsu, 226001, China, ntu.edu.cn.ORCID https://orcid.org/0009-0002-2463-6444

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveGrounded in the conservation of resources theory, this study aimed to examine the mediating role of artificial intelligence literacy in the relationship between change fatigue and attitudes toward AI application among nurses in county-level hospitals, thereby providing insights for enhancing AI technology acceptance in primary care settings.

backgroundCounty-level hospitals in China are undergoing significant organizational transformations alongside rapid technological advancements. Nurses in these settings frequently experience change fatigue due to continuous institutional reforms, while simultaneously facing challenges in adapting to artificial intelligence technologies. Understanding the psychological mechanisms underlying nurses' acceptance of AI is crucial for successful technology implementation in primary care settings.

designA cross-sectional analytic study employing mediation analysis.

methodsA cross-sectional survey was conducted using convenience sampling from August to September 2025. A total of 460 clinical nurses from a county-level tertiary B hospital in Nantong City, China (99.6% female; mean age 31-40 years: 43.3%), were assessed. Data were analyzed using structural equation modeling with the maximum likelihood estimation method, and the significance of indirect effects was tested using the bootstrap method (5000 samples).

resultsThe mean scores for change fatigue, AI literacy, and AI application attitudes were 29.27 ± 6.98, 49.82 ± 5.27, and 45.26 ± 2.45, respectively. Change fatigue showed a significant negative association with AI application attitudes (β = -0.36, p < 0.001), while AI literacy demonstrated a significant positive effect (β = 0.34, p < 0.001). AI literacy partially mediated the relationship between change fatigue and AI application attitudes (indirect effect = -0.185, 95% CI: [-0.231, -0.142]), accounting for 37.7% of the total effect.

conclusionAI literacy plays a significant partial mediating role. To improve nurses' acceptance of AI technologies, nursing administrators should implement dual interventions aimed at both alleviating change fatigue (e.g., paced change management and psychological support) and systematically enhancing AI literacy (e.g., stratified training programs).

Indexed as

Artificial IntelligenceAttitude of Health PersonnelComputer LiteracyFatigueNursesAdultAttitude to ComputersChinaCross-Sectional StudiesFemaleHumansMaleSurveys and QuestionnairesAI application attitudesartificial intelligence literacychange fatiguecounty-level nursesmediating effectnursing management

Identifiers

PMID42379874
PMCPMC13318476

What Socratic holds

Textmetadata
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 Socratic graph.