Evidence map›Paper›PMID 41814327›Full record

ArticleBMC nursing2026

Artificial intelligence literacy and related factors among nursing undergraduates in Northeast China.

Dong Chen, Xinjing Zhang, Shasha Zhang, Yanyan Pan, Chongkuan Zhu, Lei Wang

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In one paragraph

Article in BMC nursing, 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

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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

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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

6 authors.

Dong ChenDepartment of Nursing, Heilongjiang Nursing College, Harbin, Heilongjiang Province, China.
Xinjing ZhangEmergency Intensive Care Unit, Qingdao Hiser Hospital Affiliated of Qingdao University (Qingdao Traditional Chinese Medicine Hospital), Qingdao, Shandong Province, China.
Shasha ZhangDermatology and Medical Cosmetology Treatment Center Dermatology DEPT, Qingdao Hiser Hospital Affiliated of Qingdao University (Qingdao Traditional Chinese Medicine Hospital), Qingdao, Shandong Province, China.
Yanyan PanDepartment of Nursing, Heilongjiang Nursing College, Harbin, Heilongjiang Province, China.
Chongkuan ZhuIntensive Care Unit One, Qingdao Hiser Hospital Affiliated of Qingdao University (Qingdao Traditional Chinese Medicine Hospital), Qingdao, Shandong Province, China.
Lei WangSchool of Nursing, Dalian Medical University, Dalian, Liaoning Province, China. wangl09@dmu.edu.cn.

Funding

the 2023 Teaching Reform Research Project of Dalian Medical University DYLX23013the 2025 Annual Planning Project of Heilongjiang Province's Education Science "14th Five-Year Plan" ZJB1425057the 2025 School-level Vocational Education Research Project of Heilongjiang Nursing College 20250203
6 · The paper itself

Abstract

backgroundThere is a potential shortage of information-based teaching resources in Northeast China, and the artificial intelligence literacy of nursing undergraduates and related factors are not clear.

methodsThis is a cross-sectional survey study conducted in the northeastern region of China. In this study, 546 nursing undergraduates were studied. The data was collected through a mobile app-based survey in October 2024. We assessed demographic factors and artificial intelligence literacy.

resultsThe total score of artificial intelligence literacy of nursing undergraduates was 134.40 ± 4.38. Regression analysis showed that gender, monthly household income, attitude towards artificial intelligence, and whether or not participating in artificial intelligence-related education/training had a significant negative effect on artificial intelligence literacy (p < .05).

conclusionsIt is recommended to formulate effective measures in combination with relevant factors to improve the artificial intelligence literacy of nursing undergraduates in areas with a potential shortage of information-based teaching resources and promote the digital transformation of nursing undergraduates’ future careers. CLINIC TRIAL NUMBER: Not applicable.

Indexed as

Artificial intelligenceCross-sectional studyLiteracyNortheast ChinaNursing undergraduatesRelated factors

Identifiers

PMID41814327
PMCPMC13094127

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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.