Evidence map›Paper›PMID 41725770›Full record

ArticleFrontiers in public health2026

Subtypes of digital literacy and their association with innovative behavior among Chinese undergraduate nursing students: a latent profile analysis.

Xueyan Wang, Yingying Wang, Xinyue Chen, Siyuan Lv, Wanyu Ding, Shaoyong Ma, Mingfen Tao

Abstract read
In one paragraph

Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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.

Xueyan Wang *Graduate School, Wannan Medical College, Wuhu, China.
Yingying Wang *Emergency Intensive Care Unit, Yijishan Hospital of Wannan Medical College, Wuhu, China.
Xinyue Chen *Graduate School, Wannan Medical College, Wuhu, China.
Siyuan LvGraduate School, Wannan Medical College, Wuhu, China.
Wanyu DingGraduate School, Wannan Medical College, Wuhu, China.
Shaoyong MaSchool of Nursing, Wannan Medical College, Wuhu, China.
Mingfen TaoDepartment of Nursing, Yijishan Hospital of Wannan Medical College, Wuhu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Digital literacy has become a core competency for nursing professionals, enabling them to adapt to modern healthcare environments and engage effectively with emerging technologies. It is closely linked to innovative behavior, which is essential for problem solving and advancing nursing practice. Despite its importance, limited research has examined differences in digital literacy among undergraduate nursing students and how these differences influence innovation. Methods: A cross-sectional study was conducted using a convenience sample of 450 undergraduate nursing students from four universities in Anhui Province, China. Participants completed a general information questionnaire, the Undergraduate Digital Literacy Scale, and the Innovative Behavior Scale. Latent profile analysis (LPA) was employed to classify students into distinct digital literacy profiles, while logistic regression and one-way ANOVA were used to explore factors influencing profile membership and the relationship between digital literacy and innovative behavior. Results: Three latent profiles were identified: a "Low Digital Literacy" group (34.1%), a "Moderate Digital Literacy" group (15.9%), and a "High Digital Literacy" group (50.0%). Significant differences were observed across profiles in relation to gender, age, academic year, and frequency of artificial intelligence (AI) use in the past 6 months. Importantly, students with higher digital literacy consistently exhibited stronger innovative behavior ( Conclusion: Digital literacy among undergraduate nursing students is heterogeneous and shaped by demographic and experiential factors. Targeted educational interventions tailored to distinct literacy profiles are needed to bridge gaps, promote equity, and strengthen innovation. By integrating AI and advanced digital tools into nursing curricula, educators can enhance students' competencies and better prepare them to thrive in an increasingly digital and intelligent healthcare landscape.

Indexed as

Computer LiteracyCreativityStudents, NursingAdultChinaCross-Sectional StudiesEast Asian PeopleEducation, Nursing, BaccalaureateFemaleHumansMaleSurveys and QuestionnairesYoung Adultdigital literacyinnovative behaviorlatent profile analysisnursingstudent

Identifiers

PMID41725770
PMCPMC12920592

What OpenQuestion holds

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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.