ArticleBMC nursing2026
Exploring factors associated with nursing students' artificial intelligence literacy: insights from a national mixed methods study.
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.
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.
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.
Who cites it
1 citing paper in PubMed.
- Artificial intelligence literacy among nursing students and its association with learning engagement.Frontiers in public health · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIntegrating artificial intelligence (AI) into healthcare is rapidly expanding, yet research on nursing students' AI literacy (AIL) remains limited. This study assessed AIL levels, identified factors associated with AIL, and explored students' perceptions of AI use.
methodsThe mixed-methods study used a non-probability snowball sampling technique, involving 383 undergraduate nursing students in Türkiye, and utilized the Descriptive Characteristics Form and the Artificial Intelligence Literacy Scale (AILS). Quantitative analyses included t-tests, ANOVA, Pearson correlations, and multiple linear regression. Qualitative data underwent thematic analysis.
resultsThe mean age of participants was 21.52 (SD ± 3.31; range, 18-40), and 83.3% of them were female. Participants' mean AILS score was 110.80 (SD ± 40.98; range = 31-216) with 41.22 ± 19.67 for technical understanding, 40.49 ± 15.57 for critical appraisal, and 29.09 ± 10.68 for practical application. Higher comfort with new technologies (β = 0.352; t = 7.06; p < 0.001) and having witnessed/experienced ethical concerns (β = 0.094; t = 1.98; p = 0.048) were significantly associated with higher AIL. Seven themes were identified: (1) Support and Convenience, (2) Time Management, (3) Learning and Academic Development, (4) Ethical and Security Concerns, (5) Misinformation and Trust, (6) Laziness and Dependency, and (7) Creativity and Thinking.
conclusionEnhancing AIL skills among nursing students is essential for the ethical and rational use of AI. Educators should guide nursing students to develop strategies to improve their technical, appraisal, and practical AIL skills. The present study may contribute to identifying educational strategies to support nursing students' readiness for AI in nursing education.
trial registrationNot applicable.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.