ArticleBMC nursing2026
Mapping factors associated with nurses' attitudes toward artificial intelligence: a scoping review.
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 Levels and Attitudes Toward Artificial Intelligence Technology Among Intensive Care Nurses: A Cross-Sectional Study.Journal of evaluation in clinical practice · 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
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe integration of artificial intelligence (AI) into nursing practice is advancing, with nurses’ attitudes as a potential critical factor for its successful adoption. A comprehensive understanding of these attitudes is therefore needed.
objectiveThis review aims to systematically map and synthesize the factors associated with nurses’ attitudes toward AI.
methodThis scoping review was conducted in accordance with the Joanna Briggs Institute (JBI) framework for scoping reviews and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR). The research question was developed based on the Participants, Concept, and Context (PCC) framework, focusing on factors associated with clinical registered nurses’ attitudes toward AI. Inclusion criteria comprised original studies published in English or Chinese that involved nurses as participants and reported factors related to AI attitudes. The search strategy integrated subject headings and free-text terms and was applied across nine databases, such as PubMed, covering literature up to September 29, 2025. Two researchers independently screened the literature and extracted data using a predefined form, which included items such as author, year, country, study design, sample, measurement tools, attitude outcomes, and reported factors. Disagreements were resolved through team discussion or consultation with a senior researcher. The extracted factors were categorized and synthesized following the tripartite model of attitudes.
resultA total of 18 studies were included in this review. The included studies were primarily cross-sectional, focused on measuring nurses’ AI attitudes and exploring correlates. These factors were synthesized into five dimensions: demographic, cognitive, affective, conative, and external. Evidence on demographic factors was heterogeneous, while findings in other dimensions showed greater consistency. Future research should prioritize investigating the theoretical mechanisms and clinical translation pathways underlying these attitudes.
conclusionThis scoping review maps factors associated with nurses’ AI attitudes across individual, organizational, and systemic levels. Current evidence, primarily cross-sectional, suggests associations but not causation. Future research should examine multi-level interactions through longitudinal and qualitative designs to build integrated theoretical models. Beyond observation, nursing must transition to active co-creation in the AI ecosystem, ensuring integration is theoretically informed and aligned with professional values. CLINICAL TRIAL NUMBER: Not applicable.
Indexed as
Identifiers
What Socratic 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 Socratic graph.