Evidence map›Paper›PMID 39930420›Full record

ArticleBMC nursing2025

Psychometrics of the Attitude Scale towards the use of Artificial Intelligence Technologies in Nursing.

Dilek Yılmaz, Derya Uzelli, Yurdanur Dikmen

Abstract read
In one paragraph

Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 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

3 authors.

Dilek YılmazFaculty of Health Sciences, Department of Nursing, Bursa Uludağ University, Nilüfer, Bursa, 16059, Turkey. dilekk@uludag.edu.tr.
Derya UzelliFaculty of Health Sciences, Department of Nursing, İzmir Kâtip Çelebi University, Çiğli, İzmir,, 35100, Turkey.
Yurdanur DikmenFaculty of Health Sciences, Department of Nursing, Kocaeli Health and Technology University, Başiskele, Kocaeli, 41275, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIt is clear that nursing practice is directly affected by artificial intelligence (AI), and in this regard, a need is felt for more information on the knowledge and attitudes of nurses to the use of AI technology in nursing care practice. However, no inclusive measurement instrument tested for validity and reliability evaluating the attitudes of nurses to the use of AI technology was found. The aim of this research was to develop and test the validity of the Attitude Scale Towards the Use of Artificial Intelligence Technologies in Nursing (ASUAITIN) in the Turkish language.

methodsThe research was a methodological and cross-sectional study, designed to develop and test the validity of the ASUAITIN. STROBE guidelines were followed in the study. In order to create the starting materials, the researchers made a scan of the literature. Two hundred nurses working in the internal medicine, surgical and intensive care departments of a university hospital in the Marmara Region of Turkey were included in the study. Items were assessed for content validity. ASUAITIN was tested for construct validity and internal consistency reliability.

resultsASUAITIN consists of 15 items. It has two dimensions, positive attitude, and negative attitude to AI technology in nursing practice, and practice and explains 67.762% of total variance. Item loads were between 0.529 and 0.866. Cronbach alpha values were calculated to be 0.910 for the total scale, 0.933 for Factor 1, and 0.917 for Factor 2.

conclusionsThe results of this study show that the ASUAITIN scale are validated and reliable measurement tool. ASUAITIN can be used as an instrument to assess the attitudes to AI technology in practice among nurses working in the clinical field. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

Artificial intelligenceArtificial intelligence technologiesNursingScale

Identifiers

PMID39930420
PMCPMC11809082

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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 OpenQuestion graph.