Evidence map›Paper›PMID 39558522›Full record

ArticleJournal of clinical nursing2026

Examining the Anxiety and Preparedness Levels of Nurses and Nurse Candidates for Artificial Intelligence Health Technologies.

Gülseren Maraş, Eda Albayrak Günday, Yeliz Sürme

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Article in Journal of clinical nursing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 pooled it
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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

15 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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.

Gülseren MaraşErciyes University, Faculty of Health Sciences, Surgical Nursing, Kayseri, Türkiye.ORCID https://orcid.org/0000-0002-2876-5772
Eda Albayrak GündayErciyes University, Faculty of Health Sciences, Mental Health and Disease Nursing, Kayseri, Türkiye.ORCID https://orcid.org/0000-0002-0271-2955
Yeliz SürmeErciyes University, Faculty of Health Sciences, Surgical Nursing, Kayseri, Türkiye.ORCID https://orcid.org/0000-0002-0851-0254

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimsThis study examined the anxiety levels of nurses and nurse candidates regarding humanoid nurse robots and artificial intelligence health technologies in perioperative patient care.

designDescriptive and cross-sectional study.

methodsThe research was conducted with 158 intern students and 167 surgical nurses. Socio-demographic characteristics form, Questions Form Regarding Humanoid Nurse Robots and Artificial Intelligence Health Technologies, Artificial Intelligence Anxiety Scale and The Medical Artificial Intelligence Preparedness Scale were used. The independent t-test and one-way analysis of variance (ANOVA) were used. This study complied with Appendix S1.

resultsThe total scores on the Artificial Intelligence Anxiety Scale for nurses and nursing students are 73.089 ± 31.667 and 73.624 ± 28.029, respectively. The total scores on the Artificial Intelligence Readiness Scale for nurses and nursing students are 71.736 ± 15.064 and 72.183 ± 13.714, respectively. When comparing the sociodemographic characteristics and scale scores of nurses, a statistically significant difference was found between age and the Artificial Intelligence Anxiety Scale scores (p < 0.05). There was also a statistically significant difference between age, gender and work duration and the Artificial Intelligence Readiness Scale scores for nurses (p < 0.05).

conclusionBoth groups exhibited moderate levels of anxiety and readiness regarding artificial intelligence. Comprehensive research is needed to elucidate the impact of artificial intelligence technologies on nursing professionals. IMPLICATION FOR THE PROFESSION: The proper use of Artificial Intelligence technologies can enhance the quality of patient care, alleviate the workload, increase patient and staff satisfaction and foster new perspectives on acceptance. With their integration into clinics, a patient-centred care environment will emerge, improving patient safety, outcomes and overall well-being. Thus, the anxieties of nurses and students towards artificial intelligence technologies will decrease, and their readiness will increase. PATIENT OR PUBLIC CONTRIBUTION: No Patient or Public Contribution.

Indexed as

AnxietyArtificial IntelligenceNursing Staff, HospitalStudents, NursingAdultAttitude of Health PersonnelCross-Sectional StudiesFemaleHumansMaleSurveys and QuestionnairesYoung Adultartificial intelligencenursenurse candidate

Identifiers

PMID39558522
PMCPMC13569175

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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.