Evidence map›Paper›PMID 39086074›Full record

ArticleJournal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing2025

Can digital leadership transform AI anxiety and attitude in nurses?

Sinan Tarsuslu, Ferhat Onur Agaoglu, Murat Bas

Abstract read
In one paragraph

Article in Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 2 pooled it
–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

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

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  7. From Crisis Response to Recovery: A Two-Wave Qualitative Study of Nursing Leadership Trajectories in Italy (2020-2025).Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing · 2026
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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.

Sinan TarsusluHealth Services School, Erzincan Binali Yildirim University, Erzincan, Turkey.ORCID 0000-0003-0018-1430
Ferhat Onur AgaogluDepartment of Health Management, Erzincan Binali Yildirim University, Erzincan, Turkey.ORCID 0000-0001-5366-6154
Murat BasDepartment of Health Management, Erzincan Binali Yildirim University, Erzincan, Turkey.ORCID 0000-0002-9479-4571

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe lack of artificial intelligence applications in nursing education and the nursing profession in Turkey and the need for strategies for integrating artificial intelligence into the nursing profession continues. At this point, there is a need to transform the negative attitudes and anxiety that may occur in nurses.

objectivesIt was aimed to reorganize the professional transformation in this parallel by analyzing the effect of digital leadership perception, which is explained as how nurses approach digital technologies and innovations and their awareness of how and with which methods they can use these technologies on artificial intelligence anxiety and attitude in the nursing profession.

designThe study was designed as descriptive, correlational, and cross-sectional.

participantsThe research was conducted by reaching 439 nurses working in hospitals operating in three different regions of Turkey by simple random sampling method.

methodsIn the first part of the data collection tool used in this study, digital leadership scale, artificial intelligence use anxiety, and artificial intelligence attitude scales were used, including questions determining the demographic information of nurses, their relationship with technology, artificial intelligence usage status and its importance in the profession.

resultsIt was determined that 29.8% of the nurses had a good relationship with technology, 66.3% knew about using artificial intelligence in health, and 27.3% wanted it to be more involved in their lives. It was determined that nurses' perceptions of digital leadership were at a medium level of 46.9% and a high level of 41.7%, 82.7% had a positive attitude towards artificial intelligence, and 82.7% had low or medium level anxiety when their artificial intelligence anxiety status was examined. There was a significant and negative relationship between digital leadership and AI anxiety (r = -0.434; p < 0.01), a significant and positive relationship between digital leadership and AI attitude (r = 0.468; p < 0.01), and a significant and negative relationship between AI attitude and AI anxiety (r = -0.629; p < 0.01). Finally, it was determined that nurses' perception of digital leadership indirectly affected AI anxiety through AI attitude (β = -0.230, 95% CI [-0.298, -0.165]).

conclusionIt is suggested that the anxiety and attitude towards artificial intelligence can be transformed positively with the effect of digital leadership, and in this parallel, the digital leadership phenomenon should be evaluated as a practical implementation strategy in integrating artificial intelligence into the nursing profession. CLINICAL RELEVANCE: Our study showed that artificial intelligence attitude has a mediating role in the indirect effect of the perception of digital leadership in nursing on AI anxiety. It was determined that nurses' digital leadership perception, artificial intelligence anxiety, and artificial intelligence attitude differed significantly with demographic variables.

Indexed as

AnxietyArtificial IntelligenceAttitude of Health PersonnelLeadershipNursing Staff, HospitalAdultCross-Sectional StudiesFemaleHumansMaleMiddle AgedSurveys and QuestionnairesTurkeyAI anxietyAI attitudeartificial intelligence in nursingdigital leadershipintegrationnursingtransformation

Identifiers

PMID39086074
PMCPMC11771702

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.