The DOI matches its Crossref record; the references it cites are not checked yet.
Assessment of the relationship between executive Nurses’ leadership Self-Efficacy and medical artificial intelligence readiness
Abstract
Aims This study aims to assess the relationship between management nurses' leadership self-efficacy and medical artificial intelligence readiness.Methods The research was conducted using a descriptive-correlational design. The sample of the study consisted of 196 management nurses working in public, private, and educational research hospitals in Gaziantep, Turkey. The data collection tools included the Personal Information Form, the Leadership Self-Efficacy Scale, and the Medical Artificial Intelligence Readiness Scale.Results The majority of the participants in the research were female (71.4 %), married (80.1 %) and graduates of a bachelor's or higher degree in nursing (74.5 %), had 16 years or more of work experience in the profession (39.3 %), and worked during the day shift (75.5 %). Among the participating management nurses, those who were single had a significantly higher mean score in the cognition subscale and the total score of medical artificial intelligence readiness (p < 0.05). The management nurses working in shifts had significantly higher mean scores in the cognition and ability subscales, as well as the total score of medical artificial intelligence readiness (p < 0.05). The management nurses who received leadership/management-related training after their undergraduate education had a significantly higher mean score in the cognition subscale (p < 0.05). Furthermore, there was a significant relationship (p < 0.05) between leadership self-efficacy, medical artificial intelligence readiness, and their subscales, concerning following and finding artificial intelligence applications useful, as well as informing team members about artificial intelligence applications.Conclusions In the research, it was determined that the leadership self-efficacy of the manager nurses was at a good level and that their artificial intelligence readiness was at a medium level in terms of cognition, skill, foresight and ethics while presenting their professional knowledge. A positive and significant relationship was found between leadership self-efficacy and medical artificial intelligence readiness.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The MAIRS-MS has demonstrated validity and applicability in broader healthcare education settings, including nursing.
“The MAIRS-MS instrument, initially created by Karaca, has demonstrated its validity and applicability in broader healthcare education settings, including nursing [23, 24].”
Citations
The citation lists haven’t been fetched yet
References 28 · Cited by 30
Research works printed but not linked: 8
- Josea, 2022, Artificial intelligence and nursing, Specialusis Ugdymas., 1, 6234
- Kuglitsch, 2022, Artificial intelligence for disaster risk reduction: opportunities challenges, and prospects, Bulletin., 71, 30
- Önder, 2020, Artificial intelligence strategies and Türkiye, ULİSA12., 12, 1
- Akgün, 2019, Mobile apps in mental health: a systematic review of efficacy, Current Approaches Psychiatry., 11, 519
- Kılbaş, 2023, Sample selection and power analysis in scientific research, J. Biotechnology and Strategic Health Res., 7, 1
- S. Büyüköztürk, Sosyal Bilimler İçin Veri Analizi El Kitabı (21. baskı). [Manual of data analysis for social sciences (21st ed.)]. Pegem Publishing, (2018). https://scholar.google.com/scholar_lookup?hl=en&publication_year=2015&author=%C5%9E+B%C3%BCy%C3%BCk%C3%B6zt%C3%BCrk&title=Sosyal+Bilimler+%C4%B0%C3%A7in+Veri+Analizi+El+Kitab%C4%B1.
- Cansoy, 2018, Adapting leadership self-efficacy scale into turkish culture: validity and reliability study, Pesa Int. J. Social Studies., 4, 331
- Elsayed, 2021, Nurse managers’ perception and attitudes toward using artificial intelligence technology in health settings, Assiut Scientific Nursing J., 9, 182
Metadata
- Authors
- Eminoğlu, A., & Çelikkanat, Ş.
- Affiliations
- Gaziantep İslam Bilim ve Teknoloji Üniversitesi (TR)
- Corresponding author
- Eminoğlu, Ayşe
- Venue
- International Journal of Medical Informatics
- Publisher
- Elsevier BV
- Published
- 2024-04
- Volume
- 184
- Pages
- 105386
- ISSN
- 1386-5056 (ISSN-L)
- OpenAlex
- W4391957840
- Cited by
- 30
- References
- 28
- Citations by year
- 2026: 12 · 2025: 16 · 2024: 2
- FWCI
- 2.81
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- International Journal of Medical Informatics (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Nursing › Leadership and Management › Healthcare Education and Workforce Issues
- Health Sciences › Nursing › Issues, ethics and legal aspects › Nursing Education, Practice, and Leadership
- Keywords
- leadership self-efficacy, nursing management, nursing leadership training, shift work
- MeSH terms
- Artificial Intelligence, Cognition, Female, Humans, Leadership, Male, Nurses, Surveys and Questionnaires, Self Efficacy
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
