Evidence mapPaperPMID 42401846Full record

ArticleBMC nursing2026

Nurses' knowledge, attitudes, and perceived challenges toward artificial intelligence applications in patient care: a descriptive-analytical cross-sectional study.

Rehab Ragab Bayoumi Elsayed, Ahmed Mohamed Elmarakby Nagy, Eman Sobhy El-Said Hussein, Reham Adel Ebada Elsayed, Reda Mohamed El-Sayed Ramadan

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Article in BMC nursing, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Rehab Ragab Bayoumi ElsayedMedical Surgical Nursing Department, Faculty of Nursing, Zagazig University, Zagazig, 44519, Egypt.ORCID http://orcid.org/0000-0002-9564-2801
Ahmed Mohamed Elmarakby NagyMedical Surgical Nursing Department, Faculty of Nursing, Zagazig University, Zagazig, 44519, Egypt.ORCID http://orcid.org/0009-0007-5904-2220
Eman Sobhy El-Said HusseinMedical Surgical Nursing Department, Faculty of Nursing, Ain Shams University, Cairo11566, Egypt.ORCID http://orcid.org/0000-0001-9864-7803
Reham Adel Ebada ElsayedMedical Surgical Nursing Department, Faculty of Nursing, Ain Shams University, Cairo11566, Egypt. dr.reham.adel@nursing.asu.edu.eg.ORCID http://orcid.org/0000-0001-9428-2413
Reda Mohamed El-Sayed RamadanMedical Surgical Nursing Department, Faculty of Nursing, Ain Shams University, Cairo11566, Egypt.ORCID http://orcid.org/0000-0002-1430-7658

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) is increasingly being integrated into healthcare systems; however, nurses' knowledge, attitudes, and perceived challenges play a crucial role in its adoption in patient care. This study aimed to assess nurses' knowledge, attitudes, and perceived challenges toward AI, examine the relationships among these variables, and explore their associations with demographic characteristics and prior AI training.

methodsA descriptive analytical cross-sectional study was conducted among 107 nurses working in intensive care, medical, and surgical units at Zagazig University Hospital. A purposive sampling technique was used. Data were collected over two months using structured instruments during morning shifts.

resultsMost participants were aged 25-34 years (55.1%), male (65.4%; reflecting the accessible sample composition), and held bachelor's degrees (68.2%), with nearly half (49.5%) having 5-10 years of clinical experience. Overall, 68.2% of nurses achieved satisfactory knowledge scores, whereas 88.8% demonstrated positive attitudes toward AI applications. Perceived challenges were mainly related to technical and ethical concerns, particularly the need for continuous system updates, cybersecurity risks, and implementation costs. A statistically significant weak negative correlation was found between nurses' knowledge and attitudes toward AI (r = -0.195, p = 0.044). No significant correlations were observed between knowledge and perceived challenges (r = -0.162, p = 0.095) or between attitudes and perceived challenges (r = 0.142, p = 0.145). Previous AI-related training was significantly associated with more positive attitudes toward AI (p = 0.019), whereas no significant associations were found with knowledge or perceived challenges. Educational level, workplace, and years of experience were not significantly associated with nurses' knowledge, attitudes, or perceived challenges.

conclusionNurses demonstrated a satisfactory knowledge and generally positive attitudes toward AI applications in patient care, while perceiving moderate implementation challenges. Although previous AI-related training was associated with more positive attitudes, no significant associations were found with knowledge or perceived challenges. The weak negative correlation between knowledge and attitudes suggests that greater awareness of AI may be accompanied by increased concerns regarding its use. Further educational initiatives are needed to enhance nurses' preparedness for AI integration in clinical practice.

Indexed as

Artificial IntelligenceAttitudesKnowledgeNursingPerceived challenges

Identifiers

PMID42401846
PMCPMC13332585

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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 Socratic graph.