Evidence map›Paper›PMID 39863852›Full record

ArticleBMC nursing2025

Application of artificial intelligence in nursing practice: a qualitative study of Jordanian nurses' perspectives.

Wesam Taher Almagharbeh, Hazem AbdulKareem Alfanash, Khaldoon Aied Alnawafleh, Amal Ali Alasmari, Faris Abdelkarim Alsaraireh, Mutaz M Dreidi, Abdulqadir J Nashwan

Abstract read
PubMed Full text at PMC Publisher
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 26 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 3 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

26 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Review
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

7 authors.

Wesam Taher AlmagharbehMedical and Surgical Nursing Department, Faculty of Nursing, University of Tabuk, Tabuk, 7191, Saudi Arabia.
Hazem AbdulKareem AlfanashDepartment of Nursing Leadership and Education, Faculty of Nursing, University of Tabuk, Tabuk, 7191, Saudi Arabia.
Khaldoon Aied AlnawaflehMedical and Surgical Nursing Department, Faculty of Nursing, University of Tabuk, Tabuk, 7191, Saudi Arabia.
Amal Ali AlasmariMedical and Surgical Nursing Department, Faculty of Nursing, University of Tabuk, Tabuk, 7191, Saudi Arabia.
Faris Abdelkarim AlsarairehDepartment of Community and Mental Health Nursing, Faculty of Nursing, Mutah University, Alkarak, Jordan.
Mutaz M DreidiDepartment of Nursing, Faculty of Pharmacy, Nursing and Health Professions, Birzeit University, Ramallah, Palestine.
Abdulqadir J NashwanNursing Department, Hamad Medical Corporation, Doha, P.O. Box 3050, Qatar. anashwan@hamad.qa.ORCID http://orcid.org/0000-0003-4845-4119

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial Intelligence (AI) is increasingly applied in healthcare to boost productivity, reduce administrative workloads, and improve patient outcomes. In nursing, AI offers both opportunities and challenges. This study explores nurses' perspectives on implementing AI in nursing practice within the context of Jordan, focusing on the perceived benefits and concerns related to its integration.

methodA qualitative research approach was employed, involving semi-structured interviews with 25 nurses and 3 focus group discussions, each consisting of 7-8 participants. The data collected was coded and analyzed using thematic analysis to identify recurring patterns and key themes in the nurses' views on AI.

resultsThree major themes emerged from the analysis: (1) AI as an efficiency tool - Nurses recognized AI's ability to reduce administrative burdens and improve patient monitoring in real-time. (2) Ethical and practical concerns - Nurses raised issues regarding patient privacy, data security, and the fear that AI might replace human decision-making in care. (3) Lack of preparedness and training - There was a consensus on nurses' inadequate training in AI tools, limiting their ability to integrate AI into their practice fully.

conclusionWhile AI is seen as a valuable tool to enhance nursing productivity, several challenges still need to be addressed, particularly regarding ethical concerns and insufficient training. To ensure AI complements nursing without compromising the human element, healthcare institutions must address these issues by implementing comprehensive training programs and establishing clear ethical guidelines.

Indexed as

Artificial IntelligenceEthical concernsJordanNursing practicesQualitative studyThematic analysis

Identifiers

PMID39863852
PMCPMC11762109

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.