Evidence map›Paper›PMID 39696341›Full record

ArticleBMC medical education2024

Demographic factors, knowledge, attitude and perception and their association with nursing students' intention to use artificial intelligence (AI): a multicentre survey across 10 Arab countries.

Omar Al Omari, Muna Alshammari, Wafa Al Jabri, Asma Al Yahyaei, Khalid Abdullah Aljohani, Hala Mohamed Sanad, Mohammed Baqer Al-Jubouri, Ibrahim Bashayreh, Mirna Fawaz, Mohammed ALBashtawy and 7 more

Abstract readMulticenter Study
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC medical education, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 1 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

33 citing papers in PubMed, 1 synthesis or guideline 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

17 authors.

Omar Al OmariCollege of Nursing, Sultan Qaboos University, Al-Khoudh, P.O.Box 66, Postal Code 123, Muscat, Oman. o.alomari@squ.edu.om.ORCID http://orcid.org/0000-0002-7614-1729
Muna AlshammariCollege of Nursing, Public Authority for Applied Education and Training, Shuwaikh Industrial complex, Kuwait.
Wafa Al JabriCollege of Nursing, Sultan Qaboos University, Al-Khoudh, P.O.Box 66, Postal Code 123, Muscat, Oman.
Asma Al YahyaeiCollege of Nursing, Sultan Qaboos University, Al-Khoudh, P.O.Box 66, Postal Code 123, Muscat, Oman.
Khalid Abdullah AljohaniNursing College, Community Health Department, Taibah University, Medina, Saudi Arabia.
Hala Mohamed SanadCollege of Health and Sport Science, Department of Nursing, University of Bahrain, Zallaq, Bahrain.
Mohammed Baqer Al-JubouriCollege of Nursing, University of Baghdad, Baghdad, Iraq.
Ibrahim BashayrehNursing Department, Fatima College of Health Sciences, Al Ain Campus, Abu Dhabi, UAE.
Mirna FawazCollege of Health Sciences, American University of the Middle East, Egaila, Kuwait.
Mohammed ALBashtawyPrincess Salma Faculty of Nursing, Al Al-Bayt University, Mafraq, Jordan.
Abdullah AlkhawaldehPrincess Salma Faculty of Nursing, Al Al-Bayt University, Mafraq, Jordan.
Jamal QaddumiFaculty of Medicine and Health Sciences, An-Najah National University, Nablus, Palestine.
Samah Anwar ShalabyFaculty of Nursing, Alexandria University, Alexandria, Egypt.
Haitham Mokhtar AbdallahFaculty of Nursing, Alexandria University, Alexandria, Egypt.
Loai AbuSharourHealth Science Faculty of Health Sciences, Higher Colleges of Technology, Ras Al Khaimah, UAE.
Mohammad Al QadirePrincess Salma Faculty of Nursing, Al Al-Bayt University, Mafraq, Jordan.
Maen AljezawiPrincess Salma Faculty of Nursing, Al Al-Bayt University, Mafraq, Jordan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) is becoming increasingly important in healthcare, with a significant impact on nursing practice. As future healthcare practitioners, nursing students must be prepared to incorporate AI technologies into their job. This study aimed to explore the associated factors with nursing students' intention to use AI.

methodsDescriptive cross-sectional multi-centre design was used. A convenience sample of 1713 university nursing students from Bahrain, Egypt, Iraq, Jordan, Kuwait, Lebanon, Oman, Palestine, Saudi Arabia and the United Arab Emirates completed a self-reported online instrument divided into five sections covering: (1) demographic sheet, (2) knowledge, (3) attitude, (4) perception and (5) intention questionnaire.

resultsMost nursing students in Arab countries have moderate levels of knowledge, attitude, perception and intention towards the use of AI. There was a significant positive association between knowledge, attitude, perception and intention towards the use of AI. A multivariate regression analysis revealed that understanding of AI technologies, self-perception as tech-savvy, age, clinical performance in previous semesters and knowledge of AI were significant and positively correlated with intention.

conclusionThe findings highlight the importance of targeted educational interventions and customised strategies to support AI integration within nursing education settings across Arab countries, equipping future nurses with the necessary skills and knowledge to use AI effectively in their practice.

Indexed as

Artificial IntelligenceHealth Knowledge, Attitudes, PracticeIntentionStudents, NursingAdultAttitude of Health PersonnelCross-Sectional StudiesEgyptFemaleHumansIraqKuwaitLebanonMaleMiddle EastOmanArtificial IntelligenceAttitudeIntentionKnowledgeNursing studentsPerception

Identifiers

PMID39696341
PMCPMC11653676

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.