Evidence map›Paper›PMID 40809301›Full record

ArticleSAGE open nursing

The Impact of Artificial Intelligence Attitudes and Acceptance on Critical Thinking Motivation among Nursing Students in Saudi Arabia.

Ayman Mohamed El-Ashry, Nagla Saleh Al Saleh, Nora Ghalib AlOtaibi, Turki Zuhaymil Almutairi, Lujain Adel Sallam, Muhanna M Alnassar, Khloud Abdulhadi Alshehri, Sahar Abdulkarim Al-Ghareeb, Raiza Abdullah Al-Otaibi, Wejdan Munahi Almutairi and 2 more

Abstract read
In one paragraph

Article in SAGE open nursing. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–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

11 citing papers in PubMed.

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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

12 authors.

Ayman Mohamed El-AshryPsychiatric and Mental Health Nursing, Faculty of Nursing, Alexandria University, Alexandria Governorate, Egypt.ORCID https://orcid.org/0000-0001-7718-4942
Nagla Saleh Al SalehDepartment of Community Nursing, College of Nursing, Imam Abdulrahman Bin Faisal University, Dammam, Eastern Province, Saudi Arabia.
Nora Ghalib AlOtaibiDepartment of Community Nursing, College of Nursing, Imam Abdulrahman Bin Faisal University, Dammam, Eastern Province, Saudi Arabia.ORCID https://orcid.org/0000-0003-3383-2631
Turki Zuhaymil AlmutairiDepartment of Medical and Surgical, College of Nursing, Qassim University, Buraydah, Al Qassim, Saudi Arabia.ORCID https://orcid.org/0009-0006-3472-1772
Lujain Adel SallamMedical Surgical Department Nursing, King Abdulaziz University, Jeddah, Saudi Arabia.ORCID https://orcid.org/0000-0002-3766-9520
Muhanna M AlnassarDepartment of Medical Surgical, College of Nursing, King Saud University, Riyadh, Riyadh Province, Saudi Arabia.ORCID https://orcid.org/0009-0003-7898-9226
Khloud Abdulhadi AlshehriMaster in Psychiatric and Mental Health Nursing, King Abdulaziz University, Jeddah, Saudi Arabia.
Sahar Abdulkarim Al-GhareebFundamentals of Nursing Department, College of Nursing, Imam Abdulrahman Bin Faisal University, Dammam, Eastern Province, Saudi Arabia.ORCID https://orcid.org/0009-0007-6844-4539
Raiza Abdullah Al-OtaibiFundamentals of Nursing Department, College of Nursing, Imam Abdulrahman Bin Faisal University, Dammam, Eastern Province, Saudi Arabia.
Wejdan Munahi AlmutairiCollege of Nursing, Qassim University, Buraydah, Al Qassim, Saudi Arabia.
Sameer A AlkubatiDepartment of Medical Surgical Nursing, College of Nursing, University of Ha'il, Ha'il City, Saudi Arabia.ORCID https://orcid.org/0000-0001-8538-5250
Mona Metwally El-SayedPsychiatric and Mental Health Nursing, Faculty of Nursing, Alexandria University, Alexandria Governorate, Egypt.ORCID https://orcid.org/0000-0002-6495-508X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: As Saudi Arabia advances its Vision 2030 agenda, which emphasizes artificial intelligence (AI) integration in healthcare and education, understanding students' acceptance of AI in academic settings is increasingly important. Objective: To examine the relationship between nursing students' attitudes toward AI, perceived usefulness, perceived usability, and their critical thinking motivation. Methods: A multicenter cross-sectional correlational study was conducted across three Saudi universities. Data were collected from 390 undergraduate nursing students using the General Attitudes towards AI Scale, the technology acceptance model questionnaire, and the critical thinking motivation scale. Analysis included Pearson correlations and multiple linear regression. Results: Students reported positive attitudes toward AI, with strong correlations among AI attitude, usefulness, and usability ( Conclusion: Acceptance and perceived usability of AI tools are positively associated with critical thinking motivation in nursing students. These findings underscore the potential of AI to support cognitive skill development in nursing education. Educators should integrate AI early in nursing curricula, provide structured training, and frame AI as a support tool in clinical decision-making. Doing so can foster both critical thinking and digital competence among future nurses.

Indexed as

AI attitudesAI usefulnesscritical thinking motivationnursing studentsSaudi Arabia

Identifiers

PMID40809301
PMCPMC12344321

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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 OpenQuestion graph.