Evidence map›Paper›PMID 42612089›Full record

ArticleJMIR nursing2026

Factors Influencing Nursing Internship Students' Readiness to Use AI: Cross-Sectional Study Using Neural Network Analysis.

Sameer A Alkubati, Wesam T Almagharbeh, Talal A Alqalah, Basma Salameh, Hamdan Albaqawi, Awatif M Alrasheeday, Abdulhafith Alharbi, Layla Alshammari, Bushra Alshammari, Eddieson Pasay-An and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in JMIR 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.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Sameer A AlkubatiDepartment of Medical Surgical Nursing, College of Nursing, University of Ha'il, Hail University, Hail, Ha'il Region, 00966, Saudi Arabia, 966 506575284.ORCID http://orcid.org/0000-0001-8538-5250
Wesam T AlmagharbehMedical Surgical Nursing Department, University of Tabuk, Tabuk, Tabuk Region, Saudi Arabia.ORCID http://orcid.org/0000-0002-8435-1208
Talal A AlqalahDepartment of Medical Surgical Nursing, College of Nursing, University of Ha'il, Hail University, Hail, Ha'il Region, 00966, Saudi Arabia, 966 506575284.ORCID http://orcid.org/0000-0003-4667-9293
Basma SalamehDepartment of Nursing, Arab American University, Jenin, Palestinian Territory.ORCID http://orcid.org/0000-0003-1372-7199
Hamdan AlbaqawiDepartment of Medical Surgical Nursing, College of Nursing, University of Ha'il, Hail University, Hail, Ha'il Region, 00966, Saudi Arabia, 966 506575284.ORCID http://orcid.org/0000-0001-9749-9669
Awatif M AlrasheedayNursing Administration Department, Faculty of Nursing, University of Hail, Hail, Saudi Arabia.ORCID http://orcid.org/0000-0003-1157-8185
Abdulhafith AlharbiDepartment of Psychiatric and Mental Health Nursing, College of Nursing, University of Hail, Hail, Saudi Arabia.ORCID http://orcid.org/0000-0003-3490-3315
Layla AlshammariDepartment of Medical Surgical Nursing, College of Nursing, University of Ha'il, Hail University, Hail, Ha'il Region, 00966, Saudi Arabia, 966 506575284.ORCID http://orcid.org/0009-0004-9559-9024
Bushra AlshammariDepartment of Medical Surgical Nursing, College of Nursing, University of Ha'il, Hail University, Hail, Ha'il Region, 00966, Saudi Arabia, 966 506575284.ORCID http://orcid.org/0000-0001-9631-8870
Eddieson Pasay-AnFundamental of Nursing Department, College of Nursing, King Khalid University, Abha, Saudi Arabia.ORCID http://orcid.org/0000-0003-1257-3175
Anwar AbdulkareemArtificial Intelligence and Data Science Department, College of Computer Science and Engineering, College of Computer Science and Engineering, University of Hail, Hail, Saudi Arabia.ORCID http://orcid.org/0009-0004-3191-1816
Shimmaa Mohammed ElsayedCritical Care and Emergency Nursing Department, Faculty of Nursing, Damanhour University, El Beheira, Egypt.ORCID http://orcid.org/0000-0002-2065-7494

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Enhancing nursing students' awareness, attitudes, beliefs, and preparedness toward AI may help improve their health care knowledge and practice. Objective: This study aimed to assess nursing students' attitudes, perceptions, self-efficacy, barriers, and anxiety, which influence their readiness to adopt AI in nursing practice. Methods: This study used a cross-sectional, correlational design. Data were collected from 307 nursing internship students using an 8-part, self-administered questionnaire. Results: Increased self-efficacy with computers was correlated with decreased barriers to accessing AI technology, lower computer anxiety scale scores ( Conclusions: Several contributing factors influenced nursing students' readiness to embrace AI, with barriers, attitudes, and perceptions emerging as the most consistent, whereas self-efficacy and anxiety may play indirect roles. To improve the adoption of AI among nursing students, such factors should be dealt with in such educational programs; an interrelated adoption of AI in nursing practice is expounded as a more favorable environment.

Indexed as

Artificial IntelligenceNeural Networks, ComputerStudents, NursingAdultCross-Sectional StudiesFemaleHumansMaleSelf EfficacySurveys and QuestionnairesAIanxietyattitudebarriersnursing internship studentsperceptionreadinessself-efficacy

Identifiers

PMID42612089
PMCPMC13484946

What OpenQuestion holds

Textmetadata
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.