Evidence map›Paper›PMID 42952542›Full record

ArticleFrontiers in psychology2026

Artificial intelligence attitudes, presenteeism, and work engagement among nurses: a structural equation modeling approach.

Darelglal Ahmed Gassmelseed Abdallah, Majed A Alsharidah, Ashraf Ragab Ibrahim, Mohamed Ali Nemtallah

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Article in Frontiers in psychology, 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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2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Darelglal Ahmed Gassmelseed AbdallahDepartment of Nursing, College of Applied Medical Sciences, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia.
Majed A AlsharidahDepartment of Curriculum and Instruction, College of Education, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia.
Ashraf Ragab IbrahimEducational Psychology and Statistics Department, Faculty of Education, Al-Azhar University, Dakahlia, Egypt.
Mohamed Ali NemtallahEducational Psychology and Statistics Department, Faculty of Education, Al-Azhar University, Dakahlia, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: The rapid integration of artificial intelligence (AI) into healthcare has transformed clinical practice, yet the psychological mechanisms linking nurses' AI attitudes to their occupational functioning remain insufficiently understood, particularly regarding the role of presenteeism as a potential explanatory pathway. This study aimed to examine the relationships among nurses' attitudes toward AI, presenteeism, and work engagement, and to test the mediating role of presenteeism within a Job Demands-Resources framework. Methods: A cross-sectional correlational design was employed, with data collected from 806 hospital nurses across Saudi Arabia and Egypt using the AI Attitude Scale for Nurses, the Presenteeism Scale in Nursing, and the Utrecht Work Engagement Scale. Data were analyzed via structural equation modeling with bootstrapped mediation testing (2,000 resamples) and multi-group invariance analysis. Results: Following the exclusion of four multivariate outliers, the final analytic sample comprised 802 nurses. The hypothesized model demonstrated good fit (CFI = 0.981, RMSEA = 0.068). AI attitude significantly and negatively predicted presenteeism (β = -0.366, Discussion: These associational findings suggest that more favorable AI attitudes are linked to lower presenteeism and stronger engagement, offering preliminary guidance for nursing management and healthcare digitalization policies pending longitudinal confirmation.

Indexed as

artificial intelligence attitudesJob Demands-Resources modelnursespresenteeismstructural equation modelingwork engagement

Identifiers

PMID42952542
PMCPMC13713286

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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.