Artificial intelligence attitudes, presenteeism, and work engagement among nurses: a structural equation modeling approach.
- 1Department of Nursing, College of Applied Medical Sciences, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia.
- 2Department of Curriculum and Instruction, College of Education, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia.
- 3Educational Psychology and Statistics Department, Faculty of Education, Al-Azhar University, Dakahlia, Egypt.
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, p < 0.001) and positively predicted work engagement (β = 0.436, p < 0.001), while presenteeism negatively predicted engagement (β = -0.250, p < 0.001). Presenteeism significantly and partially mediated this relationship (indirect β = 0.092, 95% CI [0.065, 0.123]), with the model explaining approximately 33.2% of variance in engagement. Configural, metric, and structural invariance was confirmed across Egyptian and Saudi nurses.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.
Related
- Curriculum satisfaction and pre-service teachers’ social–emotional competencies: the serial mediation role of artificial intelligence anxiety and learning engagement
- Artificial Intelligence Readiness in Nursing: A Scoping Review of Knowledge, Attitudes, Practice, and Emerging Evidence on Patient Safety Culture
- Patient engagement, acceptability, and preference of artificial intelligence versus human coaching for diabetes prevention
- The impact of vibe coding on students’ programming self-efficacy and attitudes toward artificial intelligence
- Survey of Physician Attitudes on Artificial Intelligence
BibTeX
@article{abdallah2026artificial,
title = {{Artificial intelligence attitudes, presenteeism, and work engagement among nurses: a structural equation modeling approach.}},
author = {Darelglal Ahmed Gassmelseed Abdallah and Majed A Alsharidah and Ashraf Ragab Ibrahim and Mohamed Ali Nemtallah},
journal = {Frontiers in psychology},
year = {2026},
month = oct,
doi = {10.3389/fpsyg.2026.1902196},
url = {https://europepmc.org/article/MED/42952542},
note = {CC BY},
}
RIS
TY - JOUR
TI - Artificial intelligence attitudes, presenteeism, and work engagement among nurses: a structural equation modeling approach.
AU - Darelglal Ahmed Gassmelseed Abdallah
AU - Majed A Alsharidah
AU - Ashraf Ragab Ibrahim
AU - Mohamed Ali Nemtallah
PY - 2026
DA - 2026/10/14
JO - Frontiers in psychology
DO - 10.3389/fpsyg.2026.1902196
UR - https://europepmc.org/article/MED/42952542
AB - 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, p < 0.001) and positively predicted work engagement (β = 0.436, p < 0.001), while presenteeism negatively predicted engagement (β = -0.250, p < 0.001). Presenteeism significantly and partially mediated this relationship (indirect β = 0.092, 95% CI [0.065, 0.123]), with the model explaining approximately 33.2% of variance in engagement. Configural, metric, and structural invariance was confirmed across Egyptian and Saudi nurses.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.
SN - 1664-1078
ER -