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

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.

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.

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.

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.