Related Experiment Video
Updated: Oct 1, 2026
Problem-Solving Before Instruction (PS-I): A Protocol for Assessment and Intervention in Students with Different Abilities
Published on: September 11, 2021
AI acceptance and behavioral intention in pharmacy education: Scale development, psychometric validation, and
Jihan Safwan1, Mariam Dabbous2, Mona El Bakri3
1School of Pharmacy, Lebanese International University, Beirut, Lebanon.; INSPECT-LB: Institut National de Santé Publique, d'Épidémiologie Clinique et de Toxicologie-Liban, Beirut, Lebanon; Aging Research Team, Center for Epidemiology and Research in POPulation health (CERPOP), Université de Toulouse (formerly UPS - Toulouse III), Inserm, 31000 Toulouse, France.
Introduction:
Artificial intelligence (AI) is transforming healthcare and pharmacy practice, creating an urgent need to prepare future pharmacists for AI-enabled environments. Yet validated multidimensional tools assessing AI acceptance and behavioral intention among pharmacy students remain limited. This study developed and validated the AI Acceptance and Behavioral Intention Scale (AI-ABIS) and identified acceptance correlates.
Methods:
A cross-sectional study included pharmacy students. The AI-ABIS was developed through a Delphi process grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT). Confirmatory factor analysis, measurement invariance, reliability, validity, and linear regressions were performed.
Results:
681 students participated. CFA supported the five-factor structure, with excellent fit (CFI = 0.981; TLI = 0.973; RMSEA = 0.051; SRMR = 0.030). The AI-ABIS showed excellent internal consistency (Cronbach's α = 0.934; McDonald's ω = 0.934), scalar invariance across academic level, AI-use confidence, and pharmacy-related AI use, and established convergent and concurrent validity. In multivariable analysis, acceptance was independently predicted by very frequent AI use (B = 6.857), use purpose diversity (B = 0.914), eHealth literacy (B = 0.241), positive AI attitude (B = 0.527), trust in AI (B = 0.286), digital health readiness (B = 0.251), and ethical consciousness (B = 0.231; all P ≤ 0.001), collectively explaining 61.5% of the variance in AI acceptance (R2 = 0.615).
Conclusion:
The AI-ABIS is valid and reliable for assessing AI acceptance and behavioral intention in pharmacy education. Findings support structured, applied, ethically informed AI integration to prepare future pharmacists for AI-enabled healthcare.