Currents in pharmacy teaching & learning · 2026
AI acceptance and behavioral intention in pharmacy education: Scale development, psychometric validation, and correlates.
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Safwan Jihan, Dabbous Mariam, El Bakri Mona, Essa Reem, Fahs Iqbal, Rahal Mohamad, Sakr Fouad
Аннотация
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.
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.