Assessing nurses’ attitudes toward artificial intelligence in Kazakhstan: psychometric validation of a nine-item scale

BackgroundArtificial intelligence (AI) is increasingly integrated into healthcare, yet the attitudes and knowledge of nurses, who are the key mediators of AI implementation, remain underexplored. This study aimed to evaluate the psychometric properties of a previously validated nine-item scale measuring nurses’ knowledge and attitudes toward AI and to describe preliminary findings from primary healthcare centre (PHC) nurses in Almaty, Kazakhstan.MethodsA cross-sectional survey was conducted among 400 nurses from eight randomly selected PHCs in Almaty. The English version of the questionnaire assessing sociodemographic characteristics, knowledge of AI, and attitudes toward AI among nurses was translated and adapted in Kazakh and Russian languages. Exploratory factor analysis (EFA) was performed on 60% of the sample (n = 240) to identify the factor structure, followed by confirmatory factor analysis (CFA) on the remaining 40% (n = 160). Internal consistency, composite reliability, and average variance extracted were calculated to evaluate reliability and convergent validity.ResultsMost participants were female (94%, n = 376), aged 20–39 years (51.5%,n = 206), and held post-secondary medical college education (52.5%,n = 210). About one third of the participants reported having no general awareness of AI, and nearly half (45.8%, n = 183) reported little to no understanding of the use of AI in nursing. EFA supported a two-factor structure “Operational and Workforce Impact” and “Clinical Benefits” explaining 72.7% of the variance. CFA confirmed the model with good model fit indices and high internal consistency (Cronbach’s α overall=0.94; subscales 0.92 and 0.89). A substantial proportion of nurses recognized AI’s potential to enhance patient care, decision-making, and workflow efficiency, though 38.8% were reluctant to adopt AI personally.ConclusionsThe validated scale demonstrated excellent psychometric properties in Kazakhstani context and has the potential to be used more broadly across the Central Asian region. While nurses exhibited positive perceptions of AI’s clinical and operational benefits, gaps in specific knowledge suggest a need for targeted educational interventions.