Development and validation of an artificial intelligence awareness, knowledge, attitude, and confidence survey among physiotherapy students

Abstract

Objectives: This study aimed to develop and validate a scale assessing physiotherapy students’ knowledge, awareness, attitudes, and confidence toward artificial intelligence (AI), and to examine associations with demographic variables. Material and Method: A cross-sectional survey was conducted in Istanbul, Türkiye (February 2024-May 2025), in accordance with CROSS and CHER RIES guidelines. Item generation involved a literature review and expert feedback. A pilot study with 150 students evaluated clarity, content validity, and reliability. Based on analysis, 22 items across three subscales (knowledge, awareness, attitude-confidence) were retained. The final survey was distributed via Google Forms to 300 physiotherapy students from four universities. Reliability was determined using Cronbach’s alpha, and construct validity was assessed via confirmatory factor analysis (CFA) and structural equation modelling (SEM). Results: The scale showed high internal consistency (α = 0.914), with subscale alphas between 0.689 and 0.892. CFA and SEM demonstrated acceptable model fit (CFI = 0.916, TLI = 0.904, RMSEA = 0.070). Knowledge scores were relatively low, whereas awareness and confidence were higher. Age, aca demic year, and prior technical background significantly influenced knowledge and awareness, while attitudes and confidence differed by institution. Conclusion: The developed instrument is reliable and valid for evaluating AI-related perceptions in physiotherapy education. Results emphasize the need for structured AI literacy and ethics training to align high confidence and awareness with actual knowledge.