Measurement tools assessing generative AI use, attitudes, reliance, dependency, and related constructs: a scoping review

Generative artificial intelligence (GenAI), including large language models (LLMs) and AI-powered conversational systems, has rapidly transformed the way individuals interact with digital technologies across diverse domains, including healthcare, education, research, and professional practice. As GenAI applications become increasingly integrated into daily activities, the assessment of individuals’ behaviors, perceptions, attitudes, reliance, and potential dependency toward these technologies has gained growing importance. However, the conceptualization and measurement of GenAI-related constructs remain heterogeneous, with various instruments developed to assess different aspects of GenAI use, acceptance, trust, reliance, dependence, literacy, and attitudes. This scoping review aims to systematically identify, map, and synthesize existing measurement instruments designed to assess generative AI use and related psychological, behavioral, and cognitive constructs. Specifically, this review will examine the characteristics, theoretical foundations, development processes, psychometric properties, and application contexts of available assessment tools. The review will address the following objectives: To identify existing measurement instruments assessing generative AI use, attitudes, reliance, dependency, trust, acceptance, literacy, and other related constructs. To describe the characteristics and conceptual domains of identified measurement tools. To summarize the development processes and psychometric evaluation methods of these instruments, including reliability, validity, and other measurement properties. To explore the populations, settings, and contexts in which these instruments have been applied. To identify gaps, limitations, and future directions for the development and validation of GenAI-related measurement tools. This scoping review will follow established methodological guidance for scoping reviews, including the Joanna Briggs Institute (JBI) methodology and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). A comprehensive search strategy will be developed and applied across relevant electronic databases to identify empirical studies reporting the development, validation, or application of measurement instruments related to generative AI. The expected outcomes of this review include a comprehensive evidence map of currently available GenAI-related measurement tools, an overview of their theoretical frameworks and psychometric characteristics, and identification of methodological gaps in existing assessment approaches. The findings will provide researchers and practitioners with guidance on selecting appropriate instruments for evaluating GenAI-related behaviors and perceptions. Furthermore, this review may inform the future development of standardized, theoretically grounded, and psychometrically robust instruments for assessing human interaction with generative AI technologies.