With the increasing prevalence of generative artificial intelligence use, addiction behaviors toward this technology have begun to attract the interest of researchers. Furthermore, addressing the multidimensional structure of generative artificial intelligence addiction through context-specific measurement tools can provide significant contributions for both researchers and practitioners. This study aims to adapt the multidimensional Generative Artificial Intelligence Dependency Scale (GAIDS) for a Turkish sample and examine its psychometric properties. The research sample consists of a total of 411 Turkish participants, comprising 341 women and 70 men. Confirmatory factor analysis validated the three-factor structure consistently with the original scale: Cognitive Preoccupation, Negative Consequences, and Withdrawal symptoms. The GAIDS exhibited a high level of internal consistency (α = 0.88; ω = 0.89). Correlation analyses conducted to examine criterion validity revealed significant positive relationships between the GAIDS and the Short Form of Young’s Internet Addiction Test and the Artificial Intelligence Chatbot Addiction Scale. These findings indicate that the Turkish adaptation of the GAIDS is a valid and reliable measurement tool for assessing generative artificial intelligence addiction.
Seki et al. (Wed,) studied this question.