Development and validation of the conversational AI dependence scale for Chinese college students - Yuanyuan Chen; Mengyun Wang; Shujuan Yuan; Yan Zhao (Frontiers in Psychology, 2025)
Excessive dependence on Conversational artificial intelligence (CAI) can significantly impact individual adaptation and development. Given the growing need for empirical assessment, this study presents the development and psychometric validation of the CAI Dependence Scale (CAIDS), a new instrument designed to assess CAI dependence among Chinese college students. In Study 1, drawing on theories of problematic internet use (PIU) and qualitative interviews, we identified the psychological connotations and dimensions of CAI dependence. Item and exploratory factor analyses led to the development of the 20-item CAIDS, comprising four dimensions: uncontrollability, withdrawal symptoms, mood modification, and negative impacts. In Study 2, confirmatory factor analysis in a new sample validated the four-dimensional structure and demonstrated good reliability and validity. In Study 3, a current status survey revealed that the overall level of CAI dependence among college students was relatively high, with significant differences observed by gender, age, grade, income, and region. CAI dependence was a significant positive predictor of negative psychological outcomes and a significant negative predictor of subjective wellbeing. Withdrawal symptoms and negative impacts were more closely related to maladaptive indicators. The CAIDS provides a reliable and valid psychometric tool for assessing CAI dependence; additionally, further validation is required with more diverse samples and in cross-cultural contexts.