Initial Psychometric Evaluation of the Problematic Use of Generative Artificial Intelligence Scale Among Chinese...

Generative artificial intelligence (GAI) is increasingly used by school students, yet validated instruments for assessing problematic GAI use (PUGAI) in this population remain scarce. This study evaluated the psychometric properties of the Problematic Use of Generative Artificial Intelligence Scale (PUGAIS) in a large school-based sample of Chinese students. A cross-sectional survey included 19,484 students in Grades 4-9 who had used GAI. The sample was randomly split for exploratory and confirmatory factor analyses. Internal consistency, measurement invariance across sex, school type, and developmentally defined age groups, concurrent validity, latent classes, and a preliminary threshold were also examined. Following item refinement, the 8-item PUGAIS (PUGAIS-8) showed a dominant one-factor structure, although confirmatory model-fit evidence was mixed. The scale showed high internal consistency (Cronbach's α = 0.940) and measurement invariance of item thresholds and factor loadings across sex, school type, and age groups. Ordinal sensitivity analyses indicated that the item-reduction results were partly sensitive to analytic treatment, although the PUGAIS-8 showed a more favorable overall structural fit than the original 10-item specification. A substantial floor effect indicated limited differentiation at the lower end of the construct. PUGAIS-8 scores were positively associated with depressive symptoms, anxiety symptoms, insomnia symptoms, and short-video addiction (r = 0.365-0.413, all p < 0.01). Latent class analysis identified a high-score subgroup (7.2%), and an exploratory ROC analysis yielded an internally derived descriptive threshold of 20.5. Overall, the findings provide initial psychometric support for the PUGAIS-8 as a brief measure of PUGAI among Chinese school students, while indicating the need for independent replication of the item-reduction findings and further evaluation of its measurement properties and proposed threshold.