Generative artificial intelligence addiction is prospectively associated with psychotic-like experiences: Evidence from a two-wave longitudinal mediation and network study

Objectives With the rapid adoption of generative artificial intelligence (GAI) in learning, work, and daily life, concerns have grown about its mental health implications. Evidence beyond affective outcomes is limited. This study examined whether GAI addiction is prospectively associated with psychotic-like experiences and assessed indirect associations involving information overload and rumination. Methods A two-wave longitudinal design was used with 582 adolescents and young adults. GAI addiction, information overload, rumination, and psychotic-like experiences were assessed at baseline and 1-month follow-up. Serial mediation models tested prospective indirect associations from GAI addiction to later psychotic-like experiences via information overload and rumination, and cross-lagged panel network (CLPN) analysis examined cross-lagged associations among individual items. Results Baseline GAI addiction was significantly associated with psychotic-like experiences at follow-up ( β = 0.19, p < .001). Rumination showed a significant mediating effect. Information overload was not an independent mediator, but it contributed to a significant serial pathway through rumination. CLPN analysis indicated that baseline psychotic-like experiences were relatively strongly associated with rumination-related nodes at T2. Conclusions The prospective association between GAI addiction and psychotic-like experiences may partly involve cognitive processes, particularly rumination. These findings provide longitudinal evidence on potential mental health correlates of generative AI use.