Validating the architecture of cognitive distortions in Russian discourse using artificial intelligence and bootstrap analysis

Automated classification revealed hierarchically organized co-occurrence network in Russian-language discourse with personalization as primary hub and all-or-nothing/catastrophizing forming densely connected core. Findings suggest cluster-based interventions may be effective for Russian-speaking populations, though cross-cultural replication is required to distinguish universal mechanisms from cultural patterns. Cross-sectional design and single-language sample limit causal inference and generalizability.