Robust Early-Warning Signals of PTSD State Transitions Across Global Longitudinal Cohorts: A Standard Coherence Fidelity Layer Analysis

This study investigates the existence of structurally invariant early-warning signals preceding state transitions in population-level post-traumatic stress trajectories. Drawing on a harmonized corpus of 24 longitudinal datasets spanning over 28,000 individuals across 14 countries and multiple trauma contexts, we apply a hybrid modeling framework integrating Standard Coherence Fidelity Layer (SCFL) operators with mixed-effects and state-space statistical methods. We identify four consistent operator-level precursors—drift acceleration, coherence deformation, rigidity gradients, and fragmentation bursts—that reliably emerge prior to non-linear transitions, with median lead times of 8–14 weeks and elevated transition hazard ratios. These signals remain stable across cultures, measurement instruments, and intervention contexts, suggesting the presence of universal dynamical structure in human coherence-state systems. The analysis is conducted exclusively at the population level using aggregated, non-clinical data. Results support the hypothesis that human state transitions exhibit geometry analogous to critical phenomena in complex systems, providing a foundation for scalable early-warning frameworks in psychological and social dynamics.