Anxiety is typically treated as a unitary construct with multiple subtypes, but its clinical presentation often reveals deeper inconsistencies — especially in clients who relapse, resist treatment, or organize their identity around suffering. This paper proposes a novel framework for understanding anxiety not as a monolithic disorder but as the emergent product of two distinct psychological axes: Safety (the present-moment felt sense of protection) and Security (the internalized belief in continuity and self-coherence). Drawing on principles from attachment theory, predictive coding, and computational psychiatry, we present these axes as measurable latent variables governing both symptom expression and identity formation.Using a state-space and Markovian framing, we model psychological behavior as transitions across the safety–security plane. We argue that therapeutic resistance, identity rigidity, and relapse are best understood as failures of state transition — not failures of will. We provide formal operationalizations of both axes, demonstrate how they can be used to inform treatment selection, and propose testable hypotheses across neurophysiology, language, and behavioral prediction. This model reframes resistance as coherence-preservation and offers a compassionate, scientifically-grounded architecture for understanding anxiety and the self.
Ahmed Zeid (Sat,) studied this question.