Currently, mental disorders are usually concep-tualized as a hidden causal factor, manifested by its symptoms. This notion rests upon the reflective latent model, which is implicitly at work every time complex symptomatology gets summarized by a single number or a categorical state. The present paper reflects on the quantita-tive, testable implications of this psychometric model and shows how its restraints are untena-ble for most mental disorders. The observed data are instead consistent with mental disorders be-ing complex dynamic systems. Instead of being treated as interchangeable measures of the same latent factor, symptoms likely act as independ-ent causal entities, directly affecting each other. In recent years, this shift in ontological stance toward psychopathology has laid a basis for adapting the network theory. Under this theory, a mental disorder is a relatively stable emergent state, which arises due to a pronounced and re-current interaction of causally linked symptoms. It is discussed how models embedded within the network theory can help provide insight into the etiopathogenesis of mental disorders and ad-dress clinical intervention. In conclusion, limits and future challenges to the network theory are discussed.
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