From Many to One to Many-the Search for Causes of Psychiatric Illness.

Abstract

The search for the causes of medical and psychiatric disorders has gone through 3 historical phases. First, up until the mid-19th century, causes of illness were anecdotally recorded from individual cases, resulting in long and diverse lists for all disorders. Second, in the latter half of the 19th century, with the use of microbiological methods, single causes were found for many infectious diseases that led to specific diagnostic tests, effective preventions, and, in some cases, treatments. Causal thinking in medicine shifted from the earlier multicausal approaches to monocausal theories of etiology. Indeed, proving monocausal etiology became a way to establish the legitimacy of a disorder. Through the writings of Kahlbaum and Hecker, psychiatry was deeply influenced by this monocausal perspective, the importance of which was substantially amplified by a twist of fate: the increasing clinical importance of general paresis of the insane throughout the 19th century and the eventual proof that it too was a monocausal condition. However, in the mid-20th century, the third phase began. With decreasing deaths from infectious diseases, epidemiology and clinical medicine shifted to a chronic disease model in which paradigmatic disorders, such as cancer and cardiovascular disease, were shown to be highly multicausal. Biostatistics evolved from deterministic to probabilistic models of disease risk factors. Paradoxically, at this time, biological psychiatry, then rising to dominance in American psychiatry, vigorously pursued monocausal theories, first of neurochemical origin and then of genetic origin. We were trying to establish the legitimacy of our field by pursuing an outmoded model-that "real" diseases are monocausal. Despite ample evidence to the contrary, monocausal thinking continues to influence our field, for example, in the popular but improbable view that we can, with a few key advances, move easily from descriptive to etiologically based diagnoses.