Mental health progress requires causal diagnostic nosology and scalable causal discovery

Abstract

Nine hundred and seventy million individuals across the globe are estimated to carry the burden of a mental disorder. Limited progress has been achieved in alleviating this burden over decades of effort, compared to progress achieved for many other medical disorders. Progress on outcome improvement for all medical disorders, including mental disorders, requires research capable of discovering causality at sufficient scale and speed, and a diagnostic nosology capable of encoding the causal knowledge that is discovered. Accordingly, the field's guiding paradigm limits progress by maintaining: (a) a diagnostic nosology (DSM-5) with a profound lack of causality; (b) a misalignment between mental health etiologic research and nosology; (c) an over-reliance on clinical trials beyond their capabilities; and (d) a limited adoption of newer methods capable of discovering the complex etiology of mental disorders. We detail feasible directions forward, to achieve greater levels of progress on improving outcomes for mental disorders, by: (a) the discovery of knowledge on the complex etiology of mental disorders with application of Causal Data Science methods; and (b) the encoding of the etiological knowledge that is discovered within a causal diagnostic system for mental disorders.

Keywords: causality; diagnosis; etiology; mental health; methodology; outcomes; psychiatry.

FIGURE 1

(A) Causal structure implied by DSM. (B) Application of implied causal structure for treatment.

FIGURE 2

Causal data science vs. association methods for determining causal structure.

FIGURE 3

A causal model for the diagnosis of myocardial infarction.

FIGURE 4

A causal model for the diagnosis of a disorder of depressed mood.