Symptom networks in childhood: a new approach for understanding the structure and development of psychiatric disorders

Psychiatric disorders have been traditionally considered latent dimensions or factors that are represented by a set of symptoms. However, the adequacy of this approach is being questioned because it does not account for the inter-relationships between symptoms and their dynamic causal nature. Researchers have started visualising disorders as networks of symptoms, using analytic methods akin to mapping networks of people, leading to interesting insights for classification of psychiatric disorder in adults.

Given that precursors for psychiatric disorder are evident in childhood, we propose to investigate the network of symptoms that begin in early childhood and observe their evolution in childhood and adolescence. We will investigate symptom networks in disorders such as depression and hyperactivity, symptom networks across domains to identify comorbidities, and differences in the network based on gender, exposure to maternal depression in early childhood and between non-clinical and clinical samples.

This study will establish the suitability, feasibility and utility of analysing child symptom data and determine if the method offers new insights into the aetiology and development of psychiatric disorder.