The Network Structure of Symptoms of the Diagnostic and Statistical Manual of Mental Disorders

Lynn Boschloo, Claudia D van Borkulo, Mijke Rhemtulla, Katherine M Keyes, Denny Borsboom, Robert A Schoevers, Lynn Boschloo, Claudia D van Borkulo, Mijke Rhemtulla, Katherine M Keyes, Denny Borsboom, Robert A Schoevers

Abstract

Although current classification systems have greatly contributed to the reliability of psychiatric diagnoses, they ignore the unique role of individual symptoms and, consequently, potentially important information is lost. The network approach, in contrast, assumes that psychopathology results from the causal interplay between psychiatric symptoms and focuses specifically on these symptoms and their complex associations. By using a sophisticated network analysis technique, this study constructed an empirically based network structure of 120 psychiatric symptoms of twelve major DSM-IV diagnoses using cross-sectional data of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC, second wave; N = 34,653). The resulting network demonstrated that symptoms within the same diagnosis showed differential associations and indicated that the strategy of summing symptoms, as in current classification systems, leads to loss of information. In addition, some symptoms showed strong connections with symptoms of other diagnoses, and these specific symptom pairs, which both concerned overlapping and non-overlapping symptoms, may help to explain the comorbidity across diagnoses. Taken together, our findings indicated that psychopathology is very complex and can be more adequately captured by sophisticated network models than current classification systems. The network approach is, therefore, promising in improving our understanding of psychopathology and moving our field forward.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1. Empirical network of 120 psychiatric…
Fig 1. Empirical network of 120 psychiatric symptoms.
Symptoms are represented as nodes and associations between them as edges. Node colours refer to the type of diagnosis and numbers refer to specific symptoms (see S1 Table). Green edges represent positive associations and red edges represent negative associations, while the thickness of edges represent the strength of associations.

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