A network theory of mental disorders

Abstract

In recent years, the network approach to psychopathology has been advanced as an alternative way of conceptualizing mental disorders. In this approach, mental disorders arise from direct interactions between symptoms. Although the network approach has led to many novel methodologies and substantive applications, it has not yet been fully articulated as a scientific theory of mental disorders. The present paper aims to develop such a theory, by postulating a limited set of theoretical principles regarding the structure and dynamics of symptom networks. At the heart of the theory lies the notion that symptoms of psychopathology are causally connected through myriads of biological, psychological and societal mechanisms. If these causal relations are sufficiently strong, symptoms can generate a level of feedback that renders them self-sustaining. In this case, the network can get stuck in a disorder state. The network theory holds that this is a general feature of mental disorders, which can therefore be understood as alternative stable states of strongly connected symptom networks. This idea naturally leads to a comprehensive model of psychopathology, encompassing a common explanatory model for mental disorders, as well as novel definitions of associated concepts such as mental health, resilience, vulnerability and liability. In addition, the network theory has direct implications for how to understand diagnosis and treatment, and suggests a clear agenda for future research in psychiatry and associated disciplines.

Keywords: Psychopathology; diagnosis; mental disorders; mental health; network approach; resilience; symptom networks; treatment; vulnerability.

© 2017 World Psychiatric Association.

Figures

Figure 1

A symptom network of four symptoms (S1‐S4). If two symptoms have the tendency to activate each other, they are connected by a line (e.g., S1‐S2). Symptoms that are not directly connected to each other (e.g., S1‐S4) can still synchronize if they share a common neighbor in the network (e.g., S3). External factors that affect the network (e.g., adverse life events) are represented in the external field. These may be symptom‐specific (E1, E3) or shared across symptoms (E2).

Figure 2

Two disorders (A and B) that are connected through bridge symptoms (S5 and S6) which play a role in both networks. Although the association of symptoms will be strongest within each network, structural overlap between the disorders is unavoidable, and as a result comorbidity will arise.

Figure 3

Phases in the development of mental disorders according to the network theory. After an asymptomatic phase, in which the network is dormant (Phase 1), an external event (E1) activates some of the symptoms (Phase 2), which in turn activate connected symptoms (Phase 3). If the network is strongly connected, removal of the external event does not lead to recovery: the network is self‐sustaining and is stuck in its active state (Phase 4).

Figure 4

A weakly connected network (top panel) is resilient. Symptoms may be activated by events in the external field, but the symptom‐symptom interactions are not strong enough to lead to self‐sustaining symptom activity. A strongly connected network (bottom panel), instead, can sustain its own activity and thus develop into a disorder state.