Example citation

Key takeaways

  • “Disorders emerge from the causal interactions among symptoms themselves, and intervening on central symptoms in disorder networks promises to foster rapid recovery”
  • Hyman 2010 “The DSM is little more than reified labels, not genuine diseases”
  • The debate over DSM 5 was about kinds vs continua, but both assume that symptoms are caused by an underlying latent variable
  • Future directions: More intense time-series data with daily or multiple-per-day measurements, e.g. mood states in depression.

According to the network perspective, an episode of disorder occurs whenever the requisite number of symptoms becomes activated for a sufficient duration. Recovery from disorder occurs when symptoms deactivate, the links between them dissolve, or both.

Instead of focusing on the unique and distinct symptoms for each disorder (“hallmark symptoms”), we should put weight on the symptoms that are non-specific and appear in many disorders. Symptoms occuring in multiple disorders can bridge activation between the networks and may be particularly important. Similarly, Central symptoms have greater potential to spread activation throughout the network, crucially they do not need to be unique hallmarks for a specific disorder.

Successfully targeting a high-centrality symptom should have cascading effects on other symptoms.

One limitation of network analysis is that many studies rely on single self-report measures. A solution could therefore be to integrate multiple measures of a symptom.

No single method in the field of psychopathology is likely to provide answers to all the questions we pose about the origins and treatment of psychological disorders. Yet network analysis holds promise as both a scientific and practical approach to conceptualizing and guiding treatment of these conditions.