As I stated in my previous post, the second major content theme in The Atlas ofSocial Complexity is the Dynamics of Human Psychology. So far for this theme, I’ve given a basic overview, found here. I then moved on to the first theme, Humanpsychology as dynamical system (Chapter 13).
The focus of this post is Chapter 14: Psychopathology of mental disorders.
OVERVIEW OF CHAPTER
Chapter 14 explores the question: What is a mental disorder and how best should we assess it in terms of social complexity?
The field of psychopathology (also sometimes referred to as abnormal psychology) is the formal term for the study of mental disorders. Subfields include developmental, child, adolescent, and adult psychopathology. The general focus across all these sub-fields is on ‘abnormal’ states of thinking, feeling and behaving, particularly within a clinical context – with an awareness that our conceptualisation of what is ‘abnormal’ is deeply connected to our interpersonal relationships, community, culture and sociohistorical context.
There is general agreement that, when it comes to psychopathology, what matters most is that a person is legitimately troubled by their emotional, cognitive, behavioural or social difficulties. In short, they are suffering.
There is less agreement, however, on what constitutes a mental disorder. For example, are a person’s psychological difficulties a brain disease or latent psychological construct? Or are they a scientific classification that points to the clustering of sets of psychological symptoms that have no fundamental underlying biological existence? The former view has historically dominated. The latter – referred to as the new science of mental disorders – is fast becoming the major alternative, with the potential to override the former.
Mental Health Symptom Networks
The network science of psychopathology got its start in the Psychology Department at the University of Amsterdam with the publication of two key articles. The first, in 2008, was Denny Borsboom’s Psychometric perspectives on diagnostic system. While breaking new ground, the concept of networks remained unarticulated in it. A more complete statement arrived with the second publication, in 2010, led by Angélique Cramer.[1] It is at this point that this approach really takes off.
During the next thirteen years, the network approach would quickly become a major contender for the definition and diagnosis of psychopathology as well as a counterpoint to conventional approaches in psychometrics, with articles being published widely. Symptom network analysis has been applied to depression, schizophrenia, post-traumatic stress disorder, anxiety, psychosis, sleep disorders, autism, bipolar disorder, and a variety of comorbid mental health conditions.
This widespread adoption is demonstrated well by the fact that Cramer and colleagues published a second article in Behavioral and Brain Sciences in 2019[4].
Controversies, Challenges and an Agenda for Moving Forward
When the symptom network approach to psychopathology first emerged, its novelty was its virtue. Here, suddenly, was a way to use the latest advances in complex network analysis to think about mental disorders that felt authentic to clinical intuitions and experience. Research collided with practice, a rare event.
Nevertheless, there are a list of challenges that need to be addressed. Here is a list of the topics addressed in Chapter 14.
1. Statistical equivalence.
2. The limits of centrality measures.
3. Symptoms can be latent variables.
4. The problem of reductionism.
5. Where is the social?
6. Timing, dynamics and time scales.
7. Reproducibility and replicability.
8. Therapeutically targeting symptoms.
Why Embrace this Approach?
Within the soft transdiagnostic camp, the symptom network approach is, for us, the more viable route for those interested in the study of social complexity. And we say this despite the fact that this approach has some considerable challenges to address – which we just listed. Here is our rationale:
First and foremost, given its grounding in the complexity sciences, the network approach to psychopathology fits with the theoretical synthesis we have so far stitched together.
Second, this approach avoids the trap that the hierarchical latent variable approach falls into, given that the latter is still, ironically enough, in search of a more fundamental set of causal factors to explain mental disorders.
Third, while we appreciate the hard transdiagnostic camp’s attempt to revolutionise diagnostic nomenclature, its argument is doomed. It will never happen.
Finally, despite the flaws of the network approach, we will show that its problems can be fixed, oddly enough, by making better use of complex networks.
Our approach in Chapter 14 is to sidestep the theoretical shallowness of symptom networks by embracing a hierarchical network approach, which stiches together not only the biological and neuropsychological levels of human psychology but also, moving into the next major section of the Atlas, the social.
Still, despite the advances made by the symptom network literature, the social is still deafeningly missing from everyone’s work. Transdiagnostic approaches need to stop treating the social as a trigger for psychopathology, and see it, instead, as core to its formation.
KEY WORDS: symptom networks, psychopathology, network theory, psychometrics, transdiagnostic psychiatry and psychology, network science of mental disorders.
[1] Angélique O. J. Cramer et al., ‘Comorbidity: A Network Perspective’, Behavioral and Brain Sciences 33, no. 2–3 (June 2010): 137–50.
[2] Donald J. Robinaugh et al., ‘The Network Approach to Psychopathology: A Review of the Literature 2008–2018 and an Agenda for Future Research’, Psychological Medicine 50, no. 3 (February 2020), .p. 353.
[3] Ibid., p. 353.
[4] In reality, the paper was accepted for publication in 2017, and the commentaries and paper were collected and published online by Cambridge University Press: 24 January 2018, e2, but the final formal version was 2019.
