Future Directions for Clinical Psilocybin Research: The Relaxed Symptom Network
Evan Lewis-Healey, Ruben Laukkonen, Michiel van Elk
May 19, 2021 preprint DOI: 10.31234/osf.io/q3ymd via OpenAlex
Summary
AI-generated from the abstractPsilocybin-assisted psychotherapy (PAP) shows promise for treating depression, but how it works is debated. The authors propose that depression arises from strong interactions among symptoms in a dynamic network, and that successful PAP weakens these connections, making relapse less likely. They call this the Relaxed Symptom Network hypothesis and argue that applying network theory could improve treatment response and reduce relapse. Practical guidance for integrating this framework into future clinical research with psilocybin is provided.
Study at a glance
| Characteristics | Theoretical or philosophical paper |
|---|---|
| Intervention | Psilocybin-assisted psychotherapy |
| Topics | Anxiety Psilocybin |
| Keywords | Antidepressant Clinical trial Psychotherapist Network theory |
| Citations | 3 |
| Key finding | The authors propose that successful psilocybin-assisted psychotherapy weakens connections in a symptom network, reducing vulnerability to depression and relapse. |
Abstract
Objective: Recent clinical trials have demonstrated that psilocybin may have strong antidepressant effects, and may be effective in the treatment of depressive disorders when embedded in a psychotherapeutic protocol (psilocybin-assisted psychotherapy; PAP). However, despite promising results, the mechanism(s) that may be responsible for the antidepressant effects of PAP remain contested. Within this article, it is argued that the ‘Network Theory of Mental Disorders’ may be a useful tool for clinical research with psilocybin, and may help elucidate the antidepressant elements of PAP. Method: The clinical research using PAP for depressive disorders is briefly summarised, as are the potential mechanisms of PAP. In addition to this, the fundamental tenets of the network theory is presented, with particular reference to depression. In brief, the network theory proposes that depression is an emergent phenomenon, due to strong interactions in a complex dynamic symptom network. Results: A model of action based on a symptom network is proposed. It is hypothesised that, if PAP is successful, the connections between symptoms in a network will weaken, thereby rendering the patient less vulnerable to developing/relapsing into depression. It is argued that the application of the network theory may ultimately improve responsiveness and reduce relapse in PAP. Practical guidance in using the network theory for future clinical research with psilocybin is also provided. Conclusion: This article presents the primary hypothesis of the authors (The Relaxed Symptom Network), and intends to inform future researchers on how to integrate the network theory with future clinical studies using PAP.