The Mental Health Ecosystem: Extending Symptom Networks With Risk and Protective Factors

Abstract

Inspired by modeling approaches from the ecosystems literature, in this paper, we expand the network approach to psychopathology with risk and protective factors to arrive at an integrated analysis of resilience. We take a complexity approach to investigate the multifactorial nature of resilience and present a system in which a network of interacting psychiatric symptoms is targeted by risk and protective factors. These risk and protective factors influence symptom development patterns and thereby increase or decrease the probability that the symptom network is pulled toward a healthy or disorder state. In this way, risk and protective factors influence the resilience of the network. We take a step forward in formalizing the proposed system by implementing it in a statistical model and translating different influences from risk and protective factors to specific targets on the node and edge parameters of the symptom network. To analyze the behavior of the system under different targets, we present two novel network resilience metrics: Expected Symptom Activity (ESA, which indicates how many symptoms are active or inactive) and Symptom Activity Stability (SAS, which indicates how stable the symptom activity patterns are). These metrics follow standard practices in the resilience literature, combined with ideas from ecology and physics, and characterize resilience in terms of the stability of the system's healthy state. By discussing the advantages and limitations of our proposed system and metrics, we provide concrete suggestions for the further development of a comprehensive modeling approach to study the complex relationship between risk and protective factors and resilience.

Network Analysis of Depressive Symptomatology in Underweight and Obese Adults

“…The use of other neuroanatomical, 44 genomic, and biomarker measures related to depression and obesity is also possible. 45 , 46 In fact, it is possible to include chronic health status as a network measure, 47 and this would allow for new lines of research into comorbid clinical manifestations related to other psychological aspects. 25 , 48 , 49 The simultaneous application of various clinical measures in the network model may favor a comprehensive assessment of depressive symptomatology as a risk factor for mental and physical health.…”

“… 25 , 48 , 49 The simultaneous application of various clinical measures in the network model may favor a comprehensive assessment of depressive symptomatology as a risk factor for mental and physical health. 47 …”

Bouncing back from life’s perturbations: Formalizing psychological resilience from a complex systems perspective

“…Symptom networks could also be extended with risk and protective factors that help or hinder the further development of symptoms. These risk and protective factors may directly affect the symptom network's architecture such that it becomes more or less resilient (See Figure 7) (Isvoranu et al, 2017;Kalisch et al, 2019;Lunansky et al, 2021b). For example, the risk factor of being sexually abused in childhood is directly linked to the development of feelings of guilt later in life (Isvoranu et al, 2017), while the protective factor 'social support' may hinder the evolution of 'depressed mood' (e.g., Gariépy et al, 2016).…”

Network analysis in clinical research

“…Asimismo, en los análisis de redes se ha reportado el uso de otras medidas clínicas como las neuropsiquiátricas, 14 las neuroanatómicas 15 y las genómicas, 16,17 así como la inclusión de factores de riesgo y protección. 18 En la actualidad se viene impulsando el estudio de múltiples entidades clínicas relacionadas con el impacto negativo de la pandemia por COVID-19, tales como miedo, angustia y estrés, 12,19 y en 2021 ya se han publicado dos artículos que emplean el análisis de redes en Sudamérica en este contexto; 19,20 sin embargo, aún urge una mayor divulgación y capacitación sobre este enfoque para fomentar su uso general en la investigación de las ciencias de la salud.…”