Journal article Open Access

Deconstructing and reconstructing resilience: a dynamic network approach

Kalisch, Raffael; Cramer, Angelique OJ; Binder, Harald; Fritz, Jessica; Leertouwer, IJsbrand; Lunansky, Gabriela; Meyer, Benjamin; Timmer, Jens; Veer, Ily M.; van Harmelen, Anne-Laura

Resilience is still often viewed as a unitary personality construct that, as a kind of anti-nosological entity, protects individuals against stress-related mental problems. However, increasing evidence indicates that the maintenance of mental health in the face of adversity results from complex and dynamic processes of adaptation to stressors that involve the activation of several separable protective factors. Such resilience factors can reside at biological, psychological and social levels and may include stable predispositions (such as genotype or personality traits) and malleable properties, skills, capacities or external circumstances (such as gene expression patterns, emotion regulation abilities, appraisal styles or social support). We here abandon the notion of resilience as an entity. Starting from a conceptualization of psychiatric disorders as dynamic networks of interacting symptoms that may be driven by stressors into stable maladaptive states of disease, we deconstruct the maintenance of mental health during stressor exposure into time-variant dampening influences of resilience factors onto these symptom networks. Resilience factors are separate additional network nodes that weaken symptom-symptom interconnections or symptom auto-connections, thereby preventing maladaptive system transitions. We argue that these "hybrid symptom-and-resilience factor" (HSR) networks provide a promising new way of unraveling the complex dynamics of mental health.

Files (801.5 kB)
Name Size
Kalisch_Cramer_Resilience_Zenodo.pdf
md5:233945b994d30ff9fded54621011a832
801.5 kB Download
1,281
390
views
downloads
All versions This version
Views 1,2811,291
Downloads 390390
Data volume 312.6 MB312.6 MB
Unique views 1,1731,183
Unique downloads 346346

Share

Cite as