Bouncing back from life's perturbations: Formalizing psychological resilience from a complex systems perspective.
Journal
Psychological review
ISSN: 1939-1471
Titre abrégé: Psychol Rev
Pays: United States
ID NLM: 0376476
Informations de publication
Date de publication:
21 Oct 2024
21 Oct 2024
Historique:
medline:
21
10
2024
pubmed:
21
10
2024
entrez:
21
10
2024
Statut:
aheadofprint
Résumé
Experiencing stressful or traumatic events can lead to a range of responses, from mild disruptions to severe and persistent mental health issues. Understanding the various trajectories of response to adversity is crucial for developing effective interventions and support systems. Researchers have identified four commonly observed response trajectories to adversity, from which the resilient is the most common one. Resilience refers to the maintenance of healthy psychological functioning despite facing adversity. However, it remains an open question how to understand and anticipate resilience, due to its dynamic and multifactorial nature. This article presents a novel formalized framework to conceptualize resilience from a complex systems perspective. We use the network theory of psychopathology, which states that mental disorders are self-sustaining endpoints of direct symptom-symptom interactions organized in a network system. The internal structure of the network determines the most likely trajectory of symptom development. We introduce the resilience quadrant, which organizes the state of symptom networks on two domains: (1) healthy versus dysfunctional and (2) stable versus unstable. The quadrant captures the four commonly observed response trajectories to adversity along those dimensions: resilient trajectories in the face of adversity, as well as persistent symptoms despite treatment interventions. Subsequently, an empirical illustration, by means of a proof-of-principle, shows how simulated observations from four different network architectures lead to the four commonly observed responses to adversity. As such, we present a novel outlook on resilience by combining existing statistical symptom network models with simulation techniques. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Identifiants
pubmed: 39432353
pii: 2025-37670-001
doi: 10.1037/rev0000497
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Amsterdam University Medical Centers
Organisme : University of Amsterdam; Data Science Centre
Organisme : European Research Council
Pays : International
Organisme : Dutch Research Council
Pays : Netherlands