“Critical slowing down in depression” is a great idea that still needs empirical proof

Bos, Elisabeth H.; Jonge, Peter de

doi:10.1073/pnas.1323672111

Cited by 37 publications

(35 citation statements)

References 2 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While this is an extreme example—it seems unlikely that symptoms of mental disorders are predominantly positively associated at group-level, but negatively in the individual—we currently do not know to what extent group-level networks differ from individual networks [43]. A related point was made by Bos and Jonge [71] and Bos and Wanders [42] who warn that between-person effects should not be confused with within-person effects. Taken together, this implies that we need future studies that investigate to which degree idiographic networks match group-level networks, and to disentangle between-person from within-person effects.…”

Section: Future Directionsmentioning

confidence: 99%

Mental disorders as networks of problems: a review of recent insights

Fried

Borkulo

Cramer

et al. 2016

Soc Psychiatry Psychiatr Epidemiol

706

595

View full text Add to dashboard Cite

PurposeThe network perspective on psychopathology understands mental disorders as complex networks of interacting symptoms. Despite its recent debut, with conceptual foundations in 2008 and empirical foundations in 2010, the framework has received considerable attention and recognition in the last years.MethodsThis paper provides a review of all empirical network studies published between 2010 and 2016 and discusses them according to three main themes: comorbidity, prediction, and clinical intervention.ResultsPertaining to comorbidity, the network approach provides a powerful new framework to explain why certain disorders may co-occur more often than others. For prediction, studies have consistently found that symptom networks of people with mental disorders show different characteristics than that of healthy individuals, and preliminary evidence suggests that networks of healthy people show early warning signals before shifting into disordered states. For intervention, centrality—a metric that measures how connected and clinically relevant a symptom is in a network—is the most commonly studied topic, and numerous studies have suggested that targeting the most central symptoms may offer novel therapeutic strategies.ConclusionsWe sketch future directions for the network approach pertaining to both clinical and methodological research, and conclude that network analysis has yielded important insights and may provide an important inroad towards personalized medicine by investigating the network structures of individual patients.Electronic supplementary materialThe online version of this article (doi:10.1007/s00127-016-1319-z) contains supplementary material, which is available to authorized users.

show abstract

Section: Future Directionsmentioning

confidence: 99%

Mental disorders as networks of problems: a review of recent insights

Fried

Borkulo

Cramer

et al. 2016

Soc Psychiatry Psychiatr Epidemiol

706

595

View full text Add to dashboard Cite

show abstract

“…Such direct evidence is still missing. Only if we find that, within single individuals, EWS temporally and systematically anticipate observed qualitative shifts in mood, then these ideas may transform into precise and person-specific information on risk for transitions in depression [4]. To date, no study has yet succeeded in gathering the required observations to obtain such direct evidence: time series of experiential states that cover a demonstrable critical transition, as well as a sufficient number of observations in advance of that transition to allow for prospective measures of EWS.…”

Section: Figmentioning

confidence: 99%

Critical Slowing Down as a Personalized Early Warning Signal for Depression

Wichers

Groot

2016

Psychother Psychosom

329

431

View full text Add to dashboard Cite

“…Relatedly, researchers investigating other dynamical systems, such as ecosystems, have used early warning signals, such as increased autocorrelation among the system's state variables, to detect systems approaching a tipping point that would push it into an alternative stable (Scheffer et al, 2009). Such early warning signals may portend a shift into a depressive episode (Bos & De Jonge, 2014;van de Leemput et al, 2014;Wichers, Groot, Psychosystems, ESM Grp, & EWS Grp, 2016).…”

Section: Testing Theory Predictionsmentioning

confidence: 99%

Advancing the Network Theory of Mental Disorders: A Computational Model of Panic Disorder

Robinaugh¹,

Jmb²,

Waldorp³

et al. 2019

Preprint

107

140

View full text Add to dashboard Cite

The network theory of psychopathology posits that mental disorders are complex systems of mutually reinforcing symptoms. This overarching framework has proven highly generative but does not specify precisely how any specific mental disorder operates as such a system. We address this gap in the literature by developing a network theory of Panic Disorder and formalizing that theory as a computational model. We first review prior psychological theory and research on Panic Disorder in order to identify its core components as well as the plausible causal relations among those components. We then construct and evaluate a computational model of Panic Disorder as a non-linear dynamical system. We show that this model can explain a great deal, including individual differences in the propensity to experience panic attacks, key phenomenological characteristics of those attacks, the onset of Panic Disorder, and the efficacy of cognitive behavioral therapy. We also show that the model identifies significant gaps in our understanding of Panic Disorder and propose a theory-driven research agenda for Panic Disorder that follows from our evaluation of the model. We conclude by discussing the implications of the model for how we understand and investigate mental disorders as complex systems.

show abstract

“Critical slowing down in depression” is a great idea that still needs empirical proof

Cited by 37 publications

References 2 publications

Mental disorders as networks of problems: a review of recent insights

Mental disorders as networks of problems: a review of recent insights

Critical Slowing Down as a Personalized Early Warning Signal for Depression

Advancing the Network Theory of Mental Disorders: A Computational Model of Panic Disorder

Contact Info

Product

Resources

About