The interplay between cognitive risk and resilience factors in remitted depression: A network analysis

Hoorelbeke, Kristof; Marchetti, Igor; Schryver, Maarten De; Koster, Ernst H. W.

doi:10.1016/j.jad.2016.02.001

Cited by 84 publications

(90 citation statements)

References 67 publications

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“…Table 1). Hoorelbeke et al [45] studied the potential role of risk and protective factors and found that resilience was the principal hub in the network and it could be a key factor in the remission of depression. Cramer et al [46] found specific connections between depressive symptoms (e.g., “feelings of worthlessness”) and stressful life events such as “ending of a romantic relationship.” In a sample of women in their third trimester of pregnancy, Santos et al [47] assessed the relationship between stress and reproductive biomarkers (e.g., cortisol) and depression.…”

Section: Resultsmentioning

confidence: 99%

“…Our results bear out that adding non-symptom element can enhance the understanding of important aspects of psychopathology. The range of these elements included in NA vary a great deal, from attention bias in SA networks [90] to biomarkers [47], resilience in depressive networks [45] or the so-called external field variables [22], like life events [46]. For instance, the study by Isvoranu et al [63] revealed multiple potential pathways between childhood trauma and psychosis, either through a pathway of emotional distress or through general psychopathology.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

The Study of Psychopathology from the Network Analysis Perspective: A Systematic Review

Contreras

Nieto

Valiente

et al. 2019

Psychother Psychosom

256

189

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Background: Network analysis (NA) is an analytical tool that allows one to explore the map of connections and eventual dynamic influences among symptoms and other elements of mental disorders. In recent years, the use of NA in psychopathology has rapidly grown, which calls for a systematic and critical analysis of its clinical utility. Methods: Following PRISMA guidelines, a systematic review of published empirical studies applying NA in psychopathology, between 2010 and 2017, was conducted. We included the literature published in PubMed and PsycINFO using as keywords any combination of “network analysis” with the terms “anxiety,” “affective disorders,” “depression,” “schizophrenia,” “psychosis,” “personality disorders,” “substance abuse” and “psychopathology.” Results: The review showed that NA has been applied in a plethora of mental disorders in adults (i.e., 13 studies on anxiety disorders; 19 on mood disorders; 7 on psychosis; 1 on substance abuse; 1 on borderline personality disorder; 18 on the association of symptoms between disorders), and 6 on childhood and adolescence. Conclusions: A critical examination of the results of each study suggests that NA helps to identify, in an innovative way, important aspects of psychopathology like the centrality of the symptoms in a given disorder as well as the mutual dynamics among symptoms. Yet, despite these promising results, the clinical utility of NA is still uncertain as there are important limitations on the analytic procedures (e.g., reliability of indices), the type of data included (e.g., typically restricted to secondary analysis of already published data), and ultimately, the psychometric and clinical validity of the results.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

The Study of Psychopathology from the Network Analysis Perspective: A Systematic Review

Contreras

Nieto

Valiente

et al. 2019

Psychother Psychosom

256

189

View full text Add to dashboard Cite

show abstract

“…As such, network analysis is flexible and may be used to study psychopathology at various levels of complexity [20]. Indeed, there has been an increase in studies that have examined psychopathology at the construct level [20][21][22][23], and this approach has the advantage of reducing the amount of nodes and edges in a network, in turn simplifying interpretation [24]. As the aim of the present study was to provide a network analogue to p (which has primarily been modelled at the disorder-level), we chose to focus our enquiry at the disorder level (e.g.…”

Section: Introductionmentioning

confidence: 99%

Co-occurring internalizing and externalizing psychopathology in childhood and adolescence: a network approach

McElroy

Shevlin

Murphy

et al. 2018

Eur Child Adolesc Psychiatry

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The network approach suggests that psychopathology arises from complex associations between symptoms and may offer insight into the mechanisms that underpin psychiatric comorbidities. The transition from childhood to adolescence is a key period in the development of psychopathology, yet has rarely been considered from a network perspective. As such, the present study examined the network structure of internalizing and externalizing psychopathology from middle childhood through adolescence using data from the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 4405). Eight DSM-IV disorders were assessed using maternal reports when children were aged 7.5, 10.5 and 14 years. Weighted, undirected networks were estimated and the relative importance of each node was assessed using three common measures of node centrality; strength, betweenness, and closeness. A consistent network structure emerged at all three time points; nodes clustered together in two regions of space broadly reflecting the internalizing and externalizing spectra. Permutation tests supported structural invariance across this developmental period. These spectra were bridged by numerous disorder-level interactions, the most consistent of which was between depression and oppositional defiant disorder (ODD). Furthermore, inspection of the centrality indices indicated that generalised anxiety disorder and ODD were the most central disorders in the networks. These findings demonstrate that symptom/disorder-level interplay and reciprocal influence are plausible mechanisms for the association between internalizing and externalizing psychopathology in childhood/adolescence.

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“…YàX it is inferred that X directly predicts Y (Hoorelbeke, Marchetti, De Schryver & Koster, 2016;McNally, 2016;McNally et al, 2014;Robinaugh et al, 2014).…”

Section: Conditionally Independent Networkmentioning

confidence: 99%

Evidence that Psychopathology Symptom Networks have Limited Replicability

Forbes¹,

Wright²,

Markon³

et al. 2017

Preprint

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Network analysis is quickly gaining popularity in psychopathology research as a method that aims to reveal causal relationships among individual symptoms. To date, four main types of psychopathology networks have been proposed: (1) association networks, (2) regularized concentration networks, (3) relative importance networks, and (4) directed acyclic graphs.We examined the replicability of these analyses based on symptoms of major depression and generalized anxiety between and within two highly similar epidemiological samples (i.e., the National Comorbidity Survey -Replication [n = 9282] and the National Survey of Mental Health and Wellbeing [n = 8841]). While association networks were stable, the three other types of network analysis (i.e., the conditional independence networks) had poor replicability between and within methods and samples. The detailed aspects of the models-such as the estimation of specific edges and the centrality of individual nodes-were particularly unstable. For example, 44% of the symptoms were estimated as the "most influential" on at least one centrality index across the six conditional independence networks in the full samples, and only 13-21% of the edges were consistently estimated across these networks.One of the likely reasons for the instability of the networks is the predominance of measurement error in the assessment of individual symptoms. We discuss the implications of these findings for the growing field of psychopathology network research, and conclude that novel results originating from psychopathology networks should be held to higher standards of evidence before they are ready for dissemination or implementation in the field.Key words: Network analysis; psychopathology; causal inference; psychopathology networks; replication crisis. REPLICABILITY OF PSYCHOPATHOLOGY NETWORKS 3General Scientific Summary: A statistical method called network analysis is quickly gaining popularity for analyzing the relationships between symptoms of mental disorders.This study found that popular network analysis methods produce unreliable results, particularly for the symptom-level aspects of the models. We highlight the need to be particularly cautious in interpreting, disseminating, or implementing results that arise from psychopathology networks. REPLICABILITY OF PSYCHOPATHOLOGY NETWORKS 4 Evidence that Psychopathology Symptom Networks do not ReplicateThe popularity of network analysis is spreading quickly in the study of psychopathology. In particular, a growing number of studies using cross-sectional analyses of networks of psychopathology symptoms have appeared in the literature since Cramer et al.

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The interplay between cognitive risk and resilience factors in remitted depression: A network analysis

Cited by 84 publications

References 67 publications

The Study of Psychopathology from the Network Analysis Perspective: A Systematic Review

The Study of Psychopathology from the Network Analysis Perspective: A Systematic Review

Co-occurring internalizing and externalizing psychopathology in childhood and adolescence: a network approach

Evidence that Psychopathology Symptom Networks have Limited Replicability

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