ArticleBMC medicine2020
On the validity of the centrality hypothesis in cross-sectional between-subject networks of psychopathology.
Article in BMC medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 1 of them a synthesis that pooled it.
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Who cites it
53 citing papers in PubMed, 1 synthesis or guideline pooled it, 105 citations in OpenAlex.
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- Network-guided symptom targets in maintenance hemodialysis using in silico interventions: a multicenter cross-sectional study.BMC nephrology · 2026Observational
- A Network Approach to the Association Between Emotional Regulation and ADHD Symptoms in Adults: Pathways between Difficulties in Emotional Regulation and ADHD Dimensions.The Psychiatric quarterly · 2026Article
- Family external social support as a bridge to humanistic care: a cross-sectional network analysis with exploratory gender comparison in college students.BMC psychology · 2026Article
- Network analysis of psychological problems in school-attending students aged 6-16 years in China: A comparison between rural and urban areas.Pediatric investigation · 2026Article
- The Role of Feedback Loops in Dynamical Symptom Networks.Scientific reports · 2026Article
- Mental Health Professionals' Attitudes Towards the Network Theory of Mental Disorders.Clinical psychology in Europe · 2026Article
- Network analysis of smartphone addiction and sleep disorder symptoms in Chinese college students.PloS one · 2026Article
- External factors show reproducible local symptom-biomarker associations in middle-aged and older adults with heart disease.Frontiers in psychiatry · 2026Article
- From childhood trauma to complex PTSD: a network analysis.European journal of psychotraumatology · 2025Article
- Network Structure of Post-Traumatic Stress and Social/Emotional/Behavioral Difficulties in a Post-Earthquake Child and Adolescent Sample.European journal of investigation in health, psychology and education · 2025Article
- The component-to-trait relationship between intolerance of uncertainty and obsessive-compulsive personality traits: a network analysis.BMC psychiatry · 2025Article
- The network structure of self-compassion in older adults with different productive engagement patterns.Scientific reports · 2025Article
- A framework for parsing psychopathological heterogeneity: initial application in a large-scale unselected community sample.BMC psychiatry · 2025Article
- To Use or Not to Use: Exploring Therapists' Experiences with Pre-Treatment EMA-Based Personalized Feedback in the TheraNet Project.Administration and policy in mental health · 2025Article
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Authors and funding
6 authors at 5 institutions in 3 countries.
Funding
Abstract
backgroundIn the network approach to psychopathology, psychiatric disorders are considered networks of causally active symptoms (nodes), with node centrality hypothesized to reflect symptoms' causal influence within a network. Accordingly, centrality measures have been used in numerous network-based cross-sectional studies to identify specific treatment targets, based on the assumption that deactivating highly central nodes would proliferate to other nodes in the network, thereby collapsing the network structure and alleviating the overall psychopathology (i.e., the centrality hypothesis).
methodsHere, we summarize three types of evidence pertaining to the centrality hypothesis in psychopathology. First, we discuss the validity of the theoretical assumptions underlying the centrality hypothesis in psychopathology. We then summarize the methodological aspects of extant studies using centrality measures as predictors of symptom change following treatment, while delineating their main findings and several of their limitations. Finally, using a specific dataset of 710 treatment-seeking patients with posttraumatic stress disorder (PTSD) as an example, we empirically examine node centrality as a predictor of therapeutic change, replicating the approach taken by previous studies, while addressing some of their limitations. Specifically, we investigated whether three pre-treatment centrality indices (strength, predictability, and expected influence) were significantly correlated with the strength of the association between a symptom's change and the change in the severity of all other symptoms in the network from pre- to post-treatment (Δnode-Δnetwork association). Using similar analyses, we also examine the predictive validity of two simple non-causal node properties (mean symptom severity and infrequency of symptom endorsement).
resultsOf the three centrality measures, only expected influence successfully predicted how strongly changes in nodes/symptoms were associated with change in the remainder of the nodes/symptoms. Importantly, when excluding the amnesia node, a well-documented outlier in the phenomenology of PTSD, none of the tested centrality measures predicted symptom change. Conversely, both mean symptom severity and infrequency of symptom endorsement, two standard non-network-derived indices, were found to be more predictive than expected influence and remained significantly predictive also after excluding amnesia from the network analyses.
conclusionsThe centrality hypothesis in its current form is ill-defined, showing no consistent supporting evidence in the context of cross-sectional, between-subject networks.
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