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A computational network perspective on pediatric anxiety symptoms

Published online by Cambridge University Press:  13 August 2020

Rany Abend*
Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
Mira A. Bajaj
Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
Daniel D. L. Coppersmith
Department of Psychology, Harvard University, Cambridge, MA, USA
Katharina Kircanski
Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
Simone P. Haller
Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
Elise M. Cardinale
Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
Giovanni A. Salum
National Institute of Developmental Psychiatry for Children and Adolescents (INCT-CNPq), São Paulo, Brazil Department of Psychiatry, Universidad Federal do Rio Grande do Sul, Porto Alegre, Brazil
Reinout W. Wiers
Addiction Development and Psychopathology (ADAPT)-lab, Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands
Elske Salemink
Department of Clinical Psychology, Utrecht University, Utrecht, the Netherlands
Jeremy W. Pettit
Florida International University, Miami, FL, USA
Koraly Pérez-Edgar
The Pennsylvania State University, University Park, PA, USA
Eli R. Lebowitz
Yale University, New Haven, CT, USA
Wendy K. Silverman
Yale University, New Haven, CT, USA
Yair Bar-Haim
Tel Aviv University, Tel Aviv, Israel
Melissa A. Brotman
Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
Ellen Leibenluft
Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
Eiko I. Fried
Department of Clinical Psychology, Leiden University, Leiden, the Netherlands
Daniel S. Pine
Emotion and Development Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
Author for correspondence: Rany Abend, E-mail:



While taxonomy segregates anxiety symptoms into diagnoses, patients typically present with multiple diagnoses; this poses major challenges, particularly for youth, where mixed presentation is particularly common. Anxiety comorbidity could reflect multivariate, cross-domain interactions insufficiently emphasized in current taxonomy. We utilize network analytic approaches that model these interactions by characterizing pediatric anxiety as involving distinct, inter-connected, symptom domains. Quantifying this network structure could inform views of pediatric anxiety that shape clinical practice and research.


Participants were 4964 youths (ages 5–17 years) from seven international sites. Participants completed standard symptom inventory assessing severity along distinct domains that follow pediatric anxiety diagnostic categories. We first applied network analytic tools to quantify the anxiety domain network structure. We then examined whether variation in the network structure related to age (3-year longitudinal assessments) and sex, key moderators of pediatric anxiety expression.


The anxiety network featured a highly inter-connected structure; all domains correlated positively but to varying degrees. Anxiety patients and healthy youth differed in severity but demonstrated a comparable network structure. We noted specific sex differences in the network structure; longitudinal data indicated additional structural changes during childhood. Generalized-anxiety and panic symptoms consistently emerged as central domains.


Pediatric anxiety manifests along multiple, inter-connected symptom domains. By quantifying cross-domain associations and related moderation effects, the current study might shape views on the diagnosis, treatment, and study of pediatric anxiety.

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