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A computational network perspective on pediatric anxiety symptoms

Published online by Cambridge University Press:  13 August 2020

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

Abstract

Background

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.

Methods

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.

Results

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.

Conclusions

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.

Type
Original Article
Creative Commons
As a work owned by the United States Government, this Contribution is not subject to copyright within the United States. Outside of the United States, Cambridge University Press is the non-exclusively licensed publisher of the Contribution.
Copyright
Copyright © NIMH 2020 outside of the United States of America

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