Literature DB >> 28735697

Disentangling Heterogeneity of Childhood Disruptive Behavior Problems Into Dimensions and Subgroups.

Koen Bolhuis1, Gitta H Lubke2, Jan van der Ende1, Meike Bartels3, Catharina E M van Beijsterveldt3, Paul Lichtenstein4, Henrik Larsson5, Vincent W V Jaddoe1, Steven A Kushner6, Frank C Verhulst1, Dorret I Boomsma3, Henning Tiemeier7.   

Abstract

OBJECTIVE: Irritable and oppositional behaviors are increasingly considered as distinct dimensions of oppositional defiant disorder. However, few studies have explored this multidimensionality across the broader spectrum of disruptive behavior problems (DBPs). This study examined the presence of dimensions and distinct subgroups of childhood DBPs, and the cross-sectional and longitudinal associations between these dimensions.
METHOD: Using factor mixture models (FMMs), the presence of dimensions and subgroups of DBPs was assessed in the Generation R Study at ages 6 (n = 6,209) and 10 (n = 4,724) years. Replications were performed in two population-based cohorts (Netherlands Twin Registry, n = 4,402, and Swedish Twin Study of Child and Adolescent Development, n = 1,089) and a clinical sample (n = 1,933). We used cross-lagged modeling in the Generation R Study to assess cross-sectional and longitudinal associations between dimensions. DBPs were assessed using mother-reported responses to the Child Behavior Checklist.
RESULTS: Empirically obtained dimensions of DBPs were oppositional behavior (age 6 years), disobedient behavior, rule-breaking behavior (age 10 years), physical aggression, and irritability (both ages). FMMs suggested that one-class solutions had the best model fit for all dimensions in all three population-based cohorts. Similar results were obtained in the clinical sample. All three dimensions, including irritability, predicted subsequent physical aggression (range, 0.08-0.16).
CONCLUSION: This study showed that childhood DBPs should be regarded as a multidimensional phenotype rather than comprising distinct subgroups. Incorporating multidimensionality will improve diagnostic accuracy and refine treatment. Future studies need to address the biological validity of the DBP dimensions observed in this study; herein lies an important opportunity for neuroimaging and genetic measures.
Copyright © 2017 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  DSM-5; classification; disruptive behavior disorder; factor mixture model; irritable mood

Mesh:

Year:  2017        PMID: 28735697     DOI: 10.1016/j.jaac.2017.05.019

Source DB:  PubMed          Journal:  J Am Acad Child Adolesc Psychiatry        ISSN: 0890-8567            Impact factor:   8.829


  9 in total

1.  On Defining Irritability and its Relationship to Affective Traits and Social Interpretations.

Authors:  Christen M Deveney; Joel Stoddard; Robert Evans; Goretty Chavez; Margaret Harney; Rachel Wulff
Journal:  Pers Individ Dif       Date:  2019-03-04

2.  Subgrouping children and adolescents with disruptive behaviors: symptom profiles and the role of callous-unemotional traits.

Authors:  Mireia Rosa-Justicia; Melanie C Saam; Ulrike M E Schulze; Josefina Castro-Fornieles; Itziar Flamarique; Roger Borràs; Jilly Naaijen; Andrea Dietrich; Pieter J Hoekstra; Tobias Banaschewski; Pascal Aggensteiner; Michael C Craig; Arjun Sethi; Paramala Santosh; Ilyas Sagar-Ouriaghli; Celso Arango; María José Penzol; Daniel Brandeis; Julia E Werhahn; Jeffrey C Glennon; Barbara Franke; Marcel P Zwiers; Jan K Buitelaar
Journal:  Eur Child Adolesc Psychiatry       Date:  2020-11-04       Impact factor: 4.785

3.  Understanding Irritability in Relation to Anger, Aggression, and Informant in a Pediatric Clinical Population.

Authors:  Jodi Zik; Christen M Deveney; Jarrod M Ellingson; Simone P Haller; Katharina Kircanski; Elise M Cardinale; Melissa A Brotman; Joel Stoddard
Journal:  J Am Acad Child Adolesc Psychiatry       Date:  2021-08-23       Impact factor: 13.113

4.  Validation of an irritability measure in preschoolers in school-based and clinical Brazilian samples.

Authors:  Luisa Shiguemi Sugaya; Katharina Kircanski; Argyris Stringaris; Guilherme V Polanczyk; Ellen Leibenluft
Journal:  Eur Child Adolesc Psychiatry       Date:  2021-01-02       Impact factor: 4.785

5.  Testing Bidirectional Associations Between Childhood Aggression and BMI: Results from Three Cohorts.

Authors:  Ivonne P M Derks; Koen Bolhuis; Zeynep Yalcin; Romy Gaillard; Manon H J Hillegers; Henrik Larsson; Sebastian Lundström; Paul Lichtenstein; Catharina E M van Beijsterveldt; Meike Bartels; Dorret I Boomsma; Henning Tiemeier; Pauline W Jansen
Journal:  Obesity (Silver Spring)       Date:  2019-04-08       Impact factor: 5.002

6.  Developmental Course and Risk Factors of Physical Aggression in Late Adolescence.

Authors:  Marit Henriksen; Marit Skrove; Gry Børmark Hoftun; Erik R Sund; Stian Lydersen; Wan-Ling Tseng; Denis G Sukhodolsky
Journal:  Child Psychiatry Hum Dev       Date:  2021-08

7.  Large-scale functional brain networks of maladaptive childhood aggression identified by connectome-based predictive modeling.

Authors:  Karim Ibrahim; Stephanie Noble; George He; Cheryl Lacadie; Michael J Crowley; Gregory McCarthy; Dustin Scheinost; Denis G Sukhodolsky
Journal:  Mol Psychiatry       Date:  2021-10-25       Impact factor: 13.437

Review 8.  Behavioural and emotional disorders in childhood: A brief overview for paediatricians.

Authors:  Michael O Ogundele
Journal:  World J Clin Pediatr       Date:  2018-02-08

9.  Urinary Amine and Organic Acid Metabolites Evaluated as Markers for Childhood Aggression: The ACTION Biomarker Study.

Authors:  Fiona A Hagenbeek; Peter J Roetman; René Pool; Cornelis Kluft; Amy C Harms; Jenny van Dongen; Olivier F Colins; Simone Talens; Catharina E M van Beijsterveldt; Marjolein M L J Z Vandenbosch; Eveline L de Zeeuw; Sébastien Déjean; Vassilios Fanos; Erik A Ehli; Gareth E Davies; Jouke Jan Hottenga; Thomas Hankemeier; Meike Bartels; Robert R J M Vermeiren; Dorret I Boomsma
Journal:  Front Psychiatry       Date:  2020-03-31       Impact factor: 4.157

  9 in total

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