The Child Behavior Checklist Dysregulation Profile in Preschool Children: A Broad Dysregulation Syndrome

2015 ◽  
Vol 54 (7) ◽  
pp. 595-602.e2 ◽  
Author(s):  
Sanne Barbara Geeraerts ◽  
Marike Hester Francisca Deutz ◽  
Maja Deković ◽  
Tessa Bunte ◽  
Kim Schoemaker ◽  
...  
Keyword(s):  
Preschool Children ◽  
Child Behavior ◽  
Child Behavior Checklist ◽  
Dysregulation Profile

scholarly journals Dysregulation profile defined by Child Behavior Checklist in a sample of preschool children

2019 ◽  
Vol 90 (2) ◽  
pp. 157 ◽  
Author(s):  
Rodrigo Sierra Rosales ◽  
Paula Bedregal
Keyword(s):  
Preschool Children ◽  
Child Behavior ◽  
Child Behavior Checklist ◽  
Salud Mental ◽  
Dysregulation Profile

Introducción: El perfil de desregulación (PD) es una entidad clínica de interés en el área infantojuvenil, puesto que se asocia a psicopatología futura. El PD se define a partir del instrumento Child Behavior Checklist (CBCL), combinando síntomas internalizantes (ansiedad/depresión) y externalizantes (agresividad, problemas de atención).Objetivo: Estudiar la frecuencia del perfil de PD por CBCL en una muestra de preescolares chilenos.Pacientes y Método: Se aplicó una encuesta sociodemográfica y Cuestionario CBCL 1½ - 5 a cuidadores de niños entre 30 y 48 meses de edad, en una muestra representativa nacional de usuarios de red pública. Se estimó la frecuencia utilizando el método de Kim y colaboradores y se realizó un modelo explicativo mediante regresión logística binaria del PD utilizando variables del cuidador, del niño y del contexto.Resultados: La muestra fue de 1429 preescolares y sus cuidadores. La frecuencia de PD fue de 11,6% (IC 95% 9,9-13,5%). Las variables que permiten predecir el PD en un 88,6% fueron: Síntomas depresivos actuales en el cuidador principal (OR: 2,24; IC95%: 1,37-3,67); Número de eventos vitales estresantes vividos por el cuidador principal (p = 0,005); Número de elementos disponibles para estimulación en el hogar (p = 0,001); Número de enfermedades crónicas del niño (p = 0,006).Conclusiones: PD tiene una frecuencia alta en preescolares, lo que implica una carga en salud mental relevante, apuntando a la necesidad de intervenciones en esta área, además de seguimiento longitudinal de esta subpoblación.

scholarly journals Cross-informant agreement of the Dysregulation Profile of the Child Behavior Checklist

2010 ◽  
Vol 178 (3) ◽  
pp. 550-555 ◽  
Author(s):  
Robert R. Althoff ◽  
David C. Rettew ◽  
Lynsay A. Ayer ◽  
James J. Hudziak
Keyword(s):  
Child Behavior ◽  
Child Behavior Checklist ◽  
Informant Agreement ◽  
Dysregulation Profile

A Familial Risk Analysis of Emotional Dysregulation: A Controlled Study

2015 ◽  
Vol 22 (9) ◽  
pp. 848-854 ◽  
Author(s):  
Joseph Biederman ◽  
James Chan ◽  
Stephen V. Faraone ◽  
K. Yvonne Woodworth ◽  
Thomas J. Spencer ◽  
...  
Keyword(s):  
Child Behavior ◽  
Emotional Regulation ◽  
Child Behavior Checklist ◽  
Familial Risk ◽  
Attention Problems ◽  
Emotional Dysregulation ◽  
Adverse Outcomes ◽  
Controlled Study ◽  
Increased Risk ◽  
Dysregulation Profile

Objective: Children with deficits in emotional regulation operationalized by scores on the Child Behavior Checklist (CBCL) Attention Problems, Aggressive Behavior, and Anxious-Depressed subscales are more likely than others to manifest adverse outcomes. However, the transmission of this profile has not been well studied. The main aim of this study was to investigate the familiality of this profile. Method: Participants were youth probands with bipolar I (BP-I) disorder ( N = 140), ADHD ( N = 83), and controls ( N = 117) and their siblings. Based on the CBCL emotional dysregulation profile, we classified children with severe emotional dysregulation (aggregate cut-off score ≥210) and emotional dysregulation (aggregate cut-off score ≥ 180 and <210). Results: Emotional dysregulation profile scores correlated positively between probands and siblings. Conclusion: Youth with emotional dysregulation are at increased risk to have siblings with similar deficits, suggesting that emotional dysregulation runs in families.

Cluster Analysis of the Child Behavior Checklist 1.5–5 for Preschool Children Diagnosed With a Mental Disorder

2019 ◽  
Vol 123 (4) ◽  
pp. 1403-1424 ◽  
Author(s):  
Ji Ye Kim ◽  
Eun Hye Ha
Keyword(s):  
Cluster Analysis ◽  
Preschool Children ◽  
Mental Disorder ◽  
Child Behavior ◽  
Child Behavior Checklist ◽  
Discriminant Validity ◽  
Autism Spectrum ◽  
Clinical Group ◽  
Statistical Manual ◽  
Diagnostic And Statistical Manual

Research on the relationship between the Child Behavior Checklist (CBCL) and Diagnostic and Statistical Manual for Mental Disorder diagnoses for preschool children is scarce. Cluster analysis can be useful for investigating characteristics of a clinical group by using CBCL subscales and classifying subtypes of a Diagnostic and Statistical Manual for Mental Disorder diagnosis group. This study conducted a cluster analysis of the CBCL 1.5–5 for preschool children diagnosed with a mental disorder. Participants were 333 children (255 males and 78 females) aged 1.5 to 5 years who were diagnosed with a mental disorder. The CBCL 1.5–5 and Bayley Scales of Infant Development II were used as assessment instruments. Three clusters were extracted and then compared with CBCL 1.5–5 profiles of each Diagnostic and Statistical Manual for Mental Disorder-5 subject group to determine their clusters. Cluster 1 was named “intellectual disorder cluster.” Cluster 2 was referred to as “other mental disorders cluster,” and Cluster 3 was called “autism spectrum disorder cluster.” When differences in profiles of behavior problems distinguished by CBCL 1.5–5 scales were examined among different clusters, discriminant validity was found to be high.

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