Investigating the factor structure of the child behavior checklist dysregulation profile in children and adolescents with autism spectrum disorder.
The CBCL-DP factor structure is valid for youth with ASD, so you can safely use its mood and aggression scores to monitor dysregulation.
01Research in Context
What this study did
Camodeca et al. (2020) ran a confirmatory factor analysis on the Child Behavior Checklist Dysregulation Profile.
They wanted to know if the same three-factor pattern holds for kids and teens with autism.
All participants had ASD; parents filled out the standard CBCL forms.
What they found
The bi-factor model fit well.
Mood/anxiety and aggressive-behavior items loaded cleanly, but attention items did not.
In plain words, the CBCL-DP can track dysregulation in youth with autism, just skip the attention score.
How this fits with other research
De Kegel et al. (2016) warned that CBCL profiles give too many false positives when you try to screen for ASD itself.
Amy’s team isn’t screening; they’re measuring mood and reactivity after the ASD diagnosis is set.
Gjevik et al. (2015) showed CBCL lines up with clinical interviews for ADHD, depression, and ODD in ASD, but misses anxiety.
Amy’s factor work now tells us to lean on the anxiety/depression and aggression parts and ignore the attention part—exactly where Elen found gaps.
Neo et al. (2021) later repeated the same factor-check in preschoolers with neuro-genetic syndromes and got similar narrow-band validity, extending the pattern to even younger kids.
Why it matters
You already have the CBCL in your file cabinet.
Amy et al. give you permission to pull the Dysregulation Profile scores and trust the mood plus aggression factors when you write behavior plans or track medication response in clients with ASD.
No new test to buy, no extra parent time—just smarter use of the data you collect.
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02At a glance
03Original abstract
Dysregulation has been identified as an important risk factor for the development of psychiatric disorders in individuals with autism spectrum disorder (ASD). Therefore, it is necessary to empirically characterize dysregulation and identify psychometrically sound and readily available assessment methods in the ASD population. We sought to evaluate the factor structure of the Child Behavior Checklist-Dysregulation Profile (CBCL-DP), an established dysregulation measure in neurotypical children that is derived from the CBCL, in a large, clinically referred sample of children, ages 6-18 years, with ASD (n = 727). Confirmatory factor analysis was used to characterize dysregulation and assess the validity of the CBCL-DP in children with ASD. Our findings support a bi-factor model of dysregulation in which dysregulation is a broad and distinct syndrome that is associated with the three subdomains of the CBCL-DP, anxiety/depression (AD), attention problems (AP), and aggressive behavior (AGG). Dysregulation was associated with most items in the AD and AGG domains and few items in the AP domain. This association with AD and AGG indicates that dysregulation in ASD may be conceptualized as the combined experience of internalized, negative mood states and externalized, reactive behaviors. These findings provide support as well as important caveats for the use of the CBCL-DP as a measure of dysregulation in the ASD population. Autism Res 2020, 13: 436-443. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Dysregulation is a risk factor for psychiatric disorders in ASD. This study examined if the CBCL-DP, an established measure of dysregulation in neurotypical children, can be used to assess dysregulation in children with ASD. Findings provide evidence that in ASD, dysregulation is a broad construct that exists alongside anxiety/depression, attention problems, and aggression. These findings indicate that the CBCL-DP can be considered a valid measure of dysregulation in the ASD population and could be used in clinical settings.
Autism research : official journal of the International Society for Autism Research, 2020 · doi:10.1002/aur.2233