Scientific reports · 2020
Diagnostic Associations of Processing Speed in a Transdiagnostic, Pediatric Sample.
СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод пока не подготовлен
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Kramer Eliza, Koo Bonhwang, Restrepo Anita, Koyama Maki, Neuhaus Rebecca, Pugh Kenneth, Andreotti Charissa, Milham Michael
Аннотация
INTRODUCTION: The present study examines the relationships between processing speed (PS), mental health disorders, and learning disorders. Prior work has tended to explore relationships between PS deficits and specific diagnoses in isolation of one another. Here, we simultaneously investigated PS associations with five diagnoses (i.e., anxiety, autism, ADHD, depressive, specific learning) in a large-scale, transdiagnostic, community self-referred sample.
METHOD: 843 children, ages 8-16 were included from the Healthy Brain Network (HBN) Biobank. Principal component analysis (PCA) was employed to create a composite measure of four PS tasks, referred to as PC1. Intraclass correlation coefficient (ICC) between the four PS measures, as well as PC1, were calculated to assess reliability.
RESULTS: ICCs were moderate between WISC-V tasks (0.663), and relatively modest between NIH Toolbox Pattern Comparison and other PS scales (0.14-0.27). Regression analyses revealed specific significant relationships between PS and reading and math disabilities, ADHD-inattentive presentation (ADHD-I), and ADHD-combined presentation (ADHD-C). After accounting for inattention, the present study did not find a significant relationship with Autism Spectrum Disorder.
DISCUSSION: Our examination of PS in a large, transdiagnostic sample suggested more specific associations with ADHD and learning disorders than the literature currently suggests. Implications for understanding how PS interacts with a highly heterogeneous childhood sample are discussed.
METHOD: 843 children, ages 8-16 were included from the Healthy Brain Network (HBN) Biobank. Principal component analysis (PCA) was employed to create a composite measure of four PS tasks, referred to as PC1. Intraclass correlation coefficient (ICC) between the four PS measures, as well as PC1, were calculated to assess reliability.
RESULTS: ICCs were moderate between WISC-V tasks (0.663), and relatively modest between NIH Toolbox Pattern Comparison and other PS scales (0.14-0.27). Regression analyses revealed specific significant relationships between PS and reading and math disabilities, ADHD-inattentive presentation (ADHD-I), and ADHD-combined presentation (ADHD-C). After accounting for inattention, the present study did not find a significant relationship with Autism Spectrum Disorder.
DISCUSSION: Our examination of PS in a large, transdiagnostic sample suggested more specific associations with ADHD and learning disorders than the literature currently suggests. Implications for understanding how PS interacts with a highly heterogeneous childhood sample are discussed.