Evidence map›Paper›PMID 32572148›Full record

ArticleScientific reports2020

Diagnostic Associations of Processing Speed in a Transdiagnostic, Pediatric Sample.

Eliza Kramer, Bonhwang Koo, Anita Restrepo, Maki Koyama, Rebecca Neuhaus, Kenneth Pugh, Charissa Andreotti, Michael Milham

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Processing Speed is Related to the General Psychopathology Factor in Youth.Research on child and adolescent psychopathology · 2023
    Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Eliza KramerHealthy Brain Network, Child Mind Institute, New York, New York, USA.
Bonhwang KooCenter for the Developing Brain, Child Mind Institute, New York, New York, USA.
Anita RestrepoHealthy Brain Network, Child Mind Institute, New York, New York, USA.
Maki KoyamaHaskins Laboratories, New Haven, CT, USA.
Rebecca NeuhausHealthy Brain Network, Child Mind Institute, New York, New York, USA.
Kenneth PughHaskins Laboratories, New Haven, CT, USA.
Charissa AndreottiHealthy Brain Network, Child Mind Institute, New York, New York, USA.
Michael MilhamCenter for the Developing Brain, Child Mind Institute, New York, New York, USA. michael.milham@childmind.org.

Funding

Yale Clinical and Translational Science Award (U Component)UL1TR001863 · NCATS · YALE UNIVERSITY · PI John H. Krystal, LUCILA OHNO-MACHADO · 2016 to 2026
$102.9M
Predicting Heterogeneous Neurodevelopmental Outcomes in School-age Children with Early Caregiving AdversitiesR01MH091864 · NIMH · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI MILHAM, MICHAEL PETER, TOTTENHAM, NIM · 2010 to 2022
$5.1M
Longitudinal Discovery of Brain Developmental TrajectoriesU01MH099059 · NIMH · NATHAN S. KLINE INSTITUTE FOR PSYCH RES · PI MILHAM, MICHAEL PETER · 2013 to 2017
$3.7M
NCATS NIH HHS UL1 TR001863NIMH NIH HHS R01 MH091864NIMH NIH HHS U01 MH099059
6 · The paper itself

Abstract

introductionThe 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.

method843 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.

resultsICCs 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.

Indexed as

AdolescentAnxietyAttention Deficit Disorder with HyperactivityAutism Spectrum DisorderChildCognitionDepressionFemaleHumansLearning DisabilitiesMaleNeurodevelopmental DisordersReproducibility of ResultsWechsler Scales

Identifiers

PMID32572148
PMCPMC7308370

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.