Evidence map›Paper›PMID 38321588›Full record

ArticleDevelopmental science2024

Cognitive deficits and enhancements in youth from adverse conditions: An integrative assessment using Drift Diffusion Modeling in the ABCD study.

Stefan Vermeent, Ethan S Young, Meriah L DeJoseph, Anna-Lena Schubert, Willem E Frankenhuis

Abstract read
In one paragraph

Article in Developmental science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

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  6. Improving statistical reporting in psychology.Communications psychology · 2025
    Review
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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

5 authors.

Stefan VermeentDepartment of Psychology, Utrecht University, Utrecht, The Netherlands.ORCID https://orcid.org/0000-0002-9595-5373
Ethan S YoungDepartment of Psychology, Utrecht University, Utrecht, The Netherlands.ORCID https://orcid.org/0000-0002-8232-0184
Meriah L DeJosephInstitute of Child Development, University of Minnesota, Minneapolis, Minnesota, USA.ORCID https://orcid.org/0000-0002-5086-147X
Anna-Lena SchubertDepartment of Psychology, University of Mainz, Mainz, Germany.ORCID https://orcid.org/0000-0001-7248-0662
Willem E FrankenhuisDepartment of Psychology, Utrecht University, Utrecht, The Netherlands.ORCID https://orcid.org/0000-0002-4628-1712

Funding

Disentangling the role of poverty-related experiences on children's self-regulation: Identifying dynamic and contextually-relevant mechanismsF32HD112065 · NICHD · STANFORD UNIVERSITY · PI DEJOSEPH, MERIAH L · 2023 to 2025
$230k
Dutch Research Council V1.Vidi.195.130James S. McDonnell Foundation https://doi.org/10.37717/220020502National Institute of Child Health and Human Development 1F32HD112065-01NICHD NIH HHS F32 HD112065
6 · The paper itself

Abstract

Childhood adversity can lead to cognitive deficits or enhancements, depending on many factors. Though progress has been made, two challenges prevent us from integrating and better understanding these patterns. First, studies commonly use and interpret raw performance differences, such as response times, which conflate different stages of cognitive processing. Second, most studies either isolate or aggregate abilities, obscuring the degree to which individual differences reflect task-general (shared) or task-specific (unique) processes. We addressed these challenges using Drift Diffusion Modeling (DDM) and structural equation modeling (SEM). Leveraging a large, representative sample of 9-10 year-olds from the Adolescent Brain Cognitive Development (ABCD) study, we examined how two forms of adversity-material deprivation and household threat-were associated with performance on tasks measuring processing speed, inhibition, attention shifting, and mental rotation. Using DDM, we decomposed performance on each task into three distinct stages of processing: speed of information uptake, response caution, and stimulus encoding/response execution. Using SEM, we isolated task-general and task-specific variances in each processing stage and estimated their associations with the two forms of adversity. Youth with more exposure to household threat (but not material deprivation) showed slower task-general processing speed, but showed intact task-specific abilities. In addition, youth with more exposure to household threat tended to respond more cautiously in general. These findings suggest that traditional assessments might overestimate the extent to which childhood adversity reduces specific abilities. By combining DDM and SEM approaches, we can develop a more nuanced understanding of how adversity affects different aspects of youth's cognitive performance. RESEARCH HIGHLIGHT: To understand how childhood adversity shapes cognitive abilities, the field needs analytical approaches that can jointly document and explain patterns of lowered and enhanced performance. Using Drift Diffusion Modeling and Structural Equation Modeling, we analyzed associations between adversity and processing speed, inhibition, attention shifting, and mental rotation. Household threat, but not material deprivation, was mostly associated with slower task-general processing speed and more response caution. In contrast, task-specific abilities were largely intact. Researchers might overestimate the impact of childhood adversity on specific abilities and underestimate the impact on general processing speed and response caution using traditional measures.

Indexed as

CognitionAdolescentAdverse Childhood ExperiencesAttentionChildCognitive DysfunctionFemaleHumansMaleNeuropsychological TestsReaction Timeadolescent Brain Cognitive Development (ABCD) studyadversitycognitive deficitscognitive enhancementsDrift Diffusion Modeling

Identifiers

PMID38321588
PMCPMC11338291

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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.