Evidence map›Paper›PMID 42462447›Full record

ArticleDevelopmental cognitive neuroscience2026

The Adolescent Brain Cognitive Development (ABCD) Study: Ten years of statistical and methodological contributions.

Anthony Steven Dick, Samuel Hawes, Mohammadreza Bayat, Marilyn Curtis, Daniel A Lopez, Pravesh Parekh, Diliana Pecheva, Raul Gonzalez, Steven G Heeringa, Janosch Linkersdörfer and 8 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Developmental cognitive neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

18 authors.

Anthony Steven DickDepartment of Psychology and Center for Children and Families, Florida International University, Miami, FL, USA. Electronic address: adick@fiu.edu.
Samuel HawesDepartment of Psychology and Center for Children and Families, Florida International University, Miami, FL, USA.
Mohammadreza BayatDepartment of Psychology and Center for Children and Families, Florida International University, Miami, FL, USA.
Marilyn CurtisDepartment of Psychology and Center for Children and Families, Florida International University, Miami, FL, USA.
Daniel A LopezDepartment of Psychiatry, Oregon Health and Science University, Portland, OR, USA; Center for Mental Health Innovation, Oregon Health and Science University, Portland, OR, USA.
Pravesh ParekhCenter for Multimodal Imaging and Genetics, J. Craig Venter Institute, La Jolla, CA, USA; Centre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway.
Diliana PechevaCenter for Multimodal Imaging and Genetics, J. Craig Venter Institute, La Jolla, CA, USA; Department of Radiology, University of California, San Diego School of Medicine, La Jolla, CA, USA.
Raul GonzalezDepartment of Psychology and Center for Children and Families, Florida International University, Miami, FL, USA.
Steven G HeeringaInstitute for Social Research, University of Michigan, Ann Arbor, MI, USA.
Janosch LinkersdörferCenter for Multimodal Imaging and Genetics, J. Craig Venter Institute, La Jolla, CA, USA.
Robert LoughnanCenter for Multimodal Imaging and Genetics, J. Craig Venter Institute, La Jolla, CA, USA.
Laika AguinaldoDepartment of Psychiatry, University of California, San Diego, La Jolla, CA, USA.
Kenneth J SherPsychological Sciences, University of Missouri, Columbia, MO, USA.
Thomas E NicholsOxford Big Data Institute, University of Oxford, Oxford, UK.
Susan F TapertDepartment of Psychiatry, University of California, San Diego, La Jolla, CA, USA.
Michael NealeVirginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA.
Anders DaleCenter for Multimodal Imaging and Genetics, J. Craig Venter Institute, La Jolla, CA, USA; Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA; Department of Radiology, University of California, San Diego School of Medicine, La Jolla, CA, USA; Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA; Department of Neuroscience, University of California, San Diego, La Jolla, CA, USA.
Wesley K ThompsonCenter for Population Neuroscience and Genetics, Laureate Institute for Brain Research, Tulsa, OK, USA.

Funding

15/21 ABCD-USA Consortium: Research Project Site at LIBRU01DA050989 · NIDA · LAUREATE INSTITUTE FOR BRAIN RESEARCH · PI ROBIN L AUPPERLE, MARTIN P. PAULUS · 2020 to 2026
$14.7M
NIDA NIH HHS U01 DA050989
6 · The paper itself

Abstract

The Adolescent Brain Cognitive Development (ABCD) Study has substantially advanced developmental neuroscience through its large scale and open-science framework. This review synthesizes the study's significant statistical and methodological contributions over its first ten years, organized around the pillars of population neuroscience, longitudinal modeling, and causal inference. We first examine how ABCD's population-based design has prompted a reconsideration of how effect sizes are interpreted, helping to establish new benchmarks for distinguishing stable, biologically relevant signals from trivial associations in large-N contexts. We detail the computational innovations required to process high-dimensional data at scale, specifically highlighting new analytic tools like the Fast and Efficient Mixed Effects Algorithm (FEMA) framework for mass-univariate modeling and advanced strategies for managing selective attrition and missing data in large-scale longitudinal cohorts. In the domain of longitudinal and multilevel modeling, we discuss the transition from traditional cross-lagged designs to sophisticated frameworks - such as random-intercept cross-lagged panel models, latent growth curves, and parallel process models - that disentangle within-person developmental trajectories from stable between-person traits. We further highlight the study's role in advancing causal inference in observational research through "G-methods", marginal structural models, and quasi-experimental family-based designs. Finally, we explore how ABCD serves as a critical bridge for cross-cohort generalizability and lifespan validation using datasets like the UK Biobank. By contributing to new standards for reproducibility and methodological rigor, the ABCD Study has helped move neuroscience toward a "big data" era, providing a comprehensive statistical foundation for understanding the complex interplay between biology and environment during the transition to adulthood.

Indexed as

ABCD StudyBig dataCausal inferenceImaging geneticsLongitudinal modelingPopulation neuroscience

Identifiers

PMID42462447
PMCPMC13401018

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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 Socratic graph.