ABCDscores: an R package for computing summary scores in the ABCD Study®

Abstract The ABCD Study® is the largest longitudinal research study of brain development and child health across the United States. The study generates a rich multimodal dataset, including file-based raw and derivative data and a curated tabulated dataset comprising data from a broad spectrum of research domains. Historically, summary scores in the tabulated dataset were computed using the electronic data capture system REDCap or external scripting solutions. However, this approach was rigid, unreliable, and lacked transparency around how scores were computed. Here, we introduce ABCDscores, an R software package that is used by the study to compute most non-proprietary summary scores included in the tabulated ABCD data resource and allows for customization to meet specific research needs. ABCDscores provides a flexible, open-source solution that uses R for transparent and reproducible scoring. The package is built to apply standard scoring methods across different types of assessments, ensuring consistent and accurate results even with large datasets. By simplifying complex scoring procedures into a user-friendly process, ABCDscores streamlines research workflows, reduces errors, and saves researchers valuable time. The package aims to improve analyses of data from the ABCD Study® and can serve as a model for the development of similar tools and a standardized framework for other research studies, fostering new discoveries and innovation in the field.

Authors

Institutions

Publication Details

Journal
Frontiers in Neuroinformatics
Published
2026-08-14
DOI
https://doi.org/10.3389/fninf.2026.1858950
Citations
2
Primary Topic
Health, Environment, Cognitive Aging
Type
article
Field-Weighted Citation Impact
5.88
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ABCDscores: an R package for computing summary scores in the ABCD Study®

Biplabendu Das, Calen J. Smith, Shermaine Abad, Janosch Linkersdörfer et al.
2 citations
Frontiers in Neuroinformatics
Health, Environment, Cognitive Aging
5.88
article

ABCDscores: an R package for computing summary scores in the ABCD Study®

Biplabendu Das, Calen J. Smith, Shermaine Abad, Janosch Linkersdörfer, O. Celhay, Samantha Berman, Laura R. Ziemer, Le Zhang, Anders M. Dale
article en
2 citations

Abstract

Abstract The ABCD Study® is the largest longitudinal research study of brain development and child health across the United States. The study generates a rich multimodal dataset, including file-based raw and derivative data and a curated tabulated dataset comprising data from a broad spectrum of research domains. Historically, summary scores in the tabulated dataset were computed using the electronic data capture system REDCap or external scripting solutions. However, this approach was rigid, unreliable, and lacked transparency around how scores were computed. Here, we introduce ABCDscores, an R software package that is used by the study to compute most non-proprietary summary scores included in the tabulated ABCD data resource and allows for customization to meet specific research needs. ABCDscores provides a flexible, open-source solution that uses R for transparent and reproducible scoring. The package is built to apply standard scoring methods across different types of assessments, ensuring consistent and accurate results even with large datasets. By simplifying complex scoring procedures into a user-friendly process, ABCDscores streamlines research workflows, reduces errors, and saves researchers valuable time. The package aims to improve analyses of data from the ABCD Study® and can serve as a model for the development of similar tools and a standardized framework for other research studies, fostering new discoveries and innovation in the field.

Frontiers in NeuroinformaticsVol. 20
J. Craig Venter Institute (US)
Openalex Percentile: Top 10%
Health, Environment, Cognitive Aging
5.88
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

ABCDscores: an R package for computing summary scores in the ABCD Study® — Biplabendu Das, Calen J. Smith, et al. · Frontiers in Neuroinformatics (2026) | TGRS Research Map | TGRS