Article in Child psychiatry and human development, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.
0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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
1 citing paper in PubMed, 1 synthesis or guideline pooled it.
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
4 authors.
Kristen R ChoiSchool of Nursing, University of California Los Angeles, Los Angeles, CA, USA. krchoi@ucla.edu.
Erin C DunnDepartment of Sociology, College of Liberal Arts, Purdue University, West Lafayette, IN, USA.
W Scott ComuladaDepartment of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
Altaf SaadiDepartment of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Funding
ABCD-USA Consortium: Coordinating CenterU24DA041147 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI SANDRA A BROWN, TERRY L. JERNIGAN · 2015 to 2026
$52.0M
ABCD-USA Consortium: Data Analysis, Informatics and Resource CenterU24DA041123 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ANDERS M DALE · 2015 to 2026
$51.5M
Adolescent Substance Use Initiation: Disentangling neurocognitive risks from consequences using longitudinal and genetically-informed methodsU01DA041120 · NIDA · UNIVERSITY OF MINNESOTA · PI Monica Luciana, Sylia Wilson · 2015 to 2026
$34.5M
ABCD-USA Consortium: Research ProjectU01DA041089 · NIDA · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Joanna Jacobus, Susan F. Tapert · 2015 to 2026
$31.7M
Prospective Research Studies of Maturation (PRISM)- Research ProjectU01DA041134 · NIDA · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI ERIN MCGLADE, PERRY FRANKLIN RENSHAW · 2015 to 2026
$29.2M
ABCD-USA CONSORTIUM: RESEARCH PROJECTU01DA041048 · NIDA · CHILDREN'S HOSPITAL OF LOS ANGELES · PI Megan Marie Herting, ELIZABETH R SOWELL · 2015 to 2026
$28.7M
ABCD-USA Consortium: Research ProjectU01DA041106 · NIDA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Mary M Heitzeg, Chandra Sekhar Sripada · 2015 to 2026
$24.9M
FIU-ABCD: Pathways and Mechanisms to Addiction in the Latino Youth of South FloridaU01DA041156 · NIDA · FLORIDA INTERNATIONAL UNIVERSITY · PI Raul Gonzalez, Angela R Laird · 2015 to 2026
$22.8M
ABCD-USA Consortium: Research ProjectU01DA041148 · NIDA · OREGON HEALTH & SCIENCE UNIVERSITY · PI Damien A Fair, Rebekah S Huber · 2015 to 2026
$22.3M
ABCD-USA: NYC Research ProjectU01DA041174 · NIDA · YALE UNIVERSITY · PI Arielle Ryan Baskin-Sommers, Betty J Casey · 2015 to 2026
$19.7M
Adolescent Brain Cognitive Development (ABCD) Prospective Research in Studies of Maturation (PRISM) ConsortiumU01DA041117 · NIDA · UNIVERSITY OF MARYLAND BALTIMORE · PI LINDA CHANG, THOMAS M ERNST · 2015 to 2026
$19.5M
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
The purpose of this study was to: 1) examine the co-occurrence of household and community adverse childhood experiences (ACEs) among preadolescent youth using latent class analysis (LCA), and 2) examine the association of ACE latent clusters to clinical-range scores on the Child Behavior Checklist (CBCL). Data came from the baseline and year 1 survey of the Adolescent Brain Cognitive Development (ABCD) Study with 10,915 youth recruited from school-based catchment areas in the United States. We used LCA to examine 6 types of household adversity and 7 types of community adversity, including 4 types of discrimination. We identified 5 latent classes of household/community ACEs. The class with high levels of household and community ACEs together was most strongly associated with clinical-range CBCL scores in adjusted models. Assessing adversity comprehensively may improve identification of youth with elevated risk for behavioral symptoms, who are greatest in need of intervention.
Indexed as
AdversityCommunityDiscriminationLatent class analysis
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.
Latent Class Analysis of Household and Community Adversity Among Pre-Adolescent Youth in the United States. · full record | Socratic