Evidence map›Paper›PMID 42147011›Full record

ArticleFrontiers in psychiatry2026

Measurement properties of the Child Behavior Checklist-10: an ultra-brief screening updated in longitudinal cohort.

Chen Jiang, Xuejun Gu, Sixuan Li, Xudong Zhao, Fang Cai, Yi Zheng, Kun Zhang, Linlin Ding, Sujun Hu, Tingting Zhou and 3 more

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 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

13 authors.

Chen JiangWomen and Children's Hospital of Ningbo University, Ningbo, Zhejiang, China.
Xuejun GuWomen and Children's Hospital of Ningbo University, Ningbo, Zhejiang, China.
Sixuan LiNingbo Municipal Center for Disease Control and Prevention, Ningbo, Zhejiang, China.
Xudong ZhaoWomen and Children's Hospital of Ningbo University, Ningbo, Zhejiang, China.
Fang CaiWomen and Children's Hospital of Ningbo University, Ningbo, Zhejiang, China.
Yi ZhengWomen and Children's Hospital of Ningbo University, Ningbo, Zhejiang, China.
Kun ZhangWomen and Children's Hospital of Ningbo University, Ningbo, Zhejiang, China.
Linlin DingWomen and Children's Hospital of Ningbo University, Ningbo, Zhejiang, China.
Sujun HuWomen and Children's Hospital of Ningbo University, Ningbo, Zhejiang, China.
Tingting ZhouWomen and Children's Hospital of Ningbo University, Ningbo, Zhejiang, China.
Yingbo LvWomen and Children's Hospital of Ningbo University, Ningbo, Zhejiang, China.
Chanrong FuWomen and Children's Hospital of Ningbo University, Ningbo, Zhejiang, China.
Wei ChengWomen and Children's Hospital of Ningbo University, Ningbo, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To develop a brief behavioral screening tool for youth, we sought to reduce the Child Behavior Checklist (CBCL) by selecting the most informative items, establish its structural model, and evaluate comprehensive psychometric properties for potential attention deficit and hyperactivity disorder (ADHD) screening across diverse populations. Methods: Longitudinal data from the Future of Families and Child Wellbeing Study (FFCWS) were analyzed across three time points. Using a split-sample approach, we aimed to reduce the 34-item CBCL by integrating exploratory graph analysis (EGA) and graded response model (GRM). The final instrument would be evaluated for measurement properties. Results: Using a sample of 1,786 youth (49.5% female; 51.4% Black/African American), we systematically reduced the 34-item CBCL to a 10-item version (CBCL-10) with a three-factor structure. The CBCL-10 delineated excellent structural validity, supportive measurement invariances, and high internal consistency. The receiver operating characteristic analysis revealed good diagnostic efficiency for ADHD (area under the curve [AUC; 95% CI] = 0.843 [0.818-0.867]), with optimal sensitivity of 0.797 and specificity of 0.736 at a cutoff score of 3. Conclusions: The present study successfully developed a psychometrically sound CBCL-10 with a diagnostic efficiency for measuring youth attention/behavioral problems. Without sacrificing measurement quality, CBCL-10 offers clinicians and researchers a feasible assessment tool that captures the most diagnostically relevant attention and behavioral manifestations of ADHD.

Indexed as

Child Behavior Checklistconfirmatory factor analysisexploratory graph analysisFuture of Families and Child Wellbeing Studymeasurement invariancesreceiver operating characteristic

Identifiers

PMID42147011
PMCPMC13171534

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.