The Child Behavior Check List Usefulness in Screening for Severe Psychopathology in Youth: A Narrative Literature Review
Bibliographic record
Abstract
OBJECTIVE: This article will review the use of the CBCL to diagnose youth with psychopathological disorders focusing on: ADHD, Mood Disorders, Autism Spectrum disorders, and Disruptive Disorders. METHOD: Using a narrative review approach, we investigate the usefulness of the CBCL as a screening tool to detect childhood onset psychopathology across different diagnostic syndromes. RESULTS: The available literature supports the use of the CBCL for ADHD screening and as a measure of ADHD severity. While some studies support a specific profile linked with childhood bipolar disorder, replication studies for this profile found mixed results. The CBCL was also found to be useful in screening for patients presenting with Autism Spectrum Disorders, Conduct Disorder, and Childhood Bipolar Disorder all of which presents with more severely impaired scores. CONCLUSION: The CBCL holds promise as a screening tool for childhood psychopathology.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".