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Record W1538995304 · doi:10.1177/070674370705200110

Comparison of the Child Behavior Checklist Profiles between Community- and Clinic-Based Children with Attention Deficit Hyperactivity Disorder in Korea

2007· article· en· W1538995304 on OpenAlexvenueno aff
Cheon-Seok Suh, Jae‐Won Kim, Hanik K. Yoo, Jun‐Won Hwang, Boong‐Nyun Kim, Min‐Sup Shin, Soo-Churl Cho

Bibliographic record

VenueThe Canadian Journal of Psychiatry · 2007
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsnot available
Fundersnot available
KeywordsCBCLChild Behavior ChecklistAttention deficit hyperactivity disorderChecklistAttention deficitBehavior problemPsychologyPsychiatryAttention deficit disorderClinical psychologyIncidence (geometry)Medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of this study was to examine whether there is a difference in the behavioural characteristics of community- and clinic-based children with attention-deficit hyperactivity disorder (ADHD) in Korea. METHOD: The study included 75 community-based and 72 clinic-based subjects with ADHD. The parents of all the children completed the parent versions of the Child Behavior Checklist (CBCL). RESULTS: The community-based ADHD subjects scored significantly higher (P < 0.01) than clinic-based subjects in the Somatic Complaints and Delinquent Behaviour profiles of the CBCL. The community-based subjects with ADHD, combined subtype, showed significantly higher mean scores in the Somatic Complaints (P < 0.01) and Thought Problems (P < 0.05) profiles than the clinic-based subjects with ADHD, combined subtype. CONCLUSION: These findings suggest the possibility of an increased incidence of behavioural or emotional problems in community-based ADHD subjects when compared with clinic-based subjects in Korea.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.035
GPT teacher head0.335
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueThe Canadian Journal of Psychiatry→Same topicAttention Deficit Hyperactivity Disorder→French-language works237,207→