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Record W2111336685 · doi:10.1111/1469-7610.00617

Cognitive and Familial Contributions to Conduct Disorder in Children

2000· article· en· W2111336685 on OpenAlexaff
Jean Toupin, Michèle Déry, Robert Pauzé, Henri Mercier, Laurier Fortin

Bibliographic record

VenueJournal of Child Psychology and Psychiatry · 2000
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPsychologyConduct disorderCognitionDevelopmental psychologyClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Although young children with conduct disorder (CD) are suspected of having verbal and executive function deficits, most studies that investigated this hypothesis did not control for attention deficit hyperactivity disorder (ADHD). Furthermore, relatively little is known about the interaction between cognitive deficits and familial factors in explaining the onset and persistence of CD in children. The participants in this study were 57 children with CD and 35 controls aged 7 to 12 years. At 1-year follow-up, 41 of the participants with CD were reassessed. Children with CD were found to be significantly impaired in four of five executive function measures after ADHD symptoms and socioeconomic status (SES) were controlled. Executive function test performance, number of ADHD symptoms, and familial characteristics (SES, parental punishment) together correctly classified 90% of the participants. Only the number of ADHD symptoms was found to significantly improve prediction of CD 1 year later beyond that afforded by number of CD symptoms a year earlier. Findings indicate that children with CD and ADHD symptoms are especially at risk for persistent antisocial behaviour. Results also highlight the importance of treatment programs that cover both cognitive and familial aspects associated with CD.

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)0.001
metaresearch head score (Gemma)0.005
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 score0.054
Threshold uncertainty score0.106

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
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 head0.010
GPT teacher head0.320
Teacher spread0.310 · 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

Citations101
Published2000
Admission routes1
Has abstractyes

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