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Record W2119868994 · doi:10.1177/1087054711401346

Social Information Processing of Positive and Negative Hypothetical Events in Children With ADHD and Conduct Problems and Controls

2011· article· en· W2119868994 on OpenAlexaff
Brendan F. Andrade, Daniel A. Waschbusch, Amelie Doucet, Sará King, Maura MacKinnon, Patrick J. McGrath, Sherry H. Stewart, Penny Corkum

Bibliographic record

VenueJournal of Attention Disorders · 2011
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsDalhousie UniversityMount Saint Vincent UniversityCentre for Addiction and Mental Health
Fundersnot available
KeywordsPsychologySituational ethicsDevelopmental psychologySocial information processingClinical psychologyConduct disorderCognitionPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: This study examined social information processing (SIP) of events with varied outcomes in children with ADHD and conduct problems (CPs; defined as oppositional defiant disorder [ODD] or conduct disorder [CD]) and controls. METHOD: Participants were 64 children (46 boys, 18 girls) aged 6 to 12, including 39 with ADHD and 25 controls. Vignettes were developed that systematically varied with regard to peer intention (ambiguous, negative, positive) and event outcome (ambiguous, negative, positive), and were used to evaluate participants' SIP abilities (cue encoding, interpretation, and response generation). RESULTS: Results showed that, after controlling for CPs, children with ADHD detected fewer positive, negative, and neutral cues; attributed more negative and less positive intent to peers; focused less on situational outcomes of vignettes; and generated fewer positive responses compared with the control group. CONCLUSION: These results indicate that children with ADHD differ from non-ADHD children, even after controlling for CPs, in how they process positive and negative social experiences.

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)0.006
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.292
Teacher spread0.257 · 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

Citations56
Published2011
Admission routes1
Has abstractyes

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