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Record W2381553266 · doi:10.1097/dbp.0000000000000304

Latent Profiles of Externalizing Psychopathology and Their Relation to Children's Aggression and Social Behavior

2016· article· en· W2381553266 on OpenAlexaff
Brendan F. Andrade, Mark Wade

Bibliographic record

VenueJournal of Developmental & Behavioral Pediatrics · 2016
Typearticle
Languageen
FieldPsychology
TopicPsychopathy, Forensic Psychiatry, Sexual Offending
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsAggressionProsocial behaviorPsychologyPsychopathologyDevelopmental psychologyConduct disorderSocial skillsClinical psychology

Abstract

fetched live from OpenAlex

OBJECTIVE: This study identified profiles of clinic-referred children with disruptive behavior and determined the association between identified profiles and children's aggression, peer problems, and prosocial skills. METHOD: Parents and teachers of 208 children (163 boys) aged 6 to 12 years (Mage = 8.80, SD = 1.75) completed measures to assess children's callous-unemotional (CU) traits, inattentive-impulsive-overactive (IO) and oppositional-defiant (OD) behavior, aggression, and social behaviors. Latent class analysis was used to identify the profiles, and the pseudoclass draw method to test the equality of means for each of the aggression and social behavioral outcomes across the latent classes. RESULTS: Five profiles were identified: (1) Low (35.6% of children), with relatively low levels of CU traits and IO and OD behavior; (2) Low-Moderate (30.8%), with low-moderate levels of CU traits, low IO and moderate OD behavior; (3) Moderate (21.6%), with moderate levels of CU traits and IO and moderate-high OD behavior; (4) Moderate-High (7.2%), with moderate-high levels of CU traits, high IO and moderate-high OD behavior; and (5) High (4.8%), with high levels of CU traits, IO and OD behavior. CONCLUSION: Children categorized into profiles showed important differences in level of aggression and social behavior. The overlap between CU traits, IO, and OD behavior add to understanding of child psychopathology that influences behavior and clinical outcomes.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.157
Threshold uncertainty score0.832

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.322
Teacher spread0.288 · 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 teacher head, 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

Citations6
Published2016
Admission routes1
Has abstractyes

Explore more

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