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Record W2058541114 · doi:10.1111/1467-8624.00144

Compulsive-like Behavior in Individuals with Down Syndrome: Its Relation to Mental Age Level, Adaptive and Maladaptive Behavior

2000· article· en· W2058541114 on OpenAlexfundno aff
David Evans, Fabienne L. Gray

Bibliographic record

VenueChild Development · 2000
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsnot available
FundersFordham UniversityMcGill UniversityYale University
KeywordsPsychologyAdaptive behaviorDevelopmental psychologyCompulsive behaviorTypically developingClinical psychologyAutism

Abstract

fetched live from OpenAlex

This study examined the nature of repetitive, ritualistic, and compulsive-like behaviors in 50 typically developing children and 50 individuals with Down syndrome (DS), matched on mental age (MA; M = 59.72 months). Parents reported on their children's compulsive-like behaviors-including ritualistic habits-and perfectionistic behaviors, as well as their children's adaptive and maladaptive behaviors. Results indicated that children with DS show similar MA-related changes in compulsive-like behaviors compared to the MA-matched comparison group. Younger children (both typical and DS) exhibited significantly more compulsive-like behaviors than older children. In general, children with and without DS did not differ from each other in terms of the number of compulsive-like behaviors they engaged in, although participants with DS engaged in more frequent, more intense repetitive behaviors. Compulsive-like behaviors were differentially related to adaptive and maladaptive behaviors across the MA and mental retardation groups. The results extend the "similar sequence" model of development to the construct of compulsive-like behaviors, and also suggest that some repetitive behaviors may be among the behavioral phenotype of individuals with DS.

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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.040
GPT teacher head0.280
Teacher spread0.240 · 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

Citations111
Published2000
Admission routes1
Has abstractyes

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