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Record W2890494921 · doi:10.1002/bin.1646

Treating obsessive compulsive behavior and enhancing peer engagement in a preschooler with intellectual disability

2018· article· en· W2890494921 on OpenAlexaff
Emily L. Guertin, Tricia Vause, Heather Jaksic, Jan C. Frijters, Maurice A. Feldman

Bibliographic record

VenueBehavioral Interventions · 2018
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsBrock University
Fundersnot available
KeywordsPsychologyIntervention (counseling)Intellectual disabilityDevelopmental psychologyMultiple baseline designAdaptive behaviorClinical psychologySocial behaviorSocial skillsReinforcementCognitionAdaptive functioningPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

Intellectual disability (ID) is a neurodevelopmental disorder characterized by impairments in cognitive and adaptive functioning in social, practical, or conceptual domains. Individuals with ID present with higher‐order repetitive behaviors such as a need for sameness, ritualistic, and compulsive behaviors. Often referred to as obsessive compulsive behaviors (OCBs), these behaviors increase in prevalence between 2 and 5 years of age. The present study evaluated an exposure‐based behavioral intervention for decreasing OCBs and concomitantly increasing play skills in a 4‐year‐old boy with mild ID in an inclusive preschool setting. Using a multiple baseline across behaviors design, the intervention was associated with a decrease in target behaviors and an increase in the duration of peer social engagement, with results maintained at 3‐week follow‐up. The intervention consisted of exposure and response prevention with function‐based components. Procedures including prompting and reinforcement were generalized to parent and teacher mediators. This study provides preliminary support for the use of an exposure‐based behavioral intervention to treat OCBs in children of preschool age with ID.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.141
GPT teacher head0.420
Teacher spread0.279 · 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 designCase report
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
Published2018
Admission routes1
Has abstractyes

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