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Record W4415468723 · doi:10.1002/bin.70056

The Effects of Response‐Stimulus Pairing on Toy Play and Stereotypy in Three Children on the Autism Spectrum in China

2025· article· en· W4415468723 on OpenAlexaff
Yan Wei Li, Sheng Xu, Gabrielle T. Lee

Bibliographic record

VenueBehavioral Interventions · 2025
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsWestern University
FundersJilin Office of Philosophy and Social Science
KeywordsAutismStereotypyGeneralizationPairingAutism spectrum disorderIntervention (counseling)Affect (linguistics)

Abstract

fetched live from OpenAlex

ABSTRACT Children on the autism spectrum who exhibit a restricted range of interests may engage less in appropriate toy play and display stereotypy, which may negatively affect their social engagement and task performance. Our study replicated and extended prior research by implementing response‐stimulus pairing to increase appropriate toy play and decrease inappropriate toy play and stereotypy in three Chinese children (aged 4–5 years) on the autism spectrum. We used a multiple probe design across participants. Results indicated that the intervention effectively increased appropriate toy play while decreasing inappropriate toy play and stereotypy. These improvements were also observed during free play. Two weeks after the completion of the intervention, all participants maintained the target behavior. Future research should consider collecting generalization data from home settings and conducting more rigorous functional behavior assessments.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.130

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.040
GPT teacher head0.361
Teacher spread0.321 · 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 designNon-randomized trial
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

Citations0
Published2025
Admission routes1
Has abstractyes

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