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Record W2979821589 · doi:10.1177/0829573519870923

Peer-Mediated Pivotal Response Treatment at School for Children With Autism Spectrum Disorder

2019· article· en· W2979821589 on OpenAlexaff
Ainsley M. Boudreau, Joseph M. Lucyshyn, Penny Corkum, Katelyn Meko, Isabel M. Smith

Bibliographic record

VenueCanadian Journal of School Psychology · 2019
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsIzaak Walton Killam Health CentreDalhousie UniversityUniversity of British ColumbiaBC Children's Hospital
FundersOrganization for Autism Research
KeywordsAutism spectrum disorderPsychologyAutismMultiple baseline designTypically developingFidelityClinical psychologyDevelopmental psychologyPeer groupSocial skillsIntervention (counseling)Psychiatry

Abstract

fetched live from OpenAlex

The main objective of the present study was to evaluate the efficacy of peer training in pivotal response treatment (PRT) for children with autism spectrum disorder (ASD) in their first year of school. Four 6-year-old boys with ASD and eight typically developing (TD) children (aged 4-6 years) participated in the study. A non-concurrent multiple-probe (across participants) baseline design was used. Outcomes were assessed before, immediately after, and 6 to 9 weeks following an eight-session training period. Overall, rates of peer engagement increased following training for three of the four children with ASD and rates of social initiation increased following training for two of the four children with ASD; these gains were maintained at follow-up. TD peers’ fidelity in implementing PRT techniques also improved. The present study suggests that relatively brief peer training in PRT can produce immediate and short-term sustained gains in peer-related social communication skills of children with ASD at school.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
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 science0.0010.001
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 head0.026
GPT teacher head0.313
Teacher spread0.287 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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Same venueCanadian Journal of School PsychologySame topicAutism Spectrum Disorder ResearchFrench-language works237,207