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Record W4390080683 · doi:10.1177/23969415231221516

Predictors of Picture Exchange Communication System (PECS) outcomes

2023· article· en· W4390080683 on OpenAlexaff
Julie Koudys, Adrienne Perry, Carly Magnacca, Kristen McFee

Bibliographic record

VenueAutism & Developmental Language Impairments · 2023
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsBC Children's HospitalYork UniversityBrock University
Fundersnot available
KeywordsPsychologyAutism spectrum disorderCognitionAutismDevelopmental psychologyNonverbal communicationIntervention (counseling)Clinical psychologyGeneralizationPsychiatry

Abstract

fetched live from OpenAlex

Background & aims: Although the Picture Exchange Communication System (PECS) has been demonstrated to be an effective intervention to teach people diagnosed with autism spectrum disorder a functional communication system, the research indicates variability in PECS outcomes across people and studies. Therefore, the purpose of the current study was to explore child characteristics and treatment variables that may explain the variation in, and potentially predict, PECS outcomes. Method: A total of 22 children and youth diagnosed with autism or a related developmental disorder, all of whom scored substantially below average on standardized measures of cognitive and adaptive abilities, participated in a PECS intervention. Results: Participants who achieved high phases of PECS (≥PECS phase IIIb) differed significantly from those who mastered lower PECS phases (≤PECS phase IIIa) in terms of overall, verbal, and nonverbal mental age, matching abilities, and adaptive behavior level. Stimulus generalization was also associated with significant variation in PECS outcome. PECS outcomes could be predicted with good accuracy using a combination of these child characteristics and treatment variables. Conclusions: The findings from the current study suggest that children with relatively higher cognitive and adaptive skill levels are more likely to achieve higher phases of PECS; further, approaches to generalization training also play a role. Factors such as autism symptom severity and parental ratings of maladaptive behavior were not associated with significant differences in PECS outcomes. However, more research is needed. Implications: Gaining a better understanding of predictors of PECS outcomes is important to inform intervention, provide more accurate outcome expectations for families, and guide PECS teaching procedures. Although participants were more likely to achieve higher phases of PECS if they had a higher mental age, adaptive skill level, and matching skills, the average scores for these measures were well below those expected for same age peers. These results indicate that PECS is appropriate for use with children with clinically significant deficits in cognitive and/or adaptive abilities. Further, results suggest that even children who demonstrate more severe symptoms of autism and exhibit more challenging behavior can achieve higher phases of PECS.

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)0.008
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.020
GPT teacher head0.291
Teacher spread0.271 · 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
Published2023
Admission routes1
Has abstractyes

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