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Record W4413077897 · doi:10.1080/19411243.2025.2531332

Application of the participation-based therapy for autistic children with moderate and high support needs: Two case reports

2025· article· en· W4413077897 on OpenAlexaboutno aff
Lin-Ju Kang, Ming‐Chieh Hsieh

Bibliographic record

VenueJournal of Occupational Therapy Schools & Early Intervention · 2025
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsnot available
Fundersnot available
KeywordsOccupational therapyAutismPsychologyAssistive technologySpecial needsDevelopmental psychologyPlay therapyClinical psychologyPsychotherapistPsychiatryComputer science

Abstract

fetched live from OpenAlex

Children on the Autism Spectrum often experience restrictions in participation due to social and functional limitations as well as environmental barriers. Participation-based therapy (PBT) is a goal-oriented, family-centered, and solution-focused approach to optimize daily participation. The case reports presented the process and outcomes of a 12-week PBT in promoting community participation of two autistic children with moderate and high support needs aged 7 and 8 years. The mothers of both children were actively engaged in the intervention process. Outcome measures, the Canadian Occupational Performance Measure (COPM) and Goal Attainment Scaling (GAS), were conducted pre-intervention, post-intervention at 12 weeks, and follow-up at 24 weeks. In terms of outcomes, one child showed improvement in COPM scores and achieved the expected level of attainment in GAS after the intervention and at follow-up. The other child demonstrated slower progress in COPM but reached the expected level of attainment in GAS by the follow-up assessment. The case reports provided initial support for the immediate and sustained effects of PBT on community participation of autistic children.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.073
Threshold uncertainty score0.372

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.053
GPT teacher head0.417
Teacher spread0.364 · 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 teacher head, 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

Citations0
Published2025
Admission routes1
Has abstractyes

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