Does occupational therapy play a role for communication in children with autism spectrum disorders?
Bibliographic record
Abstract
This study investigates occupational therapy for early communication in children with autism spectrum disorders (ASD). The research explored the role of occupational therapists in supporting children with ASD to become better communicators by considering their inter-professional collaboration with speech-language pathologists. Convenience samples of 21 clinical occupational therapists and speech-language pathologists were recruited to participate in semi-structured audio-recorded focus groups, using a qualitative design. Distinct views included a child-centred focus from speech-language pathologists, whereas occupational therapists spoke of the child through societal viewpoints, which later pointed to occupational therapists' proficiency in enabling skill generalization in ASD. An equal partnership was consistently reported between these clinicians, who identified the same objectives, shared strategies, joint treatments, and ongoing collaboration as the four main facilitators to inter-professional collaboration when treating children with ASD. Three unique roles of occupational therapy comprised developing non-verbal and verbal communication pre-requisites, adapting the setting, educating-partnering-advocating for the child, and providing occupation-based intervention. These three themes meshed with the discipline-specific occupational therapy domains represented in the Person-Environment-Occupation framework. When working in inter-professional collaboration, speech-language pathologists and occupational therapists agree that occupational therapy is indispensable to early intervention in enabling communication in ASD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".