SENSORY PROCESSING ISSUES AND OCCUPATIONAL ENGAGEMENT AMONG CHILDREN WITH AUTISM SPECTRUM DISORDERS
Bibliographic record
Abstract
Children with Autism Spectrum Disorder (ASD) experience sensory processing issues, affecting their daily behaviour and functional performance. Occupational engagement is viewed as activities a person participates in which involve occupational performance and environmental factors. This study aims to identify impaired sensory processing and occupational engagement, the relationship with demographic profile, and the relationship between impaired sensory processing and occupational engagement among children with ASD. A total of 169 children with ASD from a centre in Sentul were recruited. School Companion Sensory Profile and the Short Child Occupational Profile (SCOPE) were used as the outcome measurements in this study. The research finding yields those children with ASD appear to experience some degree of processing issues in “avoiding” sensory patterns and appear to have significant challenges in “communication and interaction skills” in their occupational engagement. Sensory processing issues and activity engagement are also found to be a minimal to moderate relationship with the demographic profiles of the children. The study also concludes that sensory processing and occupational engagement among children with ASD are interrelated. The correlation coefficients range from r = -0.20 to r = -0.36 indicating a fair to moderate correlation between sensory processing and occupational engagement. These sensory processing issues significantly impact children’s life, which can be seen through their level of engagement in daily life activities. Information on sensory processing issues and occupational engagement allows one to identify successful intervention strategies.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".