Sensory-Based Approaches in Intervention for Children With Autism Spectrum Disorder: Influences on Occupational Therapists’ Recommendations and Perceived Benefits
Bibliographic record
Abstract
OBJECTIVE: We investigated factors that influenced occupational therapists' beliefs about and use of sensory-based approaches for children with autism spectrum disorder (ASD). METHOD: Occupational therapists working with children with ASD (N = 211 from 16 countries) completed an online survey addressing their work experience, training, use of sensory-based approaches, and beliefs and perceptions about the effects of the approaches. Linear regression was used to determine predictors of use of and beliefs about sensory-based approaches. RESULTS: Most respondents (98%) used sensory-based approaches for children with ASD and would recommend the approaches for 57% of the children they treated. Having a mentor who promoted sensory-based approaches and practicing outside North America and Australia predicted greater use and perceived effectiveness of these approaches. Less than 5 yr of occupational therapy experience predicted less use of the approaches. CONCLUSION: Respondents selectively used sensory-based approaches for children with ASD and were influenced by country of residence, clinical experience, and mentorship.
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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 | 0.004 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".