The impact of person–environment–occupation transactions on joint attention in children with autism spectrum disorder: A scoping review
Bibliographic record
Abstract
Introduction Individuals with autism spectrum disorder demonstrate difficulty with joint attention, affecting social and occupational performance. Studies of joint attention in children with autism spectrum disorder employ a variety of instrumentation, environments and occupations. From the occupational therapy perspective, current literature lacks a rigorous analysis of the transactions of person, environment and occupation embedded within the procedures of these studies. The goal of this scoping review was to investigate how these components transact to affect occupational performance. Method Using the Person–Environment–Occupation model as an evaluative lens, a scoping review was completed to summarize person, environment and occupation transactions in studies examining joint attention in children aged 6–12 years with autism spectrum disorder. Results Six studies were included. Findings indicated that simplified social environments and demonstrations of joint attention promoted higher joint attention performance in children with autism spectrum disorder, at the cost of ecological validity. Maintaining ecological validity in complex social environments resulted in lower joint attention performance. Conclusion The Person–Environment–Occupation model can be used to develop an occupational therapy perspective on literature from outside the discipline. There is a relationship between the person, environment, occupation transactions and joint attention in children with autism spectrum disorder.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".