What Is the Impact of Second Language Exposure and Intellectual Disability Status on Executive Function and Functional Communication Outcomes in Children and Adolescents With and Without Autism Spectrum Disorder ( <scp>ASD</scp> )?
Bibliographic record
Abstract
Over the past 10 years, research has suggested no negative effect on second language exposure in children with autism spectrum disorder (ASD), yet, parents and professionals may be concerned that using a second language with a child with ASD may negatively impact their communication and cognitive skills, especially if the child also has an intellectual disability. In this study, 396 children and adolesents (5-16 years) with and without ASD and with and without second language exposure participated in the study. Parents reported on language exposure and rated executive function (EF) and functional communication (FC) skills using a standardized questionnaire. IQ was directly measured using the WASI-II and children were classified as having an intellectual disability if they had a full-scale score of less than 70. The sample included 18 children with ASD and an intellectual disability (10 without second language exposure, 8 with second language exposure). Results showed that children with ASD and second language exposure had significantly better EF skills and were significantly less likely to have executive dysfunction in the clinical range than children with ASD with no second language exposure. Second language exposure also did not have a negative impact on EF skills in children with ASD even when an intellectual disability was present. For FC skills, we failed to find significant difference between children with ASD with and without second language exposure. For children with ASD and intellectual disability, there was no significant difference on FC skills between children with and without second language exposure. As our sample of children with ASD and intellectual disability was small, additional research with a larger sample is urgently needed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".