Factors associated with receptive and expressive language in autistic children and siblings: A systematic review
Bibliographic record
Abstract
Background & aimsLanguage abilities of autistic children and children at elevated likelihood for autism (EL-siblings) are highly heterogeneous, and many of them develop language deficits. It is as of yet unclear why language abilities of autistic children and EL-siblings vary, although an interaction of multiple influential factors is likely at play. In this review, we describe research articles that identify one or multiple of such factors associated with the receptive or expressive language abilities of autistic children and EL-siblings since the introduction of the <i>DSM-5</i>. Our aim was to identify and summarize factors that are linked to language development in autistic children and siblings in the recent literature to ultimately gain insight into the heterogeneity of language abilities in these children.MethodsThe search strategy of this review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The following databases were consulted: Embase, MEDLINE, Web of Science Core Collection, and Scopus. Inclusion criteria for studies were the presence of a sample of autistic children no older than 7 years old who were diagnosed with autism spectrum disorder per the criteria of the <i>DSM-5</i>. Intervention studies and studies without an explicitly reported language measure were excluded. Risk of bias assessment was completed using the Newcastle–Ottawa Scales. Ultimately, 55 articles were included in this review.Main contributionFifty-six factors were identified to be related to receptive or expressive language abilities of autistic children and EL-siblings. They were grouped into three main categories: biological factors; psychosocial and environmental factors; and age-related and developmental factors, each with different subcategories. Although many of the identified variables were only examined in one article, some well-researched associated factors were reported across multiple studies and were present in both autistic children and EL-siblings, in particular joint attention, nonverbal cognitive abilities and frontal EEG power. Better insight in these factors associated with language abilities in autistic children and siblings at elevated likelihood can inform future intervention strategies to reduce language deficits and its corresponding negative consequences in these children.ConclusionsOur results confirm that multiple different factors likely underlie language deficits in autism. Important aspects that should be considered are, among others, social factors such as joint attention, child characteristics such as nonverbal cognition, and neurocognitive factors.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".