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Record W4307055239 · doi:10.1093/pch/pxac100.046

47 Prevalence of and Factors Associated with Language Impairment in Canadian Children with ASD

2022· article· en· W4307055239 on OpenAlexaffabout
Nolan Lee, Whitney Weikum, Angie Ip

Bibliographic record

VenuePaediatrics & Child Health · 2022
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsBC Children's Hospital
Fundersnot available
KeywordsAutism Diagnostic Observation ScheduleAutism spectrum disorderSpecific language impairmentLanguage impairmentComorbidityMedicineAutismFunctional impairmentPediatricsPopulationAttention deficit hyperactivity disorderClinical psychologyPsychiatryPsychologyDevelopmental psychology

Abstract

fetched live from OpenAlex

Abstract Background Autism Spectrum Disorder (ASD) is a life-long neurodevelopmental disorder affecting 1 in 66 Canadians aged 5-17, and language impairment is a common comorbidity in this population. We aimed to determine the relative prevalence of diagnosed language impairment in children with ASD. We also examined factors associated with language impairment in children with ASD. Objectives 1 – To determine the relative prevalence of language impairment in children diagnosed with ASD. 2 – To identify factors associated with language impairment in children with ASD. Design/Methods Our study sample included 6,862 children aged 0-19 years, assessed for ASD (61% diagnosed with ASD) between 2010-2017 in British Columbia, Canada. ASD was diagnosed by a provincially qualified specialist and the assessment included the use of the Autism Diagnostic Observation Schedule (ADOS-2) and Autism Diagnostic Interview-Revised (ADI-R). We also looked for associations between language impairment and gender, age, intellectual disability (ID), family history of language disorders, and attention deficit hyperactivity disorder (ADHD), using chi-square analyses. Results The overall prevalence of language impairment in children diagnosed with ASD (n = 1820, 44%) was similar to those not diagnosed (n = 1199, 44%). There was more mixed receptive/expressive (80% vs 65%) and less expressive only (22% vs 29%) language impairment in children diagnosed with ASD than without. Looking only at the children diagnosed with ASD, there was no significant difference when evaluating gender (boys 44%, girls 41%; p = 0.094), but younger age was positively associated with language impairment (age <6y 53%, ≥6y 24%; p < 0.01). Increasing severity of ID was negatively associated with language impairment (mild: 44%, p = 0.911; moderate: 33%, p = 0.001; severe: 21%, p < 0.001). Family history of speech language disorder was positively associated with language impairment (no family history 12%, family history 20%; p < 0.01). Presence of comorbid ADHD was negatively associated with language impairment (no ADHD 47%, ADHD 28%; p < 0.01). Conclusion In children who have been referred for an ASD assessment, the prevalence of language impairment is similar in those with and without ASD. Children with ASD are more likely to be diagnosed with mixed language impairment than expressive only language impairment, although this difference may in part be due to challenges in fully assessing a child with ASD’s receptive language.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.004
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.015
GPT teacher head0.275
Teacher spread0.260 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2022
Admission routes2
Has abstractyes

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