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Regression of language and non‐language skills in pervasive developmental disorders

2008· article· en· W2094580611 on OpenAlexaff
Alain Meilleur, Éric Fombonne

Bibliographic record

VenueJournal of Intellectual Disability Research · 2008
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsMcGill UniversityMontreal Children's HospitalUniversité de Montréal
Fundersnot available
KeywordsAutismPervasive developmental disorderPsychologyDevelopmental disorderLanguage developmentDevelopmental psychologyAsperger syndrome

Abstract

fetched live from OpenAlex

BACKGROUND: As part of the pervasive developmental disorders (PDD), there is a subgroup of individuals reported to have a different onset of symptom appearance consisting of an apparently normal early development, followed by a loss of verbal and/or non-verbal skills prior to 2 years of age. This study aims at comparing the symptomatology of children who displayed a regression and often an associated intellectual disability through investigation of two types of loss, namely language and other skill regression. METHODS: This study examined the occurrence of regression in 135 children with PDD, mean age 6.3 years. The sample was composed of 80 (59.4%) children diagnosed with autism, 44 (32.6%) with pervasive developmental disorder-not otherwise specified (PDD-NOS) and 11 (8%) with Asperger syndrome. The Autism Diagnostic Interview Revised (ADI-R) was used to evaluate the type of loss and to characterise associated factors including birth rank, gender and thimerosal exposure through vaccination. RESULTS: A total of 30 (22%) subjects regressed: nine (30%) underwent language regression alone, 17 (57%) lost a skill other than language and four (13%) lost both language and another skill. Significantly higher levels of regression were found in autism (30%) compared with PDD-NOS (14%) and Asperger syndrome (0%). Children who regressed in language skills spoke at a significantly earlier age ( = 12 months) than those who did not regress in this domain ( = 26 months). Parents and interviewers consistently reported developmental abnormalities prior to the loss. ADI-R domain mean scores indicated a more severe autistic symptomatology profile in children who regressed compared with those who did not, especially in the repetitive behaviour domain. Regression was not associated to thimerosal exposure, indirectly estimated by year of birth. CONCLUSIONS: A loss of skill, present in one out of five children with PDD, is associated with a slightly more severe symptomatology as measured by the ADI-R, particularly in the repetitive behaviours domain. Furthermore, although abnormalities are often noticed by the caregivers at the time of regression, the ADI-R reveals that other atypical behaviours were in fact present prior to the onset of regression in most cases. None of the secondary factors investigated were associated with regression. In children unexposed to thimerosal-containing vaccines, the rate of regression was similar to that reported in studies of samples exposed to thimerosal, suggesting that thimerosal has no specific association with regressive autism.

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)0.000
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 score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.054
GPT teacher head0.376
Teacher spread0.322 · 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

Citations95
Published2008
Admission routes1
Has abstractyes

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