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Record W4367318427 · doi:10.1177/13623613231166189

Visual abilities and exploration behaviors as predictors of intelligence in autistic children from preschool to school age

2023· article· en· W4367318427 on OpenAlexafffund
Dominique Girard, Valérie Courchesne, Catherine Cimon‐Paquet, Claudine Jacques, Isabelle Soulières

Bibliographic record

VenueAutism · 2023
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversité du Québec à MontréalUniversité du Québec en OutaouaisHôpital Rivière-des-PrairiesCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean
FundersCanadian Institutes of Health Research
KeywordsNeurotypicalPsychologyDevelopmental psychologyAutismIntelligence quotientRaven's Progressive MatricesWechsler Preschool and Primary Scale of IntelligenceWechsler Adult Intelligence ScalePerceptionStanford–Binet Intelligence ScalesNonverbal communicationBorderline intellectual functioningTest (biology)Wechsler Intelligence Scale for ChildrenCognitionAutism spectrum disorder

Abstract

fetched live from OpenAlex

The current prospective cohort study investigated whether early perceptual abilities, measured at preschool age, could predict later intellectual abilities at school age in a group of 41 autistic (9 girls, 32 boys) and 57 neurotypical children (29 girls, 28 boys). More than 80% of the autistic children were considered minimally verbal. Participants were assessed at three time points between the age of 2 and 8 years using the Wechsler Preschool and Primary Scales of Intelligence–Fourth Edition as a measure of full-scale IQ and the Raven’s Colored Progressive Matrices as a measure of fluid reasoning abilities (Gf). The performance on two perceptual tests (Visual Search and Children Embedded Figures Test) and the frequency of early non-verbal behaviors served as predictors of later intellectual abilities. Early performance on perceptual tests measured at preschool age was positively related to later full-scale IQ in both autistic and neurotypical children. Furthermore, both early non-verbal behaviors and performance on perceptual tests measured at preschool age were associated with later Gf in the autistic group. In contrast, only the performance on Children Embedded Figures Test was associated with later Gf in the neurotypical group. Early perceptual abilities\and non-verbal behaviors may be indicators of general intelligence and Gf abilities. Lay Abstract At the time of diagnosis, parents of autistic children frequently wonder what the future holds for their children in terms of intellectual development. It remains however difficult to answer this question at such a young age. Indeed, while early precursors of intelligence are well known for children following a typical development, these precursors remain to be identified for autistic children. Some theoretical models of intelligence suggest that perceptual abilities or behaviors, as seen early in autistic cognitive development, could be early indicators of intelligence. However, research examining the relation between early perceptual predictors and autistic intelligence over time is needed. This article is the first to consider a variety of early perceptual abilities and behaviors as precursors/predictors of intelligence at school age in autistic children. We showed that better performance in perceptual tasks at preschool age predicted better intellectual abilities measured later in autistic children. Importantly, our sample of autistic children represented the whole spectrum, including children with few to no spoken words, who are an important proportion of autistic preschoolers. While early perceptual abilities and behaviors may not substitute for a formal intellectual assessment, our results support that these indices may help estimate later intellectual level in autistic children. Perceptual abilities have the advantage to be easy to observe at preschool age and seem to fit the cognitive style of autistic children. Assessment methods could probably gain from including and focusing more on the perceptual strengths of autistic children.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.273
Threshold uncertainty score0.731

Codex and Gemma teacher scores by category

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

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 head0.029
GPT teacher head0.327
Teacher spread0.298 · 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 teacher head, 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

Citations9
Published2023
Admission routes2
Has abstractyes

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