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Record W4393091090 · doi:10.1177/13623613241239416

Autistic preschoolers display reduced attention orientation for competition but intact facilitation from a parallel competitor: Eye-tracking and behavioral data

2024· article· en· W4393091090 on OpenAlexaff
Luodi Yu, Zhiren Wang, Yuebo Fan, Lizhi Ban, Laurent Mottron

Bibliographic record

VenueAutism · 2024
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsUniversité de MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-MontréalCentre Intégré Universitaire de Santé et de Services Sociaux du Saguenay–Lac-Saint-Jean
FundersNational Natural Science Foundation of China
KeywordsAutismPsychologyEye trackingDevelopmental psychologyCompetition (biology)Tracking (education)CognitionSocial facilitationSocial relationFacilitationOrientation (vector space)Social psychologyNeuroscienceComputer science

Abstract

fetched live from OpenAlex

While overt social atypicalities remain a key component of the autistic phenotype, recent reframing of autistic social motivation suggests that these atypicalities do not overlap with their actual level of social engagement. Our study aimed to investigate autistic preschoolers’ visual attention toward social situations with unequal interactive load and determine the potential benefits of parallel competition, a form of lateral tutorship. The study observed 26 autistic preschoolers and 20 typically developing children. First, a gaze-contingent procedure measured visual attention toward videos of parallel competitive play, overtly cooperative play, and a non-social object. Then, a motor task and a cognitive task were conducted, both independently and with a parallel competitor to assess the effect of parallel engagement on children’s performance. Eye-tracking demonstrated autistic children displayed reduced attention toward competition than typically developing children. However, behavioral data revealed the presence of a parallel competitor significantly and similarly improved performance for autistics and typically developing children. These findings suggest a dissociation between social attention and social facilitation in young autistic children, indicating that atypical visual patterns toward social situations do not necessarily preclude them from benefiting from these situations. As such, activities parallel to the child activities, or lateral tutorship, may represent an addition to traditional joint-interactive activities in early education for autistic children. Lay Abstract Recent research suggests that we might have underestimated the social motivation of autistic individuals. Autistic children might be engaged in a social situation, even if they seem not to be attending to people in a typical way. Our study investigated how young autistic children behave in a “parallel” situation, which we call “parallel competition,” where people participate in friendly contests side-by-side but without direct interaction. First, we used eye-tracking technology to observe how much autistic children pay attention to two video scenarios: one depicting parallel competition, and the other where individuals play directly with each other. The results showed that autistic children looked less toward the parallel competition video than their typically developing peers. However, when autistic children took part in parallel competitions themselves, playing physical and cognitive games against a teacher, their performance improved relative to playing individually just as much as their typically developing peers. This suggests that even though autistic children pay attention to social events differently, they can still benefit from the presence of others. These findings suggest complementing traditional cooperative activities by incorporating parallel activities into educational programs for young autistic children. By doing so, we can create more inclusive learning environments for these 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.714
Threshold uncertainty score0.879

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.079
GPT teacher head0.388
Teacher spread0.309 · 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 designBench or experimental
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

Citations1
Published2024
Admission routes1
Has abstractyes

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