Evidence map›Paper›PMID 40002508›Full record

ArticleBrain sciences2025

Linguistic Prediction in Autism Spectrum Disorder.

Aimee O'Shea, Paul E Engelhardt

Abstract read
In one paragraph

Article in Brain sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Aimee O'SheaSchool of Psychology, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK.
Paul E EngelhardtSchool of Psychology, University of East Anglia, Norwich Research Park, Norwich NR4 7TJ, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAutism spectrum disorder has been argued to involve impairments in domain-general predictive abilities. There is strong evidence that individuals with ASD have trouble navigating the dynamic world due to an inability to predict the outcomes of particular events. There is also evidence that this is apparent across the diagnostic criteria of ASD and common among correlates of ASD. However, the question remains as to whether this impairment in predictive abilities is domain-specific or domain-general, with little research investigating prediction in linguistic measures.

methodsThe current study investigated whether individuals with ASD showed atypicalities in linguistic prediction using a cloze probability task. In Experiment 1, 33 individuals with ASD were compared to 64 typically developing individuals in an offline cloze task.

resultsThere was no significant effect of an ASD diagnosis on the cloze probability. However, individuals with higher levels of autistic traits were significantly more likely to produce lower-probability (non-modal) cloze responses. In Experiment 2, 19 individuals with ASD were compared to 22 typically developing individuals in a lab-based cloze task, in which we also measured the reaction times to begin speaking (i.e., voice onset time). The results showed that individuals with ASD had significantly slower reaction times (~200 ms) but, similarly to Experiment 1, did not show differences in the cloze probability of the responses produced.

conclusionsWe conclude that individuals with ASD do show inefficiency in linguistic prediction, as well as indicating which ASD traits most strongly correlate with these inefficiencies.

Indexed as

autism spectrum disordercloze probabilitylinguistic predictionvoice onset time

Identifiers

PMID40002508
PMCPMC11852888

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.