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Sentence Prediction Deficits in Developmental Language Disorder Are a Product of Vocabulary Knowledge and Processing Abilities.

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Title: Sentence Prediction Deficits in Developmental Language Disorder Are a Product of Vocabulary Knowledge and Processing Abilities.
Authors: Kueser, Justin B.1 justin.kueser@boystown.org, Outzen, Claney2, Borovsky, Arielle2, Deevy, Patricia2, Leonard, Laurence B.2
Source: Journal of Speech, Language & Hearing Research. May2026, Vol. 69 Issue 5, p2219-2242. 24p.
Subject Terms: *Phonological awareness, *Attention, *Language disorders, *Vocabulary, *Short-term memory, Cognition disorders diagnosis, Task performance, Speech, Research funding, Cognitive processing speed, Logistic regression analysis, Descriptive statistics, Psychology of movement, Neuropsychological tests, Reaction time, Data analysis software, Eye movements
Geographic Terms: Indiana
Abstract: Purpose: Children with developmental language disorder (DLD) have difficulty making online predictions of language material following verbs (e.g., "The monkey eats a very delicious . . . [banana]"). We explore the contributions of lexicosemantic knowledge deficits and online processing deficits by comparing performance across offline lexicosemantic and online processing tasks in sentences with higher versus lower speed and complexit y. Method: Participants included twenty-six 4- to 5-year-old children with DLD and 26 age-matched children with typical development (TD). In Experiment 1, participants' lexicosemantic knowledge about verb–patient associates was assessed (e.g., "What do babies usually wear? A bib or a necklace?") in an offline pointing task. Following the offline task, participants' online predictive processing for the same verb–patient associates was assessed using eye tracking (e.g., "The baby is wearing a very special [bib vs. necklace]"). In Experiment 2, the same tasks were completed with simpler sentences spoken at a slower rate with a reduced number of words. Results: Across the two experiments, the quality of lexicosemantic knowledge impacted the quality of sentence prediction for children in both groups. In addition, children with DLD had poorer lexicosemantic knowledge compared to peers with TD. Yet even after accounting for item-level lexicosemantic knowledge, the children with DLD differed from their peers with TD in sentence prediction. Specifically, children with DLD showed similar sentence prediction to peers with TD in faster sentences, but in slower sentences, their predictions decayed over time. Conclusions: Children with DLD have sentence prediction deficits due to a combination of lexicosemantic knowledge deficits and problems with working memory decay and sustained attention. Sentence prediction deficits in DLD arise from both lexicosemantic and processing factors. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Speech, Language & Hearing Research is the property of American Speech-Language-Hearing Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Education Research Complete
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  Data: Sentence Prediction Deficits in Developmental Language Disorder Are a Product of Vocabulary Knowledge and Processing Abilities.
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  Data: <searchLink fieldCode="AR" term="%22Kueser%2C+Justin+B%2E%22">Kueser, Justin B.</searchLink><relatesTo>1</relatesTo><i> justin.kueser@boystown.org</i><br /><searchLink fieldCode="AR" term="%22Outzen%2C+Claney%22">Outzen, Claney</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Borovsky%2C+Arielle%22">Borovsky, Arielle</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Deevy%2C+Patricia%22">Deevy, Patricia</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Leonard%2C+Laurence+B%2E%22">Leonard, Laurence B.</searchLink><relatesTo>2</relatesTo>
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Speech%2C+Language+%26+Hearing+Research%22">Journal of Speech, Language & Hearing Research</searchLink>. May2026, Vol. 69 Issue 5, p2219-2242. 24p.
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  Data: Purpose: Children with developmental language disorder (DLD) have difficulty making online predictions of language material following verbs (e.g., "The monkey eats a very delicious . . . [banana]"). We explore the contributions of lexicosemantic knowledge deficits and online processing deficits by comparing performance across offline lexicosemantic and online processing tasks in sentences with higher versus lower speed and complexit y. Method: Participants included twenty-six 4- to 5-year-old children with DLD and 26 age-matched children with typical development (TD). In Experiment 1, participants' lexicosemantic knowledge about verb–patient associates was assessed (e.g., "What do babies usually wear? A bib or a necklace?") in an offline pointing task. Following the offline task, participants' online predictive processing for the same verb–patient associates was assessed using eye tracking (e.g., "The baby is wearing a very special [bib vs. necklace]"). In Experiment 2, the same tasks were completed with simpler sentences spoken at a slower rate with a reduced number of words. Results: Across the two experiments, the quality of lexicosemantic knowledge impacted the quality of sentence prediction for children in both groups. In addition, children with DLD had poorer lexicosemantic knowledge compared to peers with TD. Yet even after accounting for item-level lexicosemantic knowledge, the children with DLD differed from their peers with TD in sentence prediction. Specifically, children with DLD showed similar sentence prediction to peers with TD in faster sentences, but in slower sentences, their predictions decayed over time. Conclusions: Children with DLD have sentence prediction deficits due to a combination of lexicosemantic knowledge deficits and problems with working memory decay and sustained attention. Sentence prediction deficits in DLD arise from both lexicosemantic and processing factors. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Journal of Speech, Language & Hearing Research is the property of American Speech-Language-Hearing Association and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1044/2026_JSLHR-25-00121
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      – Code: eng
        Text: English
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    Subjects:
      – SubjectFull: Phonological awareness
        Type: general
      – SubjectFull: Attention
        Type: general
      – SubjectFull: Language disorders
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      – SubjectFull: Vocabulary
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      – SubjectFull: Speech
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      – SubjectFull: Research funding
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      – SubjectFull: Cognitive processing speed
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      – SubjectFull: Logistic regression analysis
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      – SubjectFull: Data analysis software
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      – SubjectFull: Eye movements
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      – SubjectFull: Indiana
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      – TitleFull: Sentence Prediction Deficits in Developmental Language Disorder Are a Product of Vocabulary Knowledge and Processing Abilities.
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              Text: May2026
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              Y: 2026
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