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

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 c...

Descripción completa

Detalles Bibliográficos
Publicado en:Journal of Speech, Language & Hearing Research Vol. 69; no. 5; pp. 2219 - 2243
Autores principales: Kueser, Justin B., Outzen, Claney, Borovsky, Arielle, Deevy, Patricia, Leonard, Laurence B.
Formato: Artículo
Publicado: American Speech-Language-Hearing Association May2026
Materias:
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=193696214&site=ehost-live
header:
  @attributes:
    shortDbName: ssf
    uiTerm: 193696214
    longDbName: Social Sciences Full Text (H.W. Wilson)
    uiTag: AN
  controlInfo:
    bkinfo:
    jinfo:
      jid:
        10924388
        1SM
      jtl: Journal of Speech, Language & Hearing Research
      issn: 10924388
      maglogo: N
    pubinfo:
      dt: May2026
      vid: 69
      iid: 5
      pid: 42
      pub: American Speech-Language-Hearing Association
    artinfo:
      ui:
        193696214
        10.1044/2026_JSLHR-25-00121
      ppf: 2219
      ppct: 24
      formats:
        fmt:
          @attributes:
            type: P
            size: 4.1MB
      tig:
        atl: Sentence Prediction Deficits in Developmental Language Disorder Are a Product of Vocabulary Knowledge and Processing Abilities.
      aug:
        au:
          Kueser, Justin B.
          Outzen, Claney
          Borovsky, Arielle
          Deevy, Patricia
          Leonard, Laurence B.
        affil:
          Boys Town National Research Hospital, Omaha, NE.
          Purdue University, West Lafayette, IN.
      su:
        Indiana
        Task performance
        Speech
        Attention
        Language disorders
        Vocabulary
        Cognition disorders diagnosis
        Research funding
        Phonological awareness
        Cognitive processing speed
        Logistic regression analysis
        Descriptive statistics
        Psychology of movement
        Neuropsychological tests
        Reaction time
        Data analysis software
        Short-term memory
        Eye movements
      sug:
        subj:
          Task performance
          Speech
          Attention
          Language disorders
          Vocabulary
          Indiana
          Cognition disorders diagnosis
          Research funding
          Phonological awareness
          Cognitive processing speed
          Logistic regression analysis
          Descriptive statistics
          Psychology of movement
          Neuropsychological tests
          Reaction time
          Data analysis software
          Short-term memory
          Eye movements
      ab: 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.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
    refInfo:
    copyright:
      @attributes:
        flag: N
    holdings:
      @attributes:
        islocal: N