Nonverbal Executive Functioning in Relation to Vocabulary and Morphosyntax in Preschool Children With and Without Developmental Language Disorder
Bibliographic record
Abstract
PURPOSE: Developmental language disorder (DLD) is characterized by persistent and unexplained difficulties in language development. Accumulating evidence shows that children with DLD also present with deficits in other cognitive domains, such as executive functioning (EF). There is an ongoing debate on whether exclusively verbal EF abilities are impaired in children with DLD or whether nonverbal EF is also impaired, and whether these EF impairments are related to their language difficulties. The aims of this study were to (a) compare nonverbal performance of preschoolers with DLD and typically developing (TD) peers, (b) examine how nonverbal EF and language abilities are related, and (c) investigate whether a diagnosis of DLD moderates the relationship between EF and language abilities. METHOD: = 78) participated. All children were between 3 and 6.5 years old and were monolingual Dutch. We assessed nonverbal EF with a visual selective attention task, a visuospatial short-term and working memory task, and a task gauging broad EF abilities. Vocabulary and morphosyntax were each measured with two standardized language tests. We created latent variables for EF, vocabulary, and morphosyntax. RESULTS: Analyses showed that children with DLD were outperformed by their TD peers on all nonverbal EF tasks. Nonverbal EF abilities were related to morphosyntactic abilities in both groups, whereas a relationship between vocabulary and EF skills was found in the TD group only. These relationships were not significantly moderated by a diagnosis of DLD. CONCLUSIONS: We found evidence for nonverbal EF impairments in preschool children with DLD. Moreover, nonverbal EF and morphosyntactic abilities were significantly related in these children. These findings may have implications for intervention and support the improvement of prognostic accuracy. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.24121287.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".