Generalized Slowing Rather Than Inhibition Is Associated With Language Outcomes in Both Late Talkers and Children With Typical Early Development
Bibliographic record
Abstract
Purpose While most of the children who are identified as late talkers at the age of 2 years catch up with their peers before school age, some continue to have language difficulties and will later be identified as having developmental language disorder. Our understanding of which children catch up and which do not is limited. The aim of the current study was to find out if inhibition is associated with late talker outcomes at school age. Method We recruited 73 school-aged children (ages 7–10 years) with a history of late talking ( n = 38) or typical development ( n = 35). Children completed measures of language skills and a flanker task to measure inhibition. School-age language outcome was measured as a continuous variable. Results Our analyses did not reveal associations between inhibition and school-age language index or history of late talking. However, stronger school-age language skills were associated with shorter overall response times on the flanker task, in both congruent and incongruent trials. This effect was not modulated by history of late talking, suggesting that a relationship between general response times and language development is similar in both children with typical early language development and late talkers. Conclusions Inhibition is not related to late talker language outcomes. However, children with better language outcomes had shorter general response times. We interpret this to reflect differences in general processing speed, suggesting that processing speed holds promise for predicting school-age language outcomes in both late talkers and children with typical early development. Supplemental Material https://doi.org/10.23641/asha.14226722
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".