Developmental Trajectory of Language From 2 to 13 Years in Children Born Very Preterm
Bibliographic record
Abstract
OBJECTIVES: The objective of this study was to describe language functioning at 13 years of age and examine its developmental trajectory from 2 to 13 years of age in children born very preterm (VP) compared with term controls. METHODS: Two hundred and twenty-four children born VP (<30 weeks’ gestation) and 77 term controls had language skills assessed by using performance-based and/or parent-report measures at 2, 5, 7, and 13 years of age. Regression models were used to compare verbal memory, grammar, semantics, and pragmatic skills between the VP and term groups at 13 years of age. Linear mixed effects regression models were used to assess language trajectories from 2 to 13 years of age. RESULTS: Compared with term controls, children born VP had poorer functioning across all components of language (mean group differences ranged from −0.5 SD to −1 SD; all P < .05) at 13 years of age. At each follow-up age, the VP group displayed poorer language functioning than the term controls, with the groups exhibiting similar developmental trajectories (slope difference = −0.01 SD per year; P = .55). CONCLUSIONS: Children born VP continue to display language difficulties compared with term controls at 13 years of age, with no evidence of developmental “catch-up.” Given the functional implications associated with language deficits, early language-based interventions should be considered for children born VP.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".