Cognitive and linguistic effects of narrative-based language intervention in children with Developmental Language Disorder
Why this work is in the frame
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Bibliographic record
Abstract
Background and aims: Narrative-based language intervention provides a naturalistic context for targeting overall story structure and specific syntactic goals in children with Developmental Language Disorder (DLD). Given the cognitive demands of narratives, narrative-based language intervention also has the potential to positively impact related abilities such as working memory and academic skills. Methods: Ten children (8-11 years old) with DLD completed 15 sessions of narrative-based language intervention. Results: Results of single subject data revealed gains in language for five participants, four of whom improved on a probe tapping working memory. An additional four participants improved on a working memory probe only. On standardized measures, clinically significant gains were noted for one additional participant on a language measure and one additional participant on a visuospatial working memory. Carry over to reading was noted for three participants and to math for one participant. Across measures, gains in both verbal and visuospatial working memory were common. A responder analysis revealed that improvement in language may be associated with higher verbal short-term memory and receptive language at baseline. Those with working memory impairments were among those showing the fewest improvements across measures. Conclusions: Narrative-based language intervention impacted verbal skills in different ways across individual children with DLD.Implications: Further research is needed to gain an understanding of who benefits most from narrative-based language intervention.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it