Response to intervention services for preschool children with developmental language disorder: Opinions of school and health care service professionals and managers
Bibliographic record
Abstract
Background. Children with developmental language disorder (DLD) are less prepared for school than typically developing children and are therefore at risk for academic, social, and behavioral difficulties when they enter school. To support these children, early family-centered intervention is recommended. However, access to effective care remains an issue. Researchers have therefore suggested to reconsider the place of individual specialized intervention within a broader systemic response to intervention (RTI) framework. The aim of this study is to explore the opinions of professionals and managers working with children aged 0–5 with language difficulties on strategies to better support their school readiness. Specifically, it explores the facilitators and barriers to school readiness in children with DLD as well as strategies to better prepare them for school. Finally, it examines how an RTI model can provide a framework for services to preschool children with DLD. Methods. Two focus groups were conducted with 15 professionals and managers in the health care and school systems in the province of Quebec (Canada). The interviews were analyzed using an analytical questioning strategy. Results. Five key elements in service delivery were deemed essential in supporting school readiness of children with language difficulties: (1) maximizing community initiatives, (2) training and supporting partners, (3) supporting change in practice, (4) offering flexible services adapted to children's needs, and (5) implementing mechanisms to ensure service continuity and information transfer between agencies. These key elements are conceptualized within the RTI model. Conclusion. The five key elements identified in this study should be part of an intervention model in order to optimize service organization and better support school readiness for children with DLD.
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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 | 0.011 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".