Factors Contributing to Preschoolers' Communicative Participation Outcomes: Findings From a Population-Based Longitudinal Cohort Study in Ontario, Canada
Bibliographic record
Abstract
Purpose: The aim of this study was to identify predictors of communicative participation outcomes for a large cohort of preschoolers with speech and language impairments. Method: A secondary analysis of longitudinal program evaluation data from Ontario, Canada's Preschool Speech and Language Program was done. Data available for 46,872 children 18-67 months of age (M = 41.76 months, SD = 11.92; 68% boys, 32% girls) were previously used to predict children's communicative participation skill development in 5 levels of function. Demographic and intervention-based variables were added to the models to identify new predictors of growth. Results: Three demographic and 3 intervention-based variables were statistically significant predictors of children's communicative participation outcomes. Clinically significant predictors included participation in an early learning environment, receipt of speech-language interventions, and the amount of time spent in intervention. These variables impacted predicted outcomes differently, depending on a child's level of communicative function. Conclusions: This population-based study of preschoolers with speech and language impairments identified predictors of growth in communicative participation skills-an outcome important and meaningful to families but not often explored. A broad picture emerged of factors that may influence the development of communicative participation skills and may be used to predict outcomes for preschoolers. Given the large sample size, these robust findings may be used to predict outcomes outside the Preschool Speech and Language Program as well. Supplemental Material: https://doi.org/10.23641/asha.6024422.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".