Examining the Associations Between Parent Concerns and School-Age Children's Language and Reading Abilities: A Comparison of Samples Recruited for In-School Versus Online Participation
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to examine the relationship between parent concerns about children's oral language, reading, and related skills and their children's performance on standardized assessments of language and reading, with a particular focus on whether those relationships differed between children recruited for in-school versus online participation. METHOD: = 84) recruited via advertisements completed assessments online. Parents completed a checklist of concerns. All children completed norm-referenced assessments of language and reading. RESULTS: The two recruitment strategies yielded samples that differed in racial diversity (higher in the in-school sample), caregiver education levels (higher in the online sample), and word reading test scores (higher in the online sample). Parents in both samples reported higher levels of concerns about literacy skills than oral language skills, and the correlation between parent concerns about literacy and children's word reading test scores was stronger than the correlation between parent concerns about oral language and children's language test scores. CONCLUSIONS: Researchers and clinicians should be aware of how recruitment strategies and assessment modalities (e.g., in-person vs. tele-assessment) may impact participation in studies and clinical service. A reliance on parent concerns about oral language to prompt a language evaluation may contribute to low rates of identification of children who meet criteria for DLD. Future research can consider parent concerns about literacy, attention, and executive functions as indicators of a need for language evaluation, especially considering the high comorbidity between language and other developmental disorders.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".