Associations Between Peer Functioning and Verbal Ability Among Children With and Without Attention-Deficit/Hyperactivity Disorder
Bibliographic record
Abstract
We examined the extent to which children’s skilled understanding and production of appropriate language (verbal ability) may relate to their peer functioning. Participants included two independent samples of children with and without Attention-Deficit/Hyperactivity Disorder (ADHD; Study 1, N = 124; Study 2, N = 137) who were administered a standardized intelligence test to generate verbal ability scores. Teacher ratings on the Cooperation and Assertion subscales of the Social Skills Rating System (SSRS), teacher estimates of peer acceptance, parent ratings of conflict and disengagement on playdates, and peer sociometric ratings of liking were obtained. In both Study 1 and Study 2, after statistical control of ADHD diagnostic status, disruptive behavior comorbidities, and gender, higher verbal ability was associated with better peer functioning on the teacher-reported SSRS subscales and parent ratings of conflict and disengagement on playdates. In Study 2, interaction effects suggested that the positive association between verbal ability and good peer functioning existed for boys but not for girls. For children with ADHD (but not comparison children), better verbal ability was associated with higher teacher-reported peer acceptance but lower peer sociometric liking. Implications of these findings for conceptualization of peer problems, assessment, and intervention are discussed.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".