Mother-Child Communication: The Influence of ADHD Symptomatology and Executive Functioning on Paralinguistic Style
Bibliographic record
Abstract
Paralinguistic style, involving features of speech such as pitch and volume, is an important aspect of one's communicative competence. However, little is known about the behavioral traits and cognitive skills that relate to these aspects of speech. This study examined the extent to which ADHD traits and executive functioning (EF) related to the paralinguistic styles of 8- to 12-year-old children and their mothers. Data was collected via parent report (ADHD traits), independent laboratory tasks of EF (working memory, inhibitory control, and cognitive flexibility), and an interactive problem-solving task (completed by mothers and children jointly) which was coded for paralinguistic speech elements (i.e., pitch level/variability; volume level/variability). Dyadic data analyses revealed that elevated ADHD traits in children were associated with a more exaggerated paralinguistic style (i.e., elevated and more variable pitch/volume) for both mothers and children. Mothers' paralinguistic style was additionally predicted by an interaction of mothers' and children's ADHD traits, such that mothers with elevated ADHD traits showed exaggerated paralinguistic styles particularly when their children also had elevated ADHD traits. Highlighting a cognitive mechanism, children with weaker inhibitory control showed more exaggerated paralinguistic styles.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".