Early childhood impulsivity and parenting predict children’s development of externalizing psychopathology
Bibliographic record
Abstract
Abstract Parenting and child impulsivity are consistent predictors of children’s externalizing symptoms; however, the role of the range of parenting (i.e., variation in parenting across contexts), and its interactions with child impulsivity, are poorly understood. We examined whether characteristic parenting practices and parenting range predicted the course of externalizing symptoms in 409 children (Mage = 3.43 years at baseline, 208 girls) across ages 3, 5, 8, and 11. We assessed parent positive affectivity (PPA), hostility, and parenting structure at child age 3 using three behavioral tasks that varied in context, examining range by modeling a latent difference score for each parenting dimension. Greater PPA range, mean structure, and parenting structure range all predicted fewer symptoms at age 3 for children with higher impulsivity. Lower mean hostility predicted fewer symptoms at age 3 for children with lower impulsivity. Greater PPA, and smaller PPA range, predicted a decrease in symptoms for children higher in impulsivity. Lower hostility range predicted a decrease in symptoms for children with lower impulsivity but predicted maintaining symptoms for children with higher impulsivity. Results demonstrate the differential roles average parenting practices and parenting range play in the development of child externalizing psychopathology, especially in the context of child impulsivity.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".