Facteurs de risque environnementaux précoces et trajectoires développementales d’irritabilité et du trouble du déficit de l’attention avec ou sans hyperactivité
Bibliographic record
Abstract
Introduction: irritability is frequently related with attention deficit hyperactivity disorder (ADHD). Their combination predicts more severe symptoms and greater impairment in children. Therefore, it seems important to study their developmental variations jointly and to highlight specific risk factors which can be modified through preventive public health campaigns. The aim of this study is to explore the association between early childhood environmental risk factors and irritability and ADHD developmental trajectories from a population-based cohort. Methods: data was collected from the Quebec Longitudinal Study of Child Development that followed 1588 children from 5 months to 12 years of age. Social factors, parenting behaviors and parental psychopathology were considered as potential risk factors. The child’s behavior was rated by its schoolteacher yearly between the age of 6 and 12 years old. Developmental trajectories of ADHD and irritability were estimated through multitrajectory modeling. Multinomial regression analyses were carried out to estimate association between risk factors and developmental trajectories. Results: four trajectories were estimated: one low ADHD/low irritability which was considered as physiological and three pathological trajectories (moderate irritability, high ADHD, and high irritability/high ADHD). Compared to the reference group, the combined profile was associated with male gender (adjusted Odds Ratio (aOR) = 7.01, 95% Confidence Interval (95%CI)[4.67-10.54]), non-intact families (aOR = 2.11, 95%CI [1.38-3.22]), coercive parenting (aOR=1.57, 95%CI [1.02-2.42]), consistent parenting (aOR = 0.83, 95%CI [0.72-0.95]), parental impact (aOR = 0.90, 95%CI [0.80-1.00]) and maternal history of antisocial behavior in adolescence (aOR = 1.44, 95%CI [1.05-1.96]). Conclusion: public health campaigns targeting parenting behaviors should be considered to prevent severe child psychopathology.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".