[Risk factors in families of children with disorder attention deficit/hyperactivity: Quebec data].
Bibliographic record
Abstract
INTRODUCTION: This paper focuses on Attention-Deficit/Hyperactivity Disorder (ADHD) and links with other disorders in the child and his/her parents. Adversity factors are presented around the family life and their impact on ADHD. Families who have a child with ADHD are compared to families who do not. METHOD: The parents in 82 families filled in the QFR-ADHD questionnaire: 24 children without ADHD (control group) and 58 children with ADHD (ADHD group). The children were between 5 and 21 years of age (average age: 10 years) with an average education of 1 to 14 years (average: 4th year of elementary school). The subjects were distributed as follows: 9 boys and 15 girls (control group), and 48 boys and 10 girls (TDA/H group). RESULTS: Oppositional disorder (OD), conduct disorders (CD) and learning disabilities (LD) were significantly more frequent in the ADHD group than in the control group. We found that the mothers of children with ADHD take more selective serotonin reuptake inhibitors than the mothers of children in the control group. This implies that the former experience depressive symptoms. Fathers of children with ADHD had more learning disabilities than the fathers in the control group. CONCLUSION: This research is in line with work on the etiology of ADHD. Investigation of the causes for ADHD is complex, as the disorder has both physical and psychological aspects.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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".