Childhood and adolescent hyperactivity-inattention symptoms and academic achievement 8 years later: the GAZEL Youth study
Bibliographic record
Abstract
BACKGROUND: Children with attention deficit/hyperactivity disorder (ADHD) are at risk of negative academic outcomes. However, relatively few studies in this area have been based on long-term longitudinal designs and community-based settings. This study examined the link between childhood hyperactivity-inattention symptoms (HI-s) and subsequent academic achievement in a community setting, controlling for other behavioural symptoms, socio-economic status (SES) and environmental factors at baseline. METHOD: The sample consisted of 1264 subjects (aged 12 to 26 years at follow-up) recruited from the longitudinal GAZEL Youth study. Psychopathology, environmental variables and academic outcomes were measured through self-reports. Multivariate modelling was performed to evaluate the effects of childhood HI-s and other risk factors on academic achievement 8 years later. RESULTS: HI-s independently predicted grade retention [adjusted odds ratio (OR) 3.58, 95% confidence interval (CI) 2.38-5.39], failure to graduate from secondary school (adjusted OR 2.41, 95% CI 1.43-4.05), obtaining a lower-level diploma (adjusted OR 3.00, 95% CI 1.84-4.89), and lower academic performance. These results remained significant even after accounting for school difficulties at baseline. Negative academic outcomes were also significantly associated with childhood symptoms of conduct disorder (CD), even after accounting for adjustment variables. CONCLUSIONS: This longitudinal survey replicates, in a general population-based setting, the finding of a link between HI-s and negative academic outcomes.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".