Reaching <scp>ADHD</scp> Treatment Targets?
Bibliographic record
Abstract
In a recent epidemiological study, Grøntved et al. present important results on the temporal changes of the rates in prevalence and incidence of ADHD diagnosis and use of ADHD medication in Denmark over the past two decades [1]. The authors have applied stringent, robust, and sound methods in analyzing individual-level data available from the Danish nationwide registers. Their main findings include consistent increases in the prevalence and incidence of diagnosis of ADHD and corresponding increases in pharmacological treatment across sex and age groups from 2000 to 2022. The most notable increase in recent years is observed in young adult women. They found that 3.03% of the total population living in Denmark was given a clinical diagnosis of ADHD or had received treatment with ADHD medication in 2022. Among children and adolescents aged 6–18 years, it was 4.0%; in adults aged 18–27 years, it was 7.1%; in adults aged 27–35 years, it was 6.1%; and in adults aged 35–50 years, it was 3.5%, all as observed in 2022
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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 | 0.007 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.017 | 0.007 |
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".