Guidelines and algorithms for the use of methylphenidate in children with Attention-Deficit/Hyperactivity Disorder
Bibliographic record
Abstract
OBJECTIVE: To review published algorithms for guiding the use of methylphenidate (MPH) in the treatment of Attention-Deficit/Hyperactivity Disorder (ADHD) in children and adolescents. METHODS: A consensus roundtable of 12 experts was convened to review the evidence for the safety and efficacy of MPH in the treatment of ADHD, as well as the published algorithms and practice guidelines for using MPH. The experts reviewed the algorithms for practicality and acceptability by clinicians. RESULTS: Algorithms that included MPH commonly selected it as the initial medication to be employed in the treatment of children with ADHD. Factors involved included its high efficacy, good safety record, and the ubiquitous nature of its appearance in the ADHD treatment literature. CONCLUSIONS: MPH should be considered as the first medication to be used in a treatment algorithm for children and adolescents with ADHD.
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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 | 0.016 | 0.049 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.007 | 0.001 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".