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Record W71528383 · doi:10.1177/070674370200601s11

Guidelines and algorithms for the use of methylphenidate in children with Attention-Deficit/Hyperactivity Disorder

2002· review· en· W71528383 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Attention Disorders · 2002
Typereview
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsCentre for Addiction and Mental Health
FundersNational Institute of Mental HealthNational Institutes of HealthNational Institute for Health and Care Research
KeywordsMethylphenidateAttention deficit hyperactivity disorderPsychiatryPsychologyClinical psychologyAttention deficitAlgorithmComputer science

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.866
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.141
GPT teacher head0.387
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it