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Record W2117621614 · doi:10.1007/s00787-012-0286-5

Amfetamine and methylphenidate medications for attention-deficit/hyperactivity disorder: complementary treatment options

2012· review· en· W2117621614 on OpenAlexaff
Paul Hodgkins, Monica Shaw, David Coghill, Lily Hechtman

Bibliographic record

VenueEuropean Child & Adolescent Psychiatry · 2012
Typereview
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsMcGill UniversityMcGill University Health CentreMontreal Children's Hospital
Fundersnot available
KeywordsStimulantMethylphenidateAttention deficit hyperactivity disorderAtomoxetinePsychiatryDosingPsychologyDrugMedicineClinical psychologyPharmacology

Abstract

fetched live from OpenAlex

Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders among school-aged children. It is highly symptomatic and associated with significant impairment. This review examines the role of stimulant medications in the treatment of children and adolescents with ADHD. Published clinical studies that compared methylphenidate- and amfetamine-based stimulants in children and adolescents with ADHD support the therapeutic utility of stimulant treatments, and suggest robust efficacy and acceptable safety outcomes in groups treated with either stimulant. Evidence-based guidelines agree that each patient with ADHD is unique and individual treatment strategies that incorporate both drug and non-drug treatment options should be sought. In seeking to optimize individual response and outcomes to stimulant therapy, important considerations include the selection of stimulant class, the choice of long- or short-acting stimulant formulations, addressing effectively any emergent adverse effects and strategies aimed at enhancing adherence to dosing regimen and persistence on therapy.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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.

Opus teacher head0.064
GPT teacher head0.358
Teacher spread0.294 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations146
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Child & Adolescent PsychiatrySame topicAttention Deficit Hyperactivity DisorderFrench-language works237,207