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Record W2162795493 · doi:10.1093/jpepsy/jsm106

Acute Impact of Immediate Release Methylphenidate Administered Three Times a Day on Sleep in Children with Attention-Deficit/Hyperactivity Disorder

2007· article· en· W2162795493 on OpenAlexafffund
Penny Corkum, Rhona Panton, Sarah Ironside, Margaret Macpherson, Thomas L. Williams

Bibliographic record

VenueJournal of Pediatric Psychology · 2007
Typearticle
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsMount Saint Vincent UniversityDalhousie University
FundersIWK Health CentreDalhousie University
KeywordsActigraphyMethylphenidateStimulantAttention deficit hyperactivity disorderSleep (system call)Sleep diarySleep onset latencyRandomized controlled trialSleep onsetPsychiatryMedicineEl NiñoPsychologyPediatricsPhysical therapyInsomniaInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the impact of immediate release Ritalin, given three times a day, on sleep quality and quantity in medication-naïve, newly diagnosed children with attention-deficit/hyperactivity disorder (ADHD). METHODS: Children (aged 6-12) rigorously diagnosed with ADHD (n = 21) underwent multiple measurement assessments (i.e., actigraphy, sleep diary, and questionnaires) during a 1-week baseline and then during a 3-week blinded randomized medication trial. RESULTS: Although the medication was effective in reducing ADHD symptoms, analyses of actigraphy and sleep diary data found statistically and clinically significant changes in the children's total sleep time and sleep onset latency in the medication compared to the no medication conditions. No effects on sleep were found based on the sleep questionnaire. CONCLUSIONS: Physicians and parents are encouraged to closely monitor children's sleep when treating ADHD with stimulant medication.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.362
Teacher spread0.339 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations98
Published2007
Admission routes2
Has abstractyes

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Same venueJournal of Pediatric PsychologySame topicAttention Deficit Hyperactivity DisorderFrench-language works237,207