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Record W2801492700 · doi:10.1177/0829573518770593

The Impact of Sleep Restriction on Daytime Functioning in School-Age Children With and Without ADHD: A Narrative Review of the Literature

2018· review· en· W2801492700 on OpenAlexaff
Fiona Davidson, Benjamin Rusak, Christine T. Chambers, Penny Corkum

Bibliographic record

VenueCanadian Journal of School Psychology · 2018
Typereview
Languageen
FieldMedicine
TopicAttention Deficit Hyperactivity Disorder
Canadian institutionsDalhousie University
Fundersnot available
KeywordsPsychologySleep (system call)Sleep restrictionAttention deficit hyperactivity disorderClinical psychologyDevelopmental psychologyDaytimeNarrative reviewCognitionNarrativeSleep disorderPsychiatrySleep deprivationPsychotherapist

Abstract

fetched live from OpenAlex

The purpose of this narrative review was to synthesize the existing literature on the impact of sleep on daytime functioning in both typically developing (TD) children and children with attention-deficit/hyperactivity disorder (ADHD). Correlational studies in children suggest that insufficient sleep and impaired daytime functioning are significantly associated; however, this does not address the causal relationships between sleep and daytime functioning. The review results indicated that there is limited experimental sleep manipulation research in children. In the eight studies that employed experimental methods to examine sleep restriction, the consequences of insufficient sleep were greatest for attention and inconsistent for other domains, such as cognition and emotion regulation. Despite the significant co-occurrence of ADHD and sleep problems, the experimental sleep research focused on the daytime impact of shorter sleep in children with ADHD is extremely limited and as such more research is needed.

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)0.001
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.004
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.049
GPT teacher head0.396
Teacher spread0.347 · 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 designSystematic review
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

Citations16
Published2018
Admission routes1
Has abstractyes

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Same venueCanadian Journal of School PsychologySame topicAttention Deficit Hyperactivity DisorderFrench-language works237,207