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Record W2762813457 · doi:10.1093/pch/19.6.e35-124

126: Sleep Efficiency is Associated with and Report Card Marks in Typically Developing School-Age Children

2014· article· en· W2762813457 on OpenAlexaff
Reut Gruber, G Somerville, Paul Enros, Myra Kestler, Elizabeth Gillies-Poitras

Bibliographic record

VenuePaediatrics & Child Health · 2014
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsMcGill University
Fundersnot available
KeywordsSleep (system call)ActigraphyReport cardAcademic achievementPsychologyAssociation (psychology)Psychological interventionMedicineDevelopmental psychologyClinical psychologyPsychiatryInsomnia

Abstract

fetched live from OpenAlex

Academic success plays an important role in improving future lifetime opportunities and accumulating evidence indicates that sleep has beneficial effects on academic success. Although a myriad of factors have been identified as being relevant to academic achievement, the role played by sleep in this process has been largely ignored. A considerable proportion of elementary school-aged children sleep for less than the recommended hours per night and 25% to 40% of youth are affected by asleep disorder during infancy, childhood and/or or adolescence. This is a major concern given that restricted sleep can negatively impact the academic performance of children. Measures used to assess school achievement include report cards marks. Previous studies examining the associations between sleep and marks on report cards used subjective measures of sleep. Thus, we do not know what aspects of sleep are related to performance in specific academic subjects. It is also not known which aspects of sleep are most relevant to academic performance. Determining which aspects of academic performance are specifically affected by poor sleep is important because this can inform the development of sleep interventions to improve these domains To examine the association between objectively measured aspects of sleep (sleep duration and sleep efficiency) and report card marks in healthy school-age children Nighttime sleep was monitored by actigraphy, which uses a wristwatch-like device (AW-64 series, Mini-Mitter) to evaluate sleep through the measurement of ambulatory movement, and parents provided their child's most recent report card. The study sample consisted of 72 participants between seven and 11 years of age (mean [± SD] 8.85±1.6 years). The amount of sleep that children obtained gradually decreased with age. Children in Cycle 1 obtained an average of 608.21±24.65 min, while those in Cycle 2 received 565.7±26.15 min and those in Cycle 3 received 547.43±34.5 min (F[2, 69]=24.65; P<0.0001). Using multiple linear regression analyses it was found that higher sleep efficiency showed a statistically significant association with better marks in Math, English Language, and French as a Second Language above and beyond the contributions of age, gender, and socioeconomic status. Our findings suggest that higher sleep efficiency in healthy school-age children is positively associated with better marks in Math, English Language and French as a Second Language.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.052

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.008
GPT teacher head0.263
Teacher spread0.256 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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