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Record W2030278168 · doi:10.1542/peds.2009-0690

Associations Between Secondhand Smoke Exposure and Sleep Patterns in Children

2010· article· en· W2030278168 on OpenAlexaff
Kimberly Yolton, Yingying Xu, Jane Khoury, Paul Succop, Bruce P. Lanphear, Dean W. Beebe, Judith Owens

Bibliographic record

VenuePEDIATRICS · 2010
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsBC Children's Hospital
FundersNational Institute of Environmental Health SciencesNational Heart, Lung, and Blood Institute
KeywordsMedicineAsthmaCotinineSecondhand smokeSleep (system call)Marital statusTobacco smokeDepression (economics)Environmental healthPediatricsPhysical therapyNicotinePsychiatryInternal medicinePopulation

Abstract

fetched live from OpenAlex

OBJECTIVES: The objective of this study was to investigate the relationship between exposure to secondhand smoke (SHS) and child sleep patterns among a group of children with asthma who were exposed regularly to tobacco smoke at home. METHODS: We studied 219 children who were enrolled in an asthma intervention trial and were exposed regularly to SHS. Serum cotinine levels were used to measure exposure to tobacco smoke, and sleep patterns were assessed through parent reports using the Children's Sleep Habits Questionnaire. Covariates in adjusted analyses included gender, age, race, maternal marital status, education, and income, prenatal tobacco exposure, maternal depression, Home Observation for Measurement of the Environment total score, household density, asthma severity, and use of asthma medications. RESULTS: Exposure to SHS was associated with sleep problems, including longer sleep-onset delay (P = .004), sleep-disordered breathing (P = .02), parasomnias (P = .002), daytime sleepiness (P = .022), and overall sleep disturbance (P = .0002). CONCLUSIONS: We conclude that exposure to SHS is associated with increased sleep problems among children with asthma.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.007
Threshold uncertainty score0.485

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.000

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 head0.010
GPT teacher head0.262
Teacher spread0.253 · 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 teacher head, 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

Citations97
Published2010
Admission routes1
Has abstractyes

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