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Record W4390078226 · doi:10.1017/s1355617723007464

75 Early Childhood Sleep Quantity, but not Parent-Reported Sleep Problems, Predict Impulse Control in Children at Age 8 years

2023· article· en· W4390078226 on OpenAlexaff
Sarah E. Nigro, Dean W. Beebe, James Peugh, Kimberly Yolton, Aimin Chen, Bruce P. Lanphear

Bibliographic record

VenueJournal of the International Neuropsychological Society · 2023
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsSleep (system call)PsychologySleep deprivationMedicineClinical psychologyCognitionPsychiatry

Abstract

fetched live from OpenAlex

Objective: Conduct secondary analyses on longitudinal data to determine if caregiver-reported sleep quantity and sleep problems across early childhood (ages 2 - 5 years) predict their child’s attention and executive functioning at age 8 years. Participants and Methods: This study utilized data from the Health Outcomes and Measures of the Environment (HOME) Study. The HOME Study recruited pregnant women from 20032006 within a nine-county area surrounding Cincinnati, OH. Caregivers reported on their child’s sleep patterns when children were roughly 2, 2.5, 3, 4, and 5 years of age. Our analysis included 410 participants from the HOME Study where caregivers reported sleep measures on at least 1 occasion or their child completed an assessment of attention and executive functioning at age 8. At each time point, caregiver report on an adapted version of the Child Sleep Habits Questionnaire (CSHQ) was used to determine: (1) total sleep time (TST; “your child’s usual amount of sleep each day, combining nighttime sleep and naps”) and (2) overall sleep problems (23 items related to difficulties with sleep onset, sleep maintenance, and nocturnal events). Our outcome variables, collected at age 8, included caregiver-report forms and measures of attention and executive functioning. Caregiver report measures included normed scores on the Behavior Rating Inventory of Executive Function, from which we focused on the Behavior Regulation Index (BRIEF BRI) and Metacognition Index (BRIEF MI). Performance based measures included T-scores for Omission and Commission errors on the Conner’s Continuous Performance Test, Second Edition (CPT-2) and Standard Scores on the WISC-IV; Working Memory Index (WMI). We used longitudinal growth curve models of early childhood sleep patterns to predict attention and executive functioning at age 8. Predictive analyses were run with and without key covariates: annual household income, child sex and race. To account for general intellectual functioning, we also included covariates children’s WISC-IV Verbal Comprehension and Perceptual Reasoning Indexes. Results: Children in our sample were evenly divided by sex; 60% were White. Sleep problems did not show linear or quadratic change over time, so an intercept-only model was used. Sleep problems did not predict any of our outcome measures at age 8 in unadjusted or covariate-adjusted models. As expected, sleep duration was shorter as children matured, so predictive models examined both intercept and slope. Slope was negatively associated with CPT-2 Commissions (unadjusted p=.047; adjusted p=.013); children who showed the least decline in sleep over time had fewer impulsive errors at age 8. The sleep duration intercept was negatively associated with BRIEF BRI (unadjusted p=.002; adjusted p=.043); children who slept less across early childhood had worse parent-reported behavioral regulation at age 8. Neither sleep duration slope nor intercept significantly predicted any other outcomes at age 8 in unadjusted or covariate-adjusted analyses. Conclusions: Total sleep time across early childhood predicts behavior regulation difficulties in later childhood. Inadequate sleep during early childhood may be a marker for or contribute to poor development of a child’s self-regulatory skills.

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)0.003
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 score0.015
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.020
GPT teacher head0.284
Teacher spread0.264 · 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
Published2023
Admission routes1
Has abstractyes

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