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Record W2138681842 · doi:10.1093/jpepsy/jsp097

Concurrent Associations among Sleep Problems, Indicators of Inadequate Sleep, Psychopathology, and Shared Risk Factors in a Population-based Sample of Healthy Ontario Children

2009· article· en· W2138681842 on OpenAlexafffundabout
Janie Coulombe, Graham J. Reid, Michael H. Boyle, Yvonne Racine

Bibliographic record

VenueJournal of Pediatric Psychology · 2009
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsWestern University
FundersCanadian Institutes of Health Research
KeywordsPsychopathologySleep (system call)PopulationSample (material)PsychologyClinical psychologyDevelopmental psychologyPsychiatryMedicineEnvironmental health

Abstract

fetched live from OpenAlex

OBJECTIVES: Examine the contribution of sleep problems and indicators of inadequate sleep to psychopathology among children after accounting for shared risk and comorbid psychopathology. METHODS: Secondary analyses of cross-sectional data on 4- to 11-year-old (N = 1,550) children without chronic illness or developmental delay or disability. Parents provided information about sleep problems, indicators of inadequate sleep, symptoms of psychopathology, and risk factors for psychopathology. Teachers provided information about indicators of inadequate sleep and symptoms of psychopathology. RESULTS: Adjusting for risk factors and comorbid psychopathology, sleeping more than other children was related to parent-rated aggression. Nightmares and trouble sleeping were related to parent-rated anxious/depressed mood. Sleep problems were not related to attention problems. Being overtired was related to parent- and teacher-rated psychopathology. CONCLUSIONS: Relations among sleep problems, indicators of inadequate sleep, and psychopathology are complex; accounting for potential confounding variables and considering sleep variables separately may clarify these relations.

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)0.001
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 score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.016
GPT teacher head0.305
Teacher spread0.290 · 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

Citations40
Published2009
Admission routes3
Has abstractyes

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