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Record W2114524852 · doi:10.1093/jpepsy/jsq028

Sleep Problems, Tiredness, and Psychological Symptoms among Healthy Adolescents

2010· article· en· W2114524852 on OpenAlexafffund
Janie Coulombe, Graham J. Reid, Michael H. Boyle, Yvonne Racine

Bibliographic record

VenueJournal of Pediatric Psychology · 2010
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsMcMaster UniversityWestern University
FundersSocial Sciences and Humanities Research Council of CanadaCanadian Institutes of Health Research
KeywordsAnxietyPsychopathologyAggressionPsychologyClinical psychologyDepression (economics)PsychiatrySleep (system call)Sleep disorderInsomnia

Abstract

fetched live from OpenAlex

OBJECTIVE: To examine the contribution of adolescents' sleep problems and tiredness to psychological symptoms after accounting for shared risk and psychological co-morbidity. METHODS: Secondary analyses of cross-sectional data on 12-16-year-old (N = 980) adolescents without chronic illness, functional limitation, or developmental delay. Adolescents rated sleep problems, tiredness, and psychological symptoms. Parents provided information about risk factors, adolescent tiredness, and psychological symptoms. RESULTS: Prior to accounting for psychological co-morbidity, most sleep variables were significant correlates of adolescent-, but not parent-rated, psychological symptoms. After accounting for psychological co-morbidity: nightmares were associated with adolescent-rated anxiety/depression; sleeping more than others was associated with adolescent-rated aggression; trouble sleeping was associated with adolescent-rated attention problems, anxiety/depression, and withdrawal; and adolescent-rated tiredness was associated with adolescent-rated aggression and withdrawal. CONCLUSIONS: Studies examining sleep and psychopathology should control for psychological co-morbidity.

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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.330
Teacher spread0.310 · 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

Citations62
Published2010
Admission routes2
Has abstractyes

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