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Record W2191447780 · doi:10.1177/2158244015607583

Does the Association Between Self-Reported Restless Sleep and Objective Sleep Efficiency Differ in Obese and Non-Obese Women? Findings From the Kingston Senior Women Study

2015· article· en· W2191447780 on OpenAlexaff
Alexandra Wilson, Kyra E. Pyke, Emma Bassett, Spencer Moore

Bibliographic record

VenueSAGE Open · 2015
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsQueen's University
Fundersnot available
KeywordsActigraphyMedicineObesityOdds ratioSleep (system call)Confidence intervalAssociation (psychology)InsomniaPhysical therapyGerontologyDemographyPsychologyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Our study assessed the validity of self-reported restless sleep (SRRS) in measuring sleep efficiency and the degree to which these measures differed depending on obesity status in older women. Data were from 100 participants enrolled in the Kingston Senior Women Study. Participants recorded SRRS for 7 consecutive nights. Sleep efficiency measures were recorded nightly through actigraphy. Repeated-measures multilevel logistic analysis was used. Mean sleep efficiency was 87% ( SE = 1.09), SRRS occurred in 37% ( SE = 3) of nights. Obesity status moderated the association between sleep efficiency and SRRS (odds ratio [OR] = 1.08; 95% confidence interval [CI] = [1.02, 1.14]) when controlling for age, medication intake, and depressive symptoms. Higher sleep efficiency reduced the odds of SRRS in non-obese women, but no association was shown in obese women. The lack of correspondence between objective and subjective measures in obese women suggests that SRRS may not be as indicative of sleep quality in obese compared with non-obese older women.

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)0.002
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 score0.140
Threshold uncertainty score0.619

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0010.000
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 head0.014
GPT teacher head0.290
Teacher spread0.276 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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