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Perceived sleep quality among edentulous elders

2010· article· en· W1703844938 on OpenAlexaff
Elham Emami, Gilles Lavigne, Pierre de Grandmont, Pierre Rompré, Jocelyne S. Feine

Bibliographic record

VenueGerodontology · 2010
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsUniversité de MontréalMcGill University
Fundersnot available
KeywordsMedicineSleep qualitySleep (system call)GerontologyPsychiatryInsomnia

Abstract

fetched live from OpenAlex

BACKGROUND: Anatomical changes associated with edentulism are thought to disturb seniors' sleep. OBJECTIVES: (1) To determine sleep quality and daytime sleepiness of edentulous elders. (2) To examine the association between oral health-related quality of life and sleep quality. METHODS: Data were collected at a 1-year follow-up from 173 healthy edentulous elders who had participated in a randomised controlled trial and randomly received two types of mandibular prosthesis. Subjective sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI, range 0-21), with higher scores indicating poorer sleep quality. The Epworth Sleepiness Scale (ESS) was used to measure the level of perceived daytime sleepiness, and scores ≥10 indicated sleepiness. RESULTS: The mean global PSQI and ESS scores were 4.7 ± 3.5 and 5.3 ± 3.9. There were no differences in sleep quality or sleepiness between those who wore their dentures at night and those who did not. Elders with frequent denture problems were sleepier during the day than those with fewer problems (p = 0.0034). General health (p = 0.02) and oral health-related quality of life (p = 0.001) are significant predictors of sleep quality. CONCLUSION: Healthy edentulous elders, independent of nocturnal wearing of their prosthesis, are good sleepers. Maintaining high oral health quality of life could contribute to better sleep.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.206
Threshold uncertainty score0.999

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.002

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 head0.018
GPT teacher head0.320
Teacher spread0.302 · 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; both teacher heads agree on what is shown here.

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

Citations26
Published2010
Admission routes1
Has abstractyes

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