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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 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)0.002
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 science0.0000.000
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 head0.018
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; 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

Citations26
Published2010
Admission routes1
Has abstractyes

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