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Record W2472896897

Oral pain and its covariates: findings of a Canadian population-based study.

2013· article· en· W2472896897 on OpenAlexaffabout
Vahid Ravaghi, Carlos Quiñonez, Paul Allison

Bibliographic record

VenuePubMed · 2013
Typearticle
Languageen
FieldDentistry
TopicDental Anxiety and Anesthesia Techniques
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineToothacheOral healthMultivariate analysisBivariate analysisDental carePopulationEpidemiologyDemographyDentistryEnvironmental healthInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To describe the prevalence of oral pain in Canada and to identify its covariates. METHODS: Data were derived from the 2007-2009 Canadian Health Measures Survey. Data were analyzed for a total of 5284 respondents (2558 males, 2726 females) aged 6-79 years. The outcome variable was self-reported pain in the mouth in the past 12 months. Bivariate and multivariate analyses were used to investigate the relationship between oral pain and 4 sets of covariates: socio-demographic factors, dental service utilization, oral health behaviours and clinical oral health. RESULTS: Oral pain in the past 12 months was reported by 11.7% of respondents. Oral pain was slightly, but not significantly, more prevalent among females than males (13.6% vs. 10.0%). The lowest and highest prevalence of oral pain were reported by children and young adults, respectively. Multivariate analyses suggested that oral pain was significantly more prevalent among adolescents and adults, those in the lowest income groups, those who avoided a dental professional because of the cost and those with untreated decayed teeth. CONCLUSION: Canadians with financial barriers to accessing dental care and those with untreated dental decay were at risk of having dental pain. These findings have important implications for the provision of dental care in Canada.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score0.935

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.223
Teacher spread0.201 · 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

Citations25
Published2013
Admission routes2
Has abstractyes

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