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Record W6888628409 · doi:10.1922/cdh_2573brennan

Dental self-care and visiting behaviour in relation to social inequality in caries experience

2011· article· en· W6888628409 on OpenAlexaboutno aff

Bibliographic record

VenueAdelaide Research & Scholarship (AR&S) (University of Adelaide) · 2011
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsnot available
Fundersnot available
KeywordsOral healthMultivariate analysisQuarter (Canadian coin)Tooth brushingDental healthSocial classAssociation (psychology)Inequality

Abstract

fetched live from OpenAlex

Objectives: To investigate associations of dental behaviour with social inequality in oral health. Methods: A random sample of 45-54 year-olds from Adelaide, South Australia was surveyed by self-complete questionnaire in 2004-05 (n=879, response rate 43.8%). Oral examinations were performed by calibrated dentists on 709 persons (80.7% of participants). Results: The mean (SE) number of decayed teeth (D) was 0.4 (0.04), with 5.3 (0.2) missing teeth (M), 11.0 (0.2) filled teeth (F) and 16.6 (0.2) DMFT. The majority brushed their teeth 8 or more times per week (78.8%) and had made a dental visit within the last 12 months (63.7%). Nearly a quarter had a household income of under $30,000 (24.0%). Multivariate analysis showed a three-way interaction (p<0.05, GLM) between income and brushing and visiting for decayed teeth, showing that the relationship between decayed teeth and dental behaviour varied across levels of income. Among those who had not made a dental visit in the last 12 months, those who brushed their teeth 8 or more times per week in the low income group had D=0.7 (0.2) while those who brushed less often had D=2.2 (0.5) compared to D=0.3 (0.08) and D=0.3 (0.2) respectively in the high income group. Conclusion: Dental behaviour in terms of brushing and visiting was associated with social gradients in oral health for decayed teeth across income groups, with less favourable dental behaviour having a stronger negative association with oral health among lower income groups.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.002
Open science0.0000.001
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 head0.096
GPT teacher head0.378
Teacher spread0.282 · 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.

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

Citations17
Published2011
Admission routes1
Has abstractyes

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