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Dental care access among individuals with Down syndrome in France

2000· article· en· W2081418953 on OpenAlexaff
Paul Allison, Martine Hennèquin, Denise Faulks

Bibliographic record

VenueSpecial Care in Dentistry · 2000
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsMcGill University
Fundersnot available
KeywordsMedicineOral hygieneLogistic regressionDental careFamily medicineOddsReceiptOral healthOdds ratioDental healthCross-sectional studyDentistry

Abstract

fetched live from OpenAlex

The aim of this study was to compare levels of dental care utilization, receipt of dental services, and oral hygiene habits between a sample of individuals with Down syndrome (DS) and their siblings. Data were collected by means of a recently validated, French-language, questionnaire measured of oral health and its related problems for individuals with DS. A cross-sectional survey was undertaken of parents of children with DS attending a national meeting for families and carers of individuals with DS in France. Older individuals with DS were significantly more likely to visit a dentist regularly than their older non-DS siblings, but the group with DS was significantly less likely to have received any dental treatment. The group with DS was significantly more likely to have difficulty finding both medical and dental services. Parents were nearly twice as likely to report problems finding dental services for their child with DS as they were medical services. In a multiple logistic regression analysis within the DS group, it was found that older age, regular speech therapy and ophthalmology consultations, and reports of no difficulty finding a dentist were independently associated with increased odds for regular dental consultations. Analysis of the findings suggests that the parents of children with DS in France frequently encounter problems of access to oral health care and that individuals with DS are less likely to receive dental services than are their non-DS siblings.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.009
GPT teacher head0.294
Teacher spread0.285 · 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

Citations74
Published2000
Admission routes1
Has abstractyes

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