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Dental Discomfort Questionnaire: its use with children with a learning disability

2008· article· en· W2144881435 on OpenAlexaff
Judith Versloot, Emma Hall‐Scullin, J. S. J. Veerkamp, Ruth Freeman

Bibliographic record

VenueSpecial Care in Dentistry · 2008
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsToothacheMedicineDentistryPopulationEnvironmental health

Abstract

fetched live from OpenAlex

This study investigated whether the behaviors from the Dental Discomfort Questionnaire (DDQ) could help identify toothaches in children with a learning disability, who have a limited capacity to self-report. The objectives were to examine whether the behaviors from the DDQ occur more often in children with a learning disability who have caries and a toothache than in children who do not have caries and a toothache; and secondly, to examine whether two additional items increase the specificity and sensitivity of the DDQ to recognize a toothache, in this particular population of children with a learning disability. The DDQ was completed by a convenience sample of 58 parents on behalf of their children: 31% girls, aged between 6 and 13 years (mean = 7.5, SD = 2.7). Of the total group, 26% (n = 15) suffered from a toothache and 43% (n = 25) had carious teeth. Children with caries and a toothache had a significantly higher mean DDQ score and displayed more toothache-related behaviors (e.g., problems with chewing, problems with brushing teeth) than children without caries or toothache. The DDQ seems to be a functional and easy-to-use instrument to alert parents to the presence of a toothache in this specific group of children with a learning disability.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.016
GPT teacher head0.284
Teacher spread0.268 · 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

Citations19
Published2008
Admission routes1
Has abstractyes

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