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Identifying Children with Dental Care Needs: Evaluation of a Targeted School‐based Dental Screening Program

2004· article· en· W2163805058 on OpenAlexaffabout
David Locker, Caroline Frosina, Heather Murray, David Wiebe, Peter N. Wiebe

Bibliographic record

VenueJournal of Public Health Dentistry · 2004
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsUniversity of TorontoToronto Public Health
Fundersnot available
KeywordsMedicineDental careDentistryFamily medicineMedical education

Abstract

fetched live from OpenAlex

OBJECTIVES: It has been suggested that changes in the distribution of dental caries mean that targeting high-risk groups can maximize the cost effectiveness of dental health programs. This study aimed to assess the effectiveness of a targeted school-based dental screening program in terms of the proportion of children with dental care needs it identified. METHODS: The target population was all children in junior and senior kindergarten and grades 2, 4, 6, and 8 who attended schools in four Ontario communities. The study was conducted in a random sample of 38 schools stratified according to caries risk. Universal screening was implemented in these schools. The parents of all children identified as having dental care needs were sent a short questionnaire to document the sociodemographic and family characteristics of these children. Children with needs were divided into two groups: those who would and who would not have been identified had the targeted program been implemented. The characteristics of the two groups were compared. RESULTS: Overall, 21.0 percent of the target population were identified as needing dental care, with 7.4 percent needing urgent care. The targeted program would have identified 43.5 percent of those with dental care needs and 58.0 percent of those with urgent needs. There were substantial differences across the four communities in the proportions identified by the targeted program. Identification rates were lowest when the difference in prevalence of need between the high- and low-risk groups was small and where the low-risk group was large in relation to the high-risk group. The targeted program was more effective at identifying children from disadvantaged backgrounds. Of those with needs who lived in households receiving government income support, 59.0 percent of those with needs and 80.1 percent of those with urgent needs would be identified. CONCLUSIONS: The targeted program was most effective at identifying children with dental care needs from disadvantaged backgrounds. However, any improvements in cost effectiveness achieved by targeting must be balanced against inequities in access to public health care resources.

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)0.003
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 score0.105
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.073
GPT teacher head0.390
Teacher spread0.317 · 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

Citations41
Published2004
Admission routes2
Has abstractyes

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