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Record W4386294133 · doi:10.2196/52233

Oral Health, Social and Emotional Well-Being, and Economic Costs: Protocol for the Second Australian National Child Oral Health Survey

2023· article· en· W4386294133 on OpenAlexvenueno aff
Lisa Jamieson, Liana Luzzi, Sergio Chrisopoulos, Rachel Roberts, Peter Arrow, Sanjeewa Kularatna, Murthy Mittinty, Dandara Haag, Pedro Henrique Ribeiro Santiago, Gloria Mejía

Bibliographic record

VenueJMIR Research Protocols · 2023
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilMedical Research Council
KeywordsMedicineSocioeconomic statusPopulationContext (archaeology)Environmental healthEpidemiologyFamily medicineGeography

Abstract

fetched live from OpenAlex

BACKGROUND: Given the significant investment of governments and families into the provision of child dental care services in Australia, continued population oral health surveillance through national oral health surveys is imperative. OBJECTIVE: The aims of this study are to conduct a second National Child Oral Health Survey (NCOHS-2) to (1) describe the prevalence, extent, and impact of oral diseases in contemporary Australian children; (2) evaluate changes in the prevalence and extent of oral diseases in the Australian child population and socioeconomic subgroups since the first National Child Oral Health Study (NCOHS-1) in 2012-2013; and (3) use economic modeling to evaluate the burden of child oral disease from the NCOHS-1 and NCOHS-2 and to estimate the cost-effectiveness of targeted programs for high-risk child groups. METHODS: The NCOHS-2 will closely mimic the NCOHS-1 in being a cross-sectional survey of a representative sample of Australian children aged 5-14 years. The survey will comprise oral epidemiological examinations and questionnaires to elucidate associations between dental disease in a range of outcomes, including social and emotional well-being. The information will be analyzed within the context of dental service organization and delivery at national and jurisdictional levels. Information from the NCOHS-1 and NCOHS-2 will be used to simulate oral disease and its economic burden using both health system and household costs of childhood oral health disease. RESULTS: Participant recruitment for the NCOHS-2 will commence in February 2024. The first results are expected to be submitted for publication 6 months after NCOHS-2 data collection has been completed. Thematic workshops with key partners and stakeholders will also occur at this time. CONCLUSIONS: Regular surveillance of child oral health at an Australian level facilitates timely policy and planning of each state and territory's dental public health sector. This is imperative to enable the most equitable distribution of scarce public monies, especially for socially disadvantaged children who bear the greatest dental disease burden. The last NCOHS was conducted in 2012-2014, meaning that these data need to be updated to better inform effective dental health policy and planning. The NCOHS-2 will enable more up-to-date estimates of dental disease prevalence and severity among Australian children, with cost-effective analysis being useful to determine the economic burden of poor child dental health on social and emotional well-being and other health indicators. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/52233.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.023
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.029
Threshold uncertainty score0.122

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0230.018
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.004
Science and technology studies0.0030.001
Scholarly communication0.0020.002
Open science0.0030.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0290.008

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 head0.329
GPT teacher head0.595
Teacher spread0.265 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

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

Citations7
Published2023
Admission routes1
Has abstractyes

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