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Record W2100407338 · doi:10.1155/2013/137048

Long-Term Effectiveness of Parent Education Using the “Baby Oral Health” Model on the Improvement of Oral Health of Young Children

2013· article· en· W2100407338 on OpenAlexaff
Gajanan V. Kulkarni

Bibliographic record

VenueInternational Journal of Dentistry · 2013
Typearticle
Languageen
FieldDentistry
TopicDental Health and Care Utilization
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsAlgorithmIncidence (geometry)MedicineMachine learningOral healthArtificial intelligenceComputer scienceDentistryMathematicsGeometry

Abstract

fetched live from OpenAlex

Purpose. To determine the long-term effectiveness of comprehensive education given to parents and caregivers with respect to the incidence of preventable oral diseases, utilization of dental services, and retention of knowledge related to oral health. Methods. Group presentations on oral health were conducted for caregivers of infants (n = 161) using an interactive audio-visual aid. Followup occurred at 18 months. A comparison group (n = 181) was enrolled from the same community groups. Chi-square and Fisher's exact tests were used to analyze findings. Results. There was a difference in caries incidence, knowledge levels of caregivers, and utilization of dental services (P < 0.05) when comparing the SGB to the SGFU. Conclusions. One-time exposure to parent education using a comprehensive interactive audio-visual aid has an effect on reducing caries incidence and increasing dental utilization. While most knowledge is retained by parents, there is some attrition in the information retained over an 18-month time period. This emphasizes the importance of repeated reinforcement of the same concepts over a shorter time span.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.037
GPT teacher head0.389
Teacher spread0.352 · 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 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

Citations7
Published2013
Admission routes1
Has abstractyes

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