Dental Home Visits for Caries Prevention Among Preschool Children: Protocol for a Cost-Effectiveness Analysis on a Randomized Control Trial
Bibliographic record
Abstract
BACKGROUND: In 2012, nearly 4000 children in Malaysia were referred to hospital pediatric dental services due to dental caries. Recent research has reported the effectiveness of dental home visits in preventing caries development in young children. Dental home visits (DHVs) are described as an ongoing relationship between the dentist and their patients, providing all aspects of a preventive oral health care program in the presence of the parents at home. OBJECTIVE: The objective of this study is to evaluate the cost-effectiveness of dental home visits and oral health information, in the form of educational leaflets, in preventing new caries development in young children, compared to those receiving only educational leaflets over a period of two years. Cost-effectiveness analysis will be used to evaluate the cost-effectiveness of dental home visits. METHODS: This is a collaborative project with the Oral Health Division of the Ministry of Health Malaysia. The Oral Health Division will provide access to a subsample from the National Oral Health of Preschoolers Survey which was carried out in 2015. The population of interest is children aged 5 and 6 years from kindergartens in the Selangor state of Malaysia. The study adopted a societal perspective for cost-effectiveness analysis and all types of resources that are of value to society will be included in analyzing the costs; such as cost to the patient, cost to the provider or institution, and indirect costs because of loss of productivity. RESULTS: The trial has been approved by the International Medical University Malaysia's Joint Research and Ethics Committee (Project ID: IMU R157-2014 [File III - 2016]). This trial is currently recruiting participants. CONCLUSIONS: The number of young children in Malaysia who have been referred to the hospital children's dentistry service for severe caries is disturbing. The cost of dental treatment in young children is high due to the severity of the caries which require an aggressive treatment, and the need for general anesthesia or sedation. This study will provide information on the cost and effectiveness of DHVs in caries prevention of young children in Malaysia. REGISTERED REPORT IDENTIFIER: RR1-10.2196/10053.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.035 | 0.041 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.010 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.009 |
| Insufficient payload (model declined to judge) | 0.089 | 0.010 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".