Community service‐based preventive dental education for elementary school‐aged children
Bibliographic record
Abstract
OBJECTIVES: The effectiveness of one-to-one preventive dental education provided by dental undergraduate students for improving elementary school-aged children's oral self-care skills, diet-related knowledge, and diet behavior was tested. METHODS: The sample consisted of 106 children between the ages of 5 and 12 years who attended the same school. Oral self-care skills were assessed by undergraduate dental students using a tooth-brushing assessment form, and diet knowledge and behaviors by means of a questionnaire. The effectiveness of education (two one-to-one sessions) was evaluated by measuring the post-educational changes in the children's oral self-care skills, diet knowledge, and behavior. RESULTS: There were significant improvements in the means (sd) of tooth-brushing skill scores (range: 0-18) from 6.2 (4.0) at the baseline to 8.4 (4.1) at the first and to 10.3 (3.0) at the second follow-up. Total tooth-brushing time (in seconds) significantly increased from 76.0 (59.1) at the baseline to 110.7 (74.3) at the first follow-up then decreased to 102.6 (73.1) at the second follow-up. The means (sd) of diet knowledge scores (range: 0-30) improved significantly from 18.5 (5.6) at the baseline to 23.0 (7.3) at the first and to 24.5 (4.0) at the second follow-ups. The means (sd) of weekly sugar intake scores (range: 0-18) significantly decreased from 4.9 (2.1) at the baseline to 3.1 (2.0) at the first follow-up and remained unchanged until the second follow-up. CONCLUSIONS: One-to-one dental education improved children's oral self-care skills, diet-related knowledge, and diet behavior. The post-educational improvements were maintained for 6 months in older children but not in the younger children.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".