Dentist's views on a province-wide campaign promoting early dental visits for young children.
Bibliographic record
Abstract
INTRODUCTION: The Canadian Dental Association recommends that children have their first visit to a dental professional no later than 12 months of age. In 2010, the Manitoba Dental Association launched the Free First Visit (FFV) program to increase access to early visits in the province. The purpose of the study reported here was to survey dentists about their views on the FFV program and to gain an understanding of their attitudes and practice patterns relating to the oral health of infants and toddlers and first dental visits. METHODS: A survey was mailed to registered general and pediatric dentists in Manitoba according to a modified Dillman methodology. Dentists were asked about their views on the FFV, their knowledge of early childhood oral health and the timing of first dental visits. Descriptive statistics, bivariate analyses and logistic regression analyses were performed. A p value of 0.05 or less was considered significant. RESULTS: The overall response rate was 63.2% (375 eligible responses out of 593 surveys mailed). The majority of respondents were men (255/373 [68.4%]), and most respondents were general dentists (355/372 [95.4%]). A total of 63.5% (231/364) felt that the FFV program improved access to care, 64.6% (223/345) believed that public awareness of young children's oral health has increased, and 76.2% (266/349) thought that the FFV initiative should continue past the planned end date of March 31, 2013. On average (± standard deviation), respondents thought that the first dental visit should occur at 18.1 ± 10.0 months, but in their practices, they actually recommended a slightly older age (18.9 ± 10.4 months). Compared with results from a previous survey, conducted in 2005, dentists who responded to this survey recommended that children have their first visit at a significantly younger age. A greater proportion of dentists reported seeing children 12-23 months of age in their practices than in the past (81.9% vs. 73.7%). CONCLUSIONS: A majority of dentists who responded to the survey approved of the FFV program and thought it should continue. Although these dentists recommended early first dental visits, the average age recommended by respondents was 6 months later than the target age of 12 months. It appears that, over time, dentists are becoming more aware of prevention and management techniques relating to infants and toddlers.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".