How the public’s knowledge, attitudes, and practice intersect with scientific evidence about fluoride
Bibliographic record
Abstract
For over 75 years, community water fluoridation has been implemented as a public health strategy to reduce dental caries. While early studies suggested dramatic reductions in dental caries, recent evidence indicates that the benefits of community water fluoridation are more modest. Concurrently, concerns have grown over rising rates of enamel fluorosis and possible links between fluoride intake and lowered intelligence in children and thyroid hormone disruption, even at exposure levels found in fluoridated regions. This first part of this paper discusses the historical context and current scientific evidence on the effectiveness of community water fluoridation and safety of systemic fluoride. The second part presents findings from a fluoride survey conducted with 8011 adults in Canada and the U.S. The survey assessed knowledge about fluoride, public perceptions of the risks and benefits of community water fluoridation, and fluoride use with young children. Overall, 60 % of respondents correctly identified why fluoride is added to drinking water. Knowledge of community water fluoridation was higher among older, more educated, and White participants. Among those familiar with community water fluoridation, 51 % expressed support, 27 % opposed it, and 25 % were neutral. Support was primarily driven by confidence in its safety and benefits, while opposition was driven by safety concerns and perceived violations of personal freedom. Trust in public health officials was higher among supporters (87 %) compared with non-supporters of community water fluoridation (52.1 %). When presented with hypothetical risk-benefit scenarios, participants consistently prioritized the prevention of potential health risks, such as reduced IQ, over the relatively modest dental benefit of preventing one cavity. The survey also revealed that most parents report using more fluoride toothpaste for young children than recommended, suggesting a gap in adherence to safe fluoride use guidelines. Our findings highlight mixed public views on community water fluoridation and knowledge gaps surrounding fluoride toothpaste use with children, underscoring the need for clear, evidence-based communication about fluoride exposures.
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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 | 0.026 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.003 | 0.014 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".