Oral cancer: knowledge, practices and opinions of dentists in Ireland.
Bibliographic record
Abstract
PURPOSE OF THE STUDY: Early detection of oral cancer improves prognosis, but the malignancy is often detected at advanced stages, when more aggressive therapies, often with poor and devastating outcomes for the patient, are needed. Oral cancer can be detected by opportunistic screening of oral mucosa without need of sophisticated equipment. Dentists are important in primary and secondary prevention of oral cancer; therefore, assessing their knowledge, opinions and practices is crucial. MATERIALS AND METHODS: A questionnaire survey of dentists was conducted regarding knowledge of risk factors and diagnostic concepts of oral cancer, practices of primary and secondary prevention, and opinions of the effectiveness of formal undergraduate training for early detection and prevention of this disease. The survey explored dentists' potential training needs. RESULTS: Dentists appear to be generally knowledgeable regarding diagnostic concepts and risk factors. A total of 89% reported providing screening of intra- and extra-oral soft tissue to adult patients (18+) to exclude oral cancer. A total of 27% always provide tobacco use cessation counselling, and 12% provide alcohol moderation/cessation assistance. A total of 54% felt adequately trained to palpate the lymphatic nodes associated with oral cancer. Over half of dentists reported that their knowledge of and training on oral cancer was current; however, 74% reported lack of patient education materials regarding prevention and early detection of oral cancer. CONCLUSIONS: The survey findings suggest that dentists are underutilised in the prevention and early detection of oral cancer, and one of the barriers is lack of training. Dentists' knowledge and skills must be reinforced and systematically updated by continuing professional education. Greater emphasis should be placed on the fact that dentists have a larger role to play in the prevention and detection of this malignancy at its early, curable stages.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".