Awareness and knowledge of oral cancer in the city of Baghdad, Iraq: a questionnaire-based survey
Bibliographic record
Abstract
Introduction: Early detection and successful management of oral cancer (OC) is highly dependent on the early detection of this malignancy, which is related to individuals' awareness and knowledge about this fatal condition.Objectives: This pilot study was designed to estimate awareness degree of Iraqi patients about OC.Material and methods: A total of 1,024 questionnaires were mailed to six randomly selected governmental specialized dental centers in the city of Baghdad.The questionnaire consisted of basic information section including age, gender, alcohol drinking, smoking, and frequency of dental visits.The other section comprised seven questions to estimate the degree of OC awareness.Results: A total of 318 participants (60% females, 40% males) responded to the questionnaire.The mean response of the sample was 0.36 ± 0.201, and the majority of participants answered only 2-3 questions correctly and no one responded to all seven questions correctly.The association of awareness to different factors showed that the only significant finding was related to information given by a dentist to the patient (OR: 2.9; 95% CI) about OC.Conclusions: In general, the degree of awareness of Iraqi patients was low about OC.The knowledge about OC considerably increased when the subjects received information from their dentists.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".