Knowledge of HPV and its association with oropharyngeal cancer among dental students: a systematic review and meta-analysis
Bibliographic record
Abstract
Background Human papillomavirus (HPV) infection is a significant risk factor for oropharyngeal cancer (OPC), yet dental students' knowledge of this association varies widely. Given the critical role dentists play in early detection and prevention, understanding their level of knowledge is essential. This study systematically reviews existing research to assess dental students' awareness of HPV and its link to OPC. Methods A systematic review and meta-analysis were conducted following PRISMA guidelines. PubMed, ProQuest, and Web of Science databases were searched for studies published up to August 2023. The Newcastle-Ottawa Scale was used to evaluate study quality. A random effects model was applied to calculate pooled prevalence with 95% confidence intervals. Results Sixteen studies, comprising 6,345 participants, were included. The pooled analysis showed that 69% of dental students had general knowledge of HPV (range: 56%–96.5%; 95% CI: 0.56–0.81), while 77% recognized its association with OPC (range: 18%–96.4%; 95% CI: 0.63–0.89). Significant heterogeneity was observed across studies ( Q = 646.34, P < 0.001 for HPV; Q = 804.07, P < 0.001 for HPV-OPC). Conclusion Knowledge gaps among dental students may hinder prevention efforts. Standardized education in dental curricula is crucial to ensure future dentists are well-prepared to address HPV-related conditions and promote early detection in clinical practice.
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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 | 0.014 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.037 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".