Oral cancer screening: knowledge is not enough
Bibliographic record
Abstract
OBJECTIVES: The purpose of this cross-sectional study was to investigate whether dental hygienists are transferring their knowledge of oral cancer screening into practice. This study also wanted to gain insight into the barriers that might prevent dental hygienists from performing these screenings. METHODS: A 27-item survey instrument was constructed to study the oral cancer screening practices of licensed dental hygienists in Nova Scotia. A total of 623 practicing dental hygienists received the survey. The response rate was 34% (n = 212) yielding a maximum margin of error of 5.47 at a 95% confidence level. Descriptive statistics were calculated using IBM SPSS Statistics v21 software (Armonk, NY:IBM Corp). Qualitative thematic analysis was performed on any open-ended responses. RESULTS: This study revealed that while dental hygienists perceived themselves as being knowledgeable about oral cancer screening, they were not transferring this knowledge to actual practice. Only a small percentage (13%) of respondents were performing a comprehensive extra-oral examination, and 7% were performing a comprehensive intra-oral examination. The respondents identified several barriers that prevented them from completing a comprehensive oral cancer screening. CONCLUSIONS: Early detection of oral cancer reduces mortality rates so there is a professional responsibility to ensure that comprehensive oral cancer screenings are being performed on patients. Dental hygienists may not have the authority in a dental practice to overcome all of the barriers that are preventing them from performing these screenings. Public awareness about oral cancer screenings could increase the demand for screenings and thereby play a role in changing practice norms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| 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".