Oral Health Education, Knowledge, and Practice Patterns of Nurses Caring for Cancer Patients: A Scoping Review
Bibliographic record
Abstract
Background: Global cancer diagnoses are increasing, and treatment often results in oral health concerns. To improve patient outcomes and quality of life, nurses play a critical role in managing the oral sequelae of treatment. Aims: This scoping review explores nurses’ oral health education, knowledge, and practices when caring for persons living with cancer. Methods: A systematic search of PubMed, DOSS, EMBASE, CINAHL, and Google Scholar identified 10 relevant studies. Results: Inconsistencies in oral care education, knowledge and practice were found among nurses caring for cancer patients. However, nurses with advanced education appear to be more knowledgeable and more likely to prioritize oral care for cancer patients. Collaboration with oral health professionals help to integrate oral health into nursing practice. Conclusions: Oral health practices in cancer care are critical, especially for individuals facing disparities in accessing a dental home. System, institutional, and provider-level supports are needed to enhance oral health in cancer care.
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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 | 0.001 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".