The development of an educational resource on mouth care and oral mucositis for patients receiving chemotherapy in Newfoundland and Labrador
Bibliographic record
Abstract
Background: Oral mucositis is a common side effect of chemotherapy. The development of oral mucositis has many negative impacts on the patient receiving chemotherapy and the healthcare system, such as reduced oral intake, increased risk for infection, increased need for medical intervention, interruption to chemotherapy, and increased healthcare costs. Prevention measures and early intervention should be considered to reduce the impact of oral mucositis. Patient education can be used to educate patients receiving chemotherapy about oral mucositis, prevention, early identification and intervention to reduce the impact of oral mucositis. Purpose: This practicum project aimed to develop an educational resource on mouth care and oral mucositis for patients receiving chemotherapy in Newfoundland and Labrador. Methods: Three methods were used to gather information on mouth care and oral mucositis in patients receiving chemotherapy and explore education as an intervention to address this clinical issue. The three methods used included an integrative literature review, an environmental scan, and consultations with key stakeholders. Results: An educational resource, including a resource manual and patient pamphlet, was developed based on the methods used. Orem’s Self-Care Deficit Nursing Theory was used to guide the development of the educational resource. Conclusion: An educational resource on mouth care and oral mucositis was developed for patients receiving chemotherapy in Newfoundland and Labrador. There was no implementation or evaluation component for this practicum project due to time restraints of the course. A plan for future evaluation of the resources will be outlined in this report.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".