Feeding and Oral Care Guidelines for Certified Nursing Assistants Working with Patients with Head and Neck Cancer
Bibliographic record
Abstract
Feeding and Oral Care in Head and Neck Cancer 2 This project was developed after participating in a clinical experience that required graduate speech-language pathology students to assist with feeding elderly patients in a skilled nursing facility .These patients are typically fed by certified nursing assistants (CNA) with reduced training during their educational course on proper feeding for patients with specific swallowing-related disorders.This guided the purpose of the project which was to research the current licensure requirements in the state of Illinois for programs that train CNA's, obtain CNA perceptions for providing feeding and administering oral care to subpopulations at a higher risk of a medical diagnosis of dysphagia, and develop a resource based on a deficit observed in the survey.For this project, an online survey was created and distributed through social media platforms that asked CNA's to indicate how long they have worked as a CNA, the state they work in, a text box to list what they currently know about best feeding practices, a yes/no response to identification of 3-4 signs and symptoms of dysphagia, and six yes/no responses regarding perceptions that their CNA program adequately prepared them to feed and provide oral care to the following subpopulations: stroke, dementia, and individuals with head and neck cancer.The survey yielded responses from 73 participants across the United States representing 26 states and 2 participants from Canada.Based upon results of the survey, 77% of CNA's that participated felt that their education program for obtaining a CNA license did not adequately prepare them to provide oral care to patients with head and neck cancer.Similarly, 79% of participants did not feel adequately prepared to feed individuals with head and neck cancer.Full survey questions and results can be found in the appendix.As a result of the survey responses, this project will consist of a brochure that will inform CNAs proper feeding guidelines and oral care considerations for providing care to patients with head and neck cancer.
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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 | 0.003 | 0.010 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".