Oral health knowledge, attitudes, and practices of paediatric nurses caring for hospitalized children
Bibliographic record
Abstract
Objectives Nurses are well positioned to provide oral care to hospitalized children. This study explores pediatric hospital nurses’ knowledge, attitudes, practices and perceived barriers to providing oral care. Methods Using a descriptive cross-sectional design, previously validated surveys were adapted based on input from key stakeholders and administered to all nurses and staff providing patient care on inpatient units (N = 239) of a pediatric hospital. Results The survey response rate was 40% (N = 96), providing a margin of error of 7.59% (95% C.I.). Most participants were unaware that caries is infectious (51%, n = 49) and caries-producing bacteria is transmissible (35%, n = 34). The majority (57%, n = 52) of participants did not recall oral care content within their formal education or oral care continuing education (88%, n = 81), despite high interest (87%, n = 80). Oral care was rated by most as a priority (85%, n = 81), yet the majority (74%, n = 69) believed it is under performed. More nurses with 6 or more years of experience placed a high or very high value on prioritizing oral health (p = 0.005). Furthermore, most nurses do not assess oral health on admission (63%, n = 60), routinely incorporate oral health into the care plan (45%, n = 43), or document oral care (60%, n = 56). Commonly reported barriers include lack of patient cooperation, medical status, and competing needs. Conclusions and outcome Despite nurses valuing the importance of oral care and their willingness to learn, oral care practices are lacking, and barriers exist. Future investigation is required to further explore the findings related to barriers to care and lack of practice. These results and future findings will be used to guide institutional oral care policy and education.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".