“Education Is Definitely Key”: An Interpretive Description of Nursing Students’ Experiences With Pediatric Oral Health Nursing Education
Bibliographic record
Abstract
In North America, dental disease is the leading pediatric chronic illness. Poor oral health influences a child’s ability to speak, eat, and socialize and has been linked with heart disease, diabetes, and cancer. Despite overwhelming evidence that poor oral health can have lifelong and systemic influences on overall well-being, comprehensive oral health care has not been emphasized in nursing education. The purpose of this study was to explore third-year nursing students’ perceptions and experiences with pediatric oral health nursing education through an interpretive description approach. Data for analysis gathered in focus group interviews resulted in three main themes: nursing education is key: recognition of and insight into the value of oral health care; fading away: barriers to education and practice; and spreading the culture: improving nursing education and practice. The findings highlight a predominant culture in nursing education and practice in which knowledge and skill acquisition related to pediatric oral health is being neglected. Consequently, nursing students experience limited development of the basic knowledge, skills, and resources to adequately care for infants, children, and adolescents in a holistic and comprehensive manner. Effective strategies to improve nursing education include early integration of oral health concepts, demonstration and hands-on preparation of oral health care practices and assessment, and interprofessional oral health 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 | 0.017 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.015 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.007 |
| 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".