Oral health of older residents in care and community dwellers: nursing implications
Bibliographic record
Abstract
BACKGROUND: Poor oral health is associated with a reduced quality of life and serious illnesses. Consequently, nurses need to be more aware of oral health to improve the general health of residents in care. AIM: To evaluate and compare oral health behaviours and levels of salivary haemoglobin and dental biofilm acidogenicity, which can be used to evaluate oral disease activity, between residents and community dwellers in South Korea. METHODS: This cross-sectional study included 133 participants: 64 residents and 69 community dwellers. All participants completed a questionnaire and tests to measure their salivary haemoglobin and dental biofilm acidogenicity. RESULTS: A higher percentage of community dwellers than of residents brushed their teeth three times a day, cleaned their tongue, used interdental cleaning devices and had visited a dental clinic within 1 year. The levels of salivary haemoglobin and dental biofilm acidogenicity tended to be higher in residents than in community dwellers. CONCLUSION: Residents showed poorer oral health behaviours and higher levels of gingival bleeding and acid production by oral bacteria than did community dwellers. IMPLICATIONS FOR NURSING PRACTICE: Nursing staff should enhance their monitoring of oral hygiene status and provide quality oral care to residents through cooperation with dental professionals. IMPLICATIONS FOR NURSING AND HEALTH POLICY: Policymakers should be aware that oral health is an essential component of improving general health and well-being and therefore strive to develop policies to promote oral care services provided to residents. Nursing policies, such as mandating oral care and hands-on training in oral care for nursing staff, are important. We also suggest that factors related to oral care be added to the establishment or accreditation standards of care facilities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".