May 2009 ■ Journal of Dental Education 581 Oral Care for Frail Elders: Knowledge, Attitudes, and Practices of Long-Term Care Staff
Bibliographic record
Abstract
offers dental services and provides a compre-hensive in-service education program for nursing and residential care-aide (RCA) staff in the provision of daily mouth care for elders in various long-term care (LTC) facilities in Vancouver. This study examined the general impact of the education initia-tive at one LTC site. A survey (N=90), semi-structured open-ended interviews (N=26), and product audits were conducted to 1) examine the impact of the GDP education initiative on the level of knowledge, attitudes, and practices of RCAs and nurs-ing staff regarding the provision of daily mouth care; 2) identify the enablers and barriers that influenced the provision of daily mouth care practices, policies, and protocols using the PRECEDE-PROCEED model of health promotion research; and 3) assess the self-perceptions of RCAs and nursing staff members regarding their oral health. A knowledge gap was evident in some key areas pertaining to prevention of dental diseases. Twenty-five percent of residents were missing toothbrushes and toothpaste for daily mouth care. Residents who exhibit resistance to mouth care tended not to receive regular care, while issues such as time, increased workload, limited staff, and the lack of an accountability structure are disenabling factors for provision of daily mouth care. Results suggest that the impact of educational interventions is affected by the quality of in-service education, an absence of identified predisposing, reinforcing, and enabling factors, and a strong commitment among LTC staff to the provision of daily
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".