What is Being Taught to Canadian Undergraduate Dental Students About the Oral Health of Long-Term Care Residents?
Bibliographic record
Abstract
INTRODUCTION: Residents of long-term care (LTC) facilities face many oral health challenges, which are often complicated by their underlying medical conditions, use of medications and limited access to oral health care. OBJECTIVE: To determine to what extent accredited university-based dental and dental hygiene programs in Canada prepare students in the areas of geriatric oral health and oral health of LTC residents. METHODS: Accredited dental and dental hygiene programs across Canada were assessed for the degree of education and training that is presented to students on the oral health of LTC residents. A survey questionnaire, emailed to programs, was used to gather descriptive statistics (frequencies, means and standard deviations), and bivariate analysis (χ2 and t tests) was completed. A p value ≤ 0.05 was considered significant. RESULTS: Representatives of all 4 dental hygiene and 9 out of 10 dental schools responded. All four dental hygiene and seven dental programs (77.8%, 7/9) stated that geriatric oral health is an integral part of their curriculum. The majority (91.6% [11/12], 4 dental hygiene and 7 of 9 dental schools) reported that their program educates students about medically, physically and cognitively compromised geriatric patients. Eight programs (3 dental hygiene and 5 dental schools), stated that they provide clinical training opportunities with LTC residents. However, some programs reported certain barriers preventing them from providing such clinical training opportunities. CONCLUSION: Oral health educational institutions must ensure that curricula are current and evidence-based to reflect the overall oral health needs of today's aging population.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".