The teaching of geriatric dentistry in South Korean dental schools
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to investigate the curriculum of geriatric dentistry for undergraduates in Korean dental schools. BACKGROUND: For development purposes, it was necessary to compare geriatric dentistry education programmes in South Korea to programmes in the United States and Europe. METHODS: The most recent curriculum and related information on geriatric dentistry at the undergraduate level in all 11 dental schools in South Korea were collected by both official letter and e-mail. A symposium for gathering expert opinions to improve geriatric dentistry education in South Korea was also held. The collected data were analysed, and the expert opinions at the symposium were summarised. RESULTS: Six of 11 schools had a didactic course as compulsory and three schools as elective. The course was usually conducted as a form of integrated lectures, and the level of standardisation of lecture content was very low. There were no topics for older people who cannot access dental clinics due to functional frailty or disability. No dental school-affiliated hospitals had an independent department for geriatric dentistry. No schools provided clinical teaching for geriatric dentistry. There were no outreach programmes for geriatric dentistry. CONCLUSIONS: The educational curriculum for geriatric dentistry in South Korea was insufficient to cope with social and demographic changes. Curriculum content should include clinical practice education and needs to be focused on frail and dependent older adult patients. An essential educational curriculum and core competency for geriatric dentistry should be prepared.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".