A multi‐faceted construct to guide geriatric dental education: Findings from a scoping review with consultation
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Older adults report unmet oral health care needs and barriers in access to care, due in part to provider attitudes and discomfort towards treating older patients. Our study asked: What is known from the literature about the use of undergraduate dentistry programmes to influence dental students' attitudes, perceptions and comfort towards treating geriatric patients? And how can interdisciplinary care facilitate the ability of dentists to work with geriatric patients? MATERIALS AND METHODS: A scoping review and stakeholder consultation followed established methodological guidelines. Four databases and two grey literature sources were searched. Two researchers independently selected articles using predefined inclusion criteria. Pertinent information was inputted into an iteratively developed extraction table. NVivo 12 was used to organise the extracted data into themes. Key findings were confirmed through stakeholder consultation. RESULTS: Sixty-eight articles were included in the scoping review. Five key themes emerged: (1) Curricular targets; (2) Intervention components; (3) Dentist and patient factors; (4) The role of interdisciplinary care; and (5) Post-graduation insights on knowledge-seeking patterns. Stakeholder consultations involved 19 participants from Southwestern Ontario and generally confirmed our findings. CONCLUSIONS: Inconsistent reporting of multiple intervention dimensions constrains our ability to strengthen this knowledge. Future interventions and their reporting could be improved by adopting "willingness to treat" as an overarching, multi-faceted concept which encompasses knowledge on ageing, attitudes towards older patients, perceived competence and empathy. Stakeholder interviews complemented these findings.
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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 | 0.089 | 0.190 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.025 | 0.034 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".