Domiciliary dental care for the older adults across countries: a scoping review
Bibliographic record
Abstract
Objectives: With the rapid aging of the global population, maintaining oral health in older adults with frailty has become a major public health priority.Domiciliary dental care, which provides dental services directly at home or in long-term care facilities, has emerged as a promising approach for overcoming barriers to mobility, access, and equity.However, evidence of its structure, effectiveness, and sustainability remains fragmented across countries.This scoping review aimed to map and synthesize international models of domiciliary dental care, focusing on their organizational structures, delivery processes, reported outcomes, limitations, and policy implications.We also sought to identify gaps in evidence and propose future research directions.Methods: Following the PRISMA-ScR framework, we conducted a structured review of the literature on domiciliary dental care systems in Japan, Hong Kong, Taiwan, Germany, the United Kingdom, Canada, and Australia.The data were charted on program design; service coverage; financing; workforce organization; and outcomes related to oral health, patient experience, and systemic challenges.Results: Domiciliary dental care improved access for frail or homebound older adults, facilitated early detection and prevention, enhanced oral health maintenance, and increased patient and caregiver satisfaction across countries.Education components for caregivers and facility staff further contributed to sustained oral hygiene practices.Nevertheless, most services were limited to preventive and basic restorative care, constrained by a lack of portable equipment, inadequate workforce capacity, low reimbursement levels, administrative burden, and legal liability concerns.Evidence from low-and middle-income countries was extremely limited, and few longitudinal and experimental studies were available to assess the cost-effectiveness or long-term outcomes.Conclusions: This scoping review highlights domiciliary dental care as a valuable but underdeveloped public health strategy for aging societies.To achieve sustainability and a broader impact, future efforts must address streamlined administration, standardized guidelines, adequate financing, professional training, and legal safeguards supported by stronger evidence, including economic evaluations and long-term outcome studies.
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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 | 0.011 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.017 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| 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".