What do we know about portable dental services? A scoping review
Bibliographic record
Abstract
BACKGROUND: Delivering dental care to patients in their home or residential institutions is known as "portable dentistry". The demand for portable dental services is on the rise, but dentists remain reluctant to adopt portable practices. OBJECTIVES: To explore the literature on portable dental services and understand (a) the process of planning and delivering portable dental services and (b) the benefits and challenges of portable dentistry for service providers and patients. METHODS: A systematic scoping search was conducted. We retrieved 3994 documents, 28 of which were included in the final synthesis. Three authors read the papers and conducted thematic content analyses independently. RESULTS: We present a synthesis of the literature and proposed a model of portable dentistry containing three levels with the patient is at the centre surrounded by concentric rings representing the dentist (dental team) and society. At each of these levels, our model is further subdivided into three components: 1) organisation of the service; 2) arrival and set-up of the service; and 3) delivery of the service. In addition, each level includes 1) human factors, which are related either to the dental professional or the patient; 2) non-human factors, which refer to either the equipment or the physical environment; and 3) financial factors, which are related to cost and remuneration. CONCLUSIONS: We propose a model for portable dentistry that dentists and dental educators interested in this practice should find useful.
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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 | 0.012 | 0.083 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.024 | 0.026 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".