The Impact of Dental Care Programs on Individuals and Their Families: A Scoping Review
Bibliographic record
Abstract
BACKGROUND: Despite significant global improvements in oral health, inequities persist. Targeted dental care programs are perceived as a viable approach to both improving oral health and to address inequities. However, the impacts of dental care programs on individual and family oral health outcomes remain unclear. OBJECTIVES: The purpose of this scoping review is to map the evidence on impacts of existing dental programs, specifically on individual and family level outcomes. METHODS: We systematically searched four scientific databases, MEDLINE, EMBASE, CINAHL, and Sociological Abstracts for studies published in the English language between December 1999 and November 2021. Search terms were kept broad to capture a range of programs. Four reviewers (AG, VD, AE, and KKP) independently screened the abstracts and reviewed full-text articles and extracted the data. Cohen's kappa inter-rater reliability score was 0.875, indicating excellent agreement between the reviewers. Data were summarized according to the PRISMA statement. RESULTS: The search yielded 65,887 studies, of which 76 were included in the data synthesis. All but one study assessed various individual-level outcomes (n = 75) and only five investigated family outcomes. The most common program interventions are diagnostic and preventive (n = 35, 46%) care, targeted children (n = 42, 55%), and delivered in school-based settings (n = 28, 37%). The majority of studies (n = 43, 57%) reported a significant improvement in one or more of their reported outcomes; the most assessed outcome was change in dental decay (n = 35). CONCLUSIONS: Dental care programs demonstrated effectiveness in addressing individual oral health outcomes. However, evidence to show the impact on family-related outcomes remains limited and requires attention in future research.
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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 | 0.027 | 0.115 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.022 | 0.023 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".