Oral-health promotion programs (OHPPs): community-based oral-health education/training, supervised toothbrushing with fluoride toothpaste and topical fluoride, dental screening, and dietary advice vs No oral-health promotion program, or a differing (usual-care) action under similar conditions: Incremental cost‐effectiveness
In children younger than 6 years, OHPPs were associated with lower cost per DMFT/S (OR 0.07, 95% CI 0.02 to 0.32; ungraded).
What each review found
Include earlier review versions| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Oral-health promotion programs (OHPPs): community-based oral-health education/training, supervised toothbrushing with fluoride toothpaste and topical fluoride, dental screening, and dietary advice vs No oral-health promotion program, or a differing (usual-care) action under similar conditions Incremental cost-effectiveness per DMFT/S · Children younger than 6 years (healthy except for dental caries) · Community settings: home visits, telephone contacts, healthcare centers, and primary schools, Age < 6 years In children younger than 6 years, OHPPs were associated with lower cost per DMFT/S (OR 0.07, 95% CI 0.02 to 0.32; ungraded). Clinical Effectiveness and Cost-Effectiveness of Oral-Health Promotion in Dental Caries Prevention among… (2019) All outcomes | OR 0.07 [0.02, 0.32] | 6 studies | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Clinical Effectiveness and Cost-Effectiveness of Oral-Health Promotion in Dental Caries Prevention among Children: Systematic Review and… 2019 All outcomes | 11 December 2018 (search initiated) | 29 | Critically Low / Critically Low |
Studies behind the findings
None of these reviews ties its included studies to this outcome in the data here. Cochrane reviews and reviews with headline outcomes only do not list their studies yet.
How reviews are matched to this question
Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.