Question · asked by 1 review
Theory-based oral health education/promotion interventions (HBM, TPB, SCT, HAPA, TTM, PMT, SOC, PRECEDE-PROCEED, MI) vs Control (waitlist, routine/standard oral health education, or minimal intervention): Periodontal health status
- Population
- school‐age children and adolescents
- Intervention
- Theory-based oral health education/promotion interventions (HBM, TPB, SCT, HAPA, TTM, PMT, SOC, PRECEDE-PROCEED, MI)
- Comparison
- Control (waitlist, routine/standard oral health education, or minimal intervention)
- Outcome
- Periodontal health status
Theory-based interventions significantly improved periodontal health (SMD -1.18; moderate certainty).
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Theory-based oral health education/promotion interventions (HBM, TPB, SCT, HAPA, TTM, PMT, SOC, PRECEDE-PROCEED, MI) vs Control (waitlist, routine/standard oral health education, or minimal intervention) Periodontal health (gingival/periodontal indices) · Children and adolescents aged 5-18 years · Post-intervention (follow-up 2 weeks to 6 months, varies by study), School-based and community settings; multiple countries (predominantly Iran; also Pakistan, Hong Kong, Lithuania, Thailand), Overall Theory-based interventions significantly improved periodontal health (SMD -1.18; moderate certainty). Health promotion theory-based educational interventions for improving oral health in children and… (2025) All outcomes | SMD -1.18 [-1.83, -0.53] | 4 studies · 3342 participants | Moderate |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Health promotion theory-based educational interventions for improving oral health in children and adolescents: a systematic review and… 2025 All outcomes | Up to March 2025 (searches conducted January to March 2025) | 36 | Critically Low / Critically Low |
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.