Sonic toothbrushing vs Manual toothbrushing: Ease of maintenance
- Population
- Adults with dental implants and peri-implant mucositis at baseline
- Intervention
- Sonic toothbrushing
- Comparison
- Manual toothbrushing
- Outcome
- Ease of maintenance
Sonic toothbrushing showed no clear difference in ease of maintenance compared with manual toothbrushing; GRADE not reported.
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Sonic toothbrushing vs Manual toothbrushing Ease of maintenance · Adults with dental implants and peri-implant mucositis at baseline · 6 months Sonic toothbrushing showed no clear difference in ease of maintenance compared with manual toothbrushing; GRADE not reported. Interventions for replacing missing teeth: maintaining and recovering soft tissue health around dental… (2010) · Cochrane All outcomes | RR 0.94 [0.79, 1.12] | 1 study · 31 participants | GRADE not reported |
Sonic toothbrushing vs Manual toothbrushing Ease of maintenance · Adults with dental implants and peri-implant mucositis at baseline · 6 months Interventions for replacing missing teeth: maintaining and recovering soft tissue health around dental… (2008) · Cochrane All outcomesearlier version CD003069.PUB3, superseded | After 6 months no statistically significant difference in difficulty in brushing | 1 study · 31 participants | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Interventions for replacing missing teeth: maintaining and recovering soft tissue health around dental implants 2010 · Cochrane All outcomes | 2010-06-02 | Not listed | Not assessed |
Related questions
The same intervention and outcome, asked in another population or against another comparator.
- Sonic toothbrushing vs Manual toothbrushing · People with dental implants · 0 reviews
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.