Question · asked by 1 review

Powered toothbrush, rotation oscillation action vs Manual toothbrush: Plaque

Population
Individuals of any age with no reported disability that might affect toothbrushing (including people wearing orthodontic appliances)
Intervention
Powered toothbrush, rotation oscillation action
Comparison
Manual toothbrush
Outcome
Plaque

Powered toothbrush, rotation oscillation action led to lower plaque score (>3 months) compared with manual toothbrush; GRADE not reported.

What each review found

Include earlier review versions
No studies found 0 · 0%GRADE not reported 2 · 100%Very low 0 · 0%Low 0 · 0%Moderate 0 · 0%High 0 · 0%
FindingEffectStudiesGRADE certainty
Powered toothbrush, rotation oscillation action vs Manual toothbrush
Plaque score (>3 months) · Individuals of any age with no reported disability that might affect toothbrushing (including people wearing… · Long term (>3 months)
Powered toothbrush, rotation oscillation action led to lower plaque score (>3 months) compared with manual toothbrush; GRADE not reported.
Powered versus manual toothbrushing for oral health (2014) · Cochrane All outcomes
SMD -0.66 [-1.28, -0.03]7 studies · 527 participantsGRADE not reported
Powered toothbrush, rotation oscillation action vs Manual toothbrush
Plaque score (1 to 3 months) · Individuals of any age with no reported disability that might affect toothbrushing (including people wearing… · Short term (1 to 3 months)
Powered toothbrush, rotation oscillation action led to lower plaque score (1 to 3 months) compared with manual toothbrush; GRADE not reported.
Powered versus manual toothbrushing for oral health (2014) · Cochrane All outcomes
SMD -0.53 [-0.74, -0.31]20 studies · 1404 participantsGRADE not reported

Findings are shown side by side, never pooled across reviews.

The reviews

ReviewSearched up toIncluded studiesAMSTAR 2
Powered versus manual toothbrushing for oral health
2014 · Cochrane All outcomes
2014-01-23Not listedNot assessed
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.