A Meta-analysis Comparing Toothbrush Technologies on Gingivitis and Plaque
Bibliographic record
Abstract
BACKGROUND: Research continues to show an association between oral health and systemic health, further stressing the importance of effective daily plaque removal via toothbrushing to maintain periodontal health and overall well-being. This investigation was undertaken to compare the efficacy of oscillating-rotating, sonic, and manual toothbrushes in reducing gingivitis and plaque in randomised controlled trials (RCTs) with up to 6 months' follow-up. METHODS: This meta-analysis was conducted from a single database (Procter & Gamble Oral Care Clinical Archive) including RCTs from 2007 to 2022. Three authors independently assessed study eligibility. Disagreements concerning selected studies were resolved by discussion with an expert colleague. Direct and indirect treatment comparisons along with transition rates to gingival health were calculated using participant-level data. Transition-to-health time was calculated using data from all time points. Subregion analyses evaluated number of bleeding sites and plaque reduction. RESULTS: This meta-analysis included 21 gingivitis RCTs and 25 plaque RCTs. Relative to manual and sonic brushes, oscillating-rotating brushes had a higher percentage of participants who transitioned to gingival health (72% vs 21% and 54%; P < .001). Compared with manual and sonic brushes, respectively, oscillating-rotating brushes demonstrated greater bleeding site reductions (by 52% and 29%; P < .001) and superior plaque reductions (by 19% and 5%; P < .001). Oscillating-rotating brushes provided faster transitions to health than sonic brushes and showed greater efficacy across subregions. The most advanced oscillating-rotating brush demonstrated statistically significantly greater efficacy compared with traditional oscillating-rotating, manual, and sonic brushes when analysed separately. Risk of bias was deemed low for all studies. CONCLUSIONS: Oscillating-rotating toothbrushes offer superior results for transition to health, gingivitis, and plaque reduction compared with manual and sonic brushes. The most advanced oscillating-rotating model offers enhanced efficacy vs traditional models.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.023 | 0.043 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.061 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".