Clinical examination with risk-based recall vs Clinical examination with 24-month recall: Patient satisfaction with actual care received (1-7 scale)
- Population
- Dentate adults (aged 18 years and older) receiving dental check-ups in UK general dental practices (regular attenders)
- Intervention
- Clinical examination with risk-based recall
- Comparison
- Clinical examination with 24-month recall
- Outcome
- Patient satisfaction with actual care received (1-7 scale)
Clinical examination with risk-based recall led to higher patient satisfaction with actual care received (1-7 scale) compared with clinical examination with 24-month recall; GRADE not reported.
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Clinical examination with risk-based recall vs Clinical examination with 24-month recall Patient satisfaction with actual care received (1-7 scale) · Dentate adults (aged 18 years and older) receiving dental check-ups in UK general dental practices (regular attenders) · 4 years Clinical examination with risk-based recall led to higher patient satisfaction with actual care received (1-7 scale) compared with clinical examination with 24-month recall; GRADE not reported. Recall intervals for oral health in primary care patients (2020) · Cochrane All outcomes | MD 0.16 [0.01, 0.31] | 1 study · 304 participants | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Recall intervals for oral health in primary care patients 2020 · Cochrane All outcomes | 2020-01 | Not listed | Not assessed |
Related questions
The same intervention and outcome, asked in another population or against another comparator.
- Clinical examination with risk-based recall vs Clinical examination with 6-month recall · Dentate adults (aged 18 years and older) receiving dental check-ups in UK general dental… · 1 review
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.