Question · asked by 1 review

30 minutes of one-to-one instruction by a dental hygienist covering the relationship between sugar consumption and dental health, plus oral hygiene, fluoride and regular dental visits (a multi-intervention) vs No special instructions (control): Mean sugar consumption (self-reported, 1 to 5 scale; higher score = more positive behaviour)

Population
Adults newly registered at a group dental practice in a suburban Dutch village, the Netherlands
Intervention
30 minutes of one-to-one instruction by a dental hygienist covering the relationship between sugar consumption and dental health, plus oral hygiene, fluoride and regular dental visits (a multi-intervention)
Comparison
No special instructions (control)
Outcome
Mean sugar consumption (self-reported, 1 to 5 scale; higher score = more positive behaviour)

What each review found

Current versions only
FindingEffectStudiesGRADE certainty
30 minutes of one-to-one instruction by a dental hygienist covering the relationship between sugar consumption and dental health, plus oral hygiene, fluoride and regular dental visits (a multi-intervention) vs No instruction
Mean sugar consumption (self-reported, 1 to 5 scale; higher score = more positive behaviour) · Adults newly registered at a group dental practice in a suburban Dutch village, the Netherlands · 6 to 12 months
One‐to‐one dietary interventions undertaken in a dental setting to change dietary behaviour (2012) · Cochrane All outcomes
Table 3, mean (SD) sugar consumption (1-5 scale): instruction group 3.41 (1.50) at baseline to 3.58 (1.07) at follow-up (significant versus baseline); control 2.89 (0.99) to 2.88 (1.27). The review judges the results…1 studyGRADE not reported

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

The reviews

ReviewSearched up toIncluded studiesAMSTAR 2
One‐to‐one dietary interventions undertaken in a dental setting to change dietary behaviour
2012 · Cochrane All outcomes
2012-01Not 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.