Brief motivational interviewing (BMI) vs usual treatment alone: Alcohol consumption: consuming more than 21 units of alcohol per week
- Population
- Male patients aged 16 to 35 years attending an oral and maxillofacial surgery outpatient clinic for follow-up of an alcohol-related facial injury, Welsh dental teaching hospital
- Intervention
- Brief motivational interviewing (BMI)
- Comparison
- usual treatment alone
- Outcome
- Alcohol consumption: consuming more than 21 units of alcohol per week
Brief one-session, manual-guided discussion based on the principles… led to lower alcohol consumption: consuming more than 21 units of alcohol per week compared with treatment at the outpatient clinic as usual; GRADE not reported.
What each review found
Include earlier review versions| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Brief one-session, manual-guided discussion based on the principles of motivational interviewing (aimed at reducing alcohol consumption) vs Treatment at the outpatient clinic as usual Alcohol consumption: consuming more than 21 units of alcohol per week · Male patients aged 16 to 35 years attending an oral and maxillofacial surgery outpatient clinic for follow-up of an… · 12 months Brief one-session, manual-guided discussion based on the principles… led to lower alcohol consumption: consuming more than 21 units of alcohol per week compared with treatment at the outpatient clinic as usual; GRADE not reported. One‐to‐one dietary interventions undertaken in a dental setting to change dietary behaviour (2012) · Cochrane All outcomes | RR 0.52 [0.32, 0.85] | 1 study · 151 participants | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| One‐to‐one dietary interventions undertaken in a dental setting to change dietary behaviour 2012 · Cochrane All outcomes | 2012-01 | Not listed | Not 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.