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Drug Alcohol Depend. 2017 Jun 1;175:119-126. doi: 10.1016/j.drugalcdep.2017.01.040. Epub 2017 Mar 31.

Who benefits from computer-based brief alcohol intervention? Day-to-day drinking patterns as a moderator of intervention efficacy.

Author information

1
Institute of Social Medicine and Prevention, University Medicine Greifswald, Walther-Rathenau-Str. 48, D-17475 Greifswald, Germany; German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Fleischmannstr. 42-44, D-17475 Greifswald, Germany. Electronic address: sophie.baumann@uni-greifswald.de.
2
Robert Koch Institute Berlin, Department of Epidemiology and Health Monitoring, General-Pape-Str. 62-66, D-12101 Berlin, Germany.
3
Institute of Social Medicine and Prevention, University Medicine Greifswald, Walther-Rathenau-Str. 48, D-17475 Greifswald, Germany; German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Fleischmannstr. 42-44, D-17475 Greifswald, Germany.
4
Department of Psychiatry and Psychotherapy, Medical University of Lübeck, Ratzeburger Allee 160, D-23538 Lübeck, Germany.
5
Institute of Social Medicine and Prevention, University Medicine Greifswald, Walther-Rathenau-Str. 48, D-17475 Greifswald, Germany; German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Fleischmannstr. 42-44, D-17475 Greifswald, Germany; Institute for Medical Psychology, University Medicine Greifswald, Walther-Rathenau-Str. 48, D-17475 Greifswald, Germany.

Abstract

OBJECTIVE:

to test if people with different day-to-day drinking patterns benefitted differently from two brief alcohol interventions (BAIs).

METHODS:

A total of 1243 job-seekers with at-risk alcohol use aged 18-64 years (64% men) were randomized to (a) intervention tailored to the motivational stage (ST), (b) non-stage tailored intervention (NST), or (c) assessment only (AO). ST and NST contained individualized computer-generated feedback letters. Follow-ups were conducted at months 3, 6, and 15. Using growth mixture models, day-to-day drinking patterns were identified based on the number of drinks consumed on each day in the week prior to baseline assessment. To test drinking pattern-specific intervention effects, zero-inflated growth models were used. Outcomes were (1) the 15-month change in the likelihood of any alcohol use and (2) the 15-month change in the total number of drinks per week when alcohol was consumed.

RESULTS:

Four day-to-day drinking patterns were found: daily medium use (2-4 drinks/day; 47%), daily low use (1-2 drinks/day; 29%), weekend only use (18%), and no use (6%). Only persons with daily low use benefitted from intervention, with higher odds of being abstinent after 15 months in the ST group compared to AO (odds ratio, OR=1.67, p=0.001) and NST group (OR=1.43, p=0.035). ST worked better among persons with daily low use compared to daily medium use (OR=1.91, p=0.001).

CONCLUSIONS:

Among at-risk drinking persons with regular low-quantity alcohol use, stage tailored BAIs may be superior over no BAI and non-stage tailored BAIs.

KEYWORDS:

Alcohol; Brief intervention; Computerized intervention; Drinking patterns; Growth mixture modeling; Stage tailored intervention

[Indexed for MEDLINE]

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