A randomized controlled non-inferiority trial of primary care-based facilitated access to an alcohol reduction website (EFAR Spain).

backgroundBrief interventions (BI) for risky drinkers in primary healthcare have been demonstrated to be cost-effective but they are still poorly implemented. Digital BI seems to be a complementary strategy to overcome some barriers to implementation but there is a scarcity of studies in clinical environments. We present the results of a randomized controlled non-inferiority trial which tests the non-inferiority of facilitated access to a digital intervention (experimental condition) for risky drinkers against a face-to-face BI (control condition) provided by primary healthcare professionals.

methodIn a non-inferiority randomized controlled trial, unselected primary healthcare patients (≥ 18 years old) were given a brief introduction and asked to log on to the study website to fill in the 3-item version of the Alcohol Use Disorders Identification Test. Positively screened patients (4+ for women and 5+ for men) received further online assessment (AUDIT, socio-demographic characteristics and EQ-5D-5L) and were automatically randomized to either face-to-face or digital BI (1:1). The primary outcome was the proportion of patients classified as risky drinkers by the digitally administered AUDIT at month 3. A multiple imputation approach for the missing data was performed.

resultsOf the 4499 patients approached by 115 healthcare professionals, 1521 completed the AUDIT-C. Of the 368 positively screened patients, 320 agreed to participate and were randomized to either intervention. At month 3, there were more risky drinkers in the experimental group (59.8%) than in the control group (52%), which was similar to the distribution at baseline and less than the pre-specified margin of 10%. The difference was not significant when accounting for possible confounders.

conclusionDigital BI was not inferior to face-to-face BI, in line with previous findings and the a priori hypothesis. However, the low power of the final sample, due to the low recruitment and loss to follow-up, limits the interpretation of the findings. New approaches in this field are required to ensure the effective implementation of digital interventions in actual practice.