Randomized Controlled Trial of Proactive Web-Based Alcohol Screening and Brief Intervention for University Students

Abstract

Proactive Web-based screening and intervention reduces drinking in undergraduates, and such a program could be implemented widely.

Using Bayes factors for testing hypotheses about intervention effectiveness in addictions research

“…P = primary outcome; S = secondary outcome;* significant at P  < 0.05;** significant at P  < 0.01;*** significant at P  < 0.001;RaR = rate ratio; RR = relative risk; OR = odds ratio; MD = mean difference;Ω range of population SD reflects the CI of the expected effect size;α range of population SD based on opinion on a viable effect; a one‐directional relationship was assumed in all instances; Based on:a 31;b 32;c 33;d 34;e 35;f 36;g values specified in the sample size calculation;h 37;i 38;j 39;k 40;l 41;m 42;n 43;o 44;p 45;q 46;r 47;s 48;t 49;u 50;v 51;w 52;z 53;y values specified in the sample size calculation.HAMD = Hamilton Rating Scale for Depression; p.p.m. = parts per million.…”

Electronic Interventions for Alcohol Misuse and Alcohol Use Disorders

“…Five trials offered 2 to 5 sessions with the e-intervention (for 3 trials that enrolled adults and 2 that enrolled students) (37-40), 1 trial offered 62 sessions (38), and 3 trials (32,41,42) offered participants unlimited access to the program. The most common e-intervention component was personalized normative feedback (for 8 trials that enrolled adults and 12 that enrolled students), but the breadth, intensity, and type of e-interventions that we combined in metaanalyses were heterogeneous.…”

“…One trial rated as low risk of bias in students (38) reported elevated probability of meeting drinking limits in the e-intervention group at 6 months (odds ratio, Binge Drinking-In adults, 1 trial rated as moderate risk of bias found similar proportions of binge drinkers in the e-intervention (23%) and treatment-as-usual groups (25%) at 6 months (difference, −1.9% [CI, −10.4% to 6.6%]) (47). A trial rated as low risk of bias also found similar proportions of binge drinkers in the e-intervention (47%) and control groups (45%) at 6 months (β = 0; SE = 0.01; P = 0.76) (46).…”

Electronic communication based interventions for hazardous young drinkers: A systematic review

“…Hester et al,'s (2012) study comprising of personalised feedback along with decisional balance exercises, social norms and risk factors, found that reductions in drinking and alcohol-related problems tended to be significantly greater in the intervention group compared to the assessment only control group (p < .01). Kypri et al,'s (2014) study consisting of personalised feedback indicated a slight reduction in the amount consumed per typical drinking occasion, providing support that a brief intervention can have some impact upon alcohol consumption (Kaner et al, 2007). However, there was no decrease in the frequency of drinking, overall volume consumed, or in related academic problems.…”

“…Although some of these studies demonstrated a number of strengths, achieving a diverse selection of student population and drinking cultures (Kypri et al, 2014), utilising a randomised controlled design (Hester et al, 2012), and achieving high retention rates (Palfai, Zisserson & Saitz, 2011), some had issues of being underpowered (Cunningham et al, 2012), and potential social desirability bias (Hester et al, 2012) Improving knowledge, self-efficacy and awareness of social norms was found to significantly reduce weekly alcohol consumption (Voogt et al, 2014b), and was particularly effective in lowering drinking levels for subgroups of heavy drinking students in the short-term (Voogt et al, 2013b). It was also found that those in the experimental condition experienced higher social pressure Drinking Refusal Self-Efficacy (DRSE) compared to participants in the control condition, which was sustained after 6 months (Voogt et al, 2014a).…”