Can stand-alone computer-based interventions reduce alcohol consumption? A systematic review

ABSTRACT Aim To determine the effects of computer‐based interventions aimed at reducing alcohol consumption in adult populations. Methods The review was undertaken following standard Cochrane and Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) guidance for systematic reviews. The literature was searched until December 2008, with no restrictions on language. Randomized trials with parallel comparator groups were identified in the form of published and unpublished data. Two authors independently screened s and papers for inclusion. Data extraction and bias assessment was undertaken by one author and checked by a second author. Studies that measured total alcohol consumption and frequency of binge drinking episodes were eligible for inclusion in meta‐analyses. A random‐effects model was used to pool mean differences. Results Twenty‐four studies were included in the review (19 combined in meta‐analyses). The meta‐analyses suggested that computer‐based interventions were more effective than minimally active comparator groups (e.g. assessment‐only) at reducing alcohol consumed per week in student and non‐student populations. However, most studies used the mean to summarize skewed data, which could be misleading in small samples. A sensitivity analysis of those studies that used suitable measures of central tendency found that there was no difference between intervention and minimally active comparator groups in alcohol consumed per week by students. Few studies investigated non‐student populations or compared interventions with active comparator groups. Conclusion Computer‐based interventions may reduce alcohol consumption compared with assessment‐only; the conclusion remains tentative because of methodological weaknesses in the studies. Future research should consider that the distribution of alcohol consumption data is likely to be skewed and that appropriate measures of central tendency are reported.