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We cannot ignore bias, especially if effects are small, but we need better methods for evaluating prevention systems.

We made a few data extraction and coding mistakes in our original review, so we asked the Cochrane Group to withdraw the reviewwhile we corrected thesemistakes and updated the search. The updated review will be available in the first part of 2016, and it is unlikely that our original findings and conclusions will change. Grant et al. [1] make four points. The first three concern the methodology of Cochrane Reviews, and among these there is a suggestion that performance bias should be dealt with more leniently. This does not seem right; just because this bias is difficult to deal with in complex behavioural intervention trials does not mean that we should downplay or ignore it. More research is needed to understand the problem and, in the meantime, it seems appropriate to be cautious. Of particular concern when participants are not blinded to study condition and when outcomes are self-reported behaviours is the potential for overestimation of intervention effects. In a systematic review of the effects of blinding participants in trials with self-reported outcomes, Hrobjartsson et al. [2] found that non-blinded participants exaggerated the standardized mean difference (SMD) effect size by an average of 0.56, although with considerable variation. It is therefore a strong plausible hypothesis that the impact of non-blinding of participants in motivational interviewing trials could account fully for any small effects found in our review. Other forms of performance and detection bias are also important. For example, in a systematic review and metaanalysis of 300 randomized trials, Petrosino et al. [3] looked at the impact of non-independent researchers and found that in those trials where programme developers were also the researchers themean effect size was 0.47, comparedwith 0.00 when the evaluation team were external and independent. Petrosino et al. concluded that: ‘studies in which evaluators were greatly influential in the design and implementation of treatment report consistently and substantially larger effect sizes than other types of evaluators’. The Cochrane risk of bias approach does not include an assessment of this particular risk of bias, and the extent to which programme evaluators were involved in developing and delivering the intervention is not always clear from studies. Therefore, we cannot rule out the possibility that the effect sizes obtained in the current reviewmay be inflated by a conflict-of-interest bias. The fourth point should be discussed more widely among researchers and policymakers: what sort of effect size is good enough? Our interpretation of the effect sizes wewere finding across a series of meta-analyses was that they were very small, and unlikely to be of any meaningful benefit on their own, regardless of any possible but unknown reductions in effect sizes due to bias. For example, in the original review, we estimated that the obtained effect sizes would mean (approximately, on average): a decrease in the number of days per week that alcohol was consumed from 2.7 days to 2.5 days; a decrease in the number of drinks consumed each week from 13 to 11 drinks per week; and a decrease in the 69-point Rutgers Alcohol Problems Index (RAPI) from a score of 8.9 to 8.7.We suggest that these achieved effect sizes may fall short of a minimally important clinical difference (MCID). Grant et al. disagree with our interpretation, and that is alright: users of research evidence should make up their own minds on the right interpretation of the evidence. Perhaps an even more important question for the field is this: even if the effects of motivational interviewing for alcohol misuse prevention in young adults are really small, does that mean that we should forget about motivational interviewing as part of a portfolio of different types of prevention interventions [4]? This would be premature, because it is plausible that the whole is greater than the sum of the parts; that the combined effect of multiple single (but individually weak) interventions is worthwhile. However, this should not be seen as a green light for policymakers and practitioners to ignore evidence from randomized controlled trials of single interventions. Rather, it should serve as a focus for the research community. We need better methods for evaluating the combined effect of interventions within prevention systems, and for selecting well-evidenced interventions to incorporate into prevention systems.