Scale among hundreds of other measures); inclusion criteria for eligible RCTs differed across reviews; and the review authors’ conclusions were often inconsistent across reviews. Therefore, for this application, the bubble plots simply differentiate the findings according to 4 categories: “evidence of no effect,” “unclear evidence,” “evidence of a potential positive effect,” and “evidence of a positive effect.” The category “evidence of no effect” was used for research areas that provided evidence for no positive effect, that is to say reviews which showed that results in the control groups are equivocal or better than in the acupuncture group. The “unclear evidence” category was used for conflicting results across reviews that could not be resolved or for conflicting results within reviews with authors summarizing the evidence as inconclusive. The “evidence of a potential positive effect” category was used for those areas where reviews showed that all individual RCTs or the pooled effect across RCTs were positive, but the best available secondary evidence or all systematic reviews concluded that the evidence base was insufficient to draw firm conclusions despite the statistically significant positive treatment effect. For example, several systematic reviews produced pooled estimates of effects that were statistically significantly positive, yet the review authors judged the evidence insufficient due to limitations of the included trials. The final category, “evidence of a positive effect,” was used for clinical areas with evidence of a statistically significant positive effect of acupuncture and where authors of the best available secondary literature recommended the intervention without major concerns regarding the existing evidence. For each clinical topic, all available systematic reviews and recently published trials were reviewed. Most emphasis was given to Cochrane reviews, individual patient data reviews, and the largest review or recent trial. For topics with narrative reviews without statistical metaanalysis, conflicting results across or within reviews that could be resolved by a synthesis including all relevant RCTs, and for areas where a recent large trial was identified that was not yet incorporated into existing reviews, a statistician checked whether studies could be pooled and performed a meta-analysis to determine the treatment effect. The reanalysis used the data documented in the systematic reviews; it was not feasible to obtain primary study data from several hundred RCTs included in existing reviews. In many cases, it was not possible to resolve the conflicting evidence. Furthermore, the bubble plots summarize dozens of clinical areas, of which each area is represented by up to 10 recent reviews, each review potentially summarizing a large number of individual research studies. Hence the clinical effectiveness category should not be construed as a definitive answer of the effectiveness but rather represents a broad overview, or trend, to broadly summarize the research field. The effect determination focused on the effectiveness of acupuncture compared to that of “passive” control groups, such as a waiting list group, no treatment, placebo / sham acupuncture, Evidence Map of Acupuncture Evidence-based Synthesis Program 6 prescription-free or provider-independent interventions, usual care not further specified, and treatments given to both RCT arms. As we discuss in the future research section, what constitutes a valid control group for acupuncture intervention studies is an area of controversy. For this broad map of the literature we did not favor one control modality over another and had to rely on the published reviews to differentiate or pool across passive comparators. In order to provide a coherent and easy-to-interpret bubble plot across individual topics, we did not include the comparative effectiveness of acupuncture, that is to say acupuncture compared to active comparators such as medication interventions (e.g., equivalence or superiority assessments for acupuncture versus antidepressants). Instead, identified comparative effectiveness results were summarized in the narrative synthesis. Confidence Finally, our confidence in the effect for each clinical indicator is represented by the size of the corresponding bubble. By default, we categorized our level of confidence as “Medium”. We changed the confidence to “High” only if an effect was shown in a Cochrane review adhering to strict methodological criteria or in an IPD systematic review not subject to typical meta-analytic limitations, based on the assumption that both of these kinds of reviews represent stronger evidence than an average systematic review. We changed the confidence to “Low” if the reported treatment effect was based primarily on studies not indexed in the largest medical database PubMed (defined as more than 50% of relevant RCTs not indexed) based on the assumption that studies in journals and other outlets not indexed in PubMed are more likely to be of low quality than studies published in PubMed-indexed journals. This issue has been shown to be of particular relevance to the research area acupuncture.22,23 Given the large number of clinical topics, the large number of reviews, and the fact that some clinical topics were associated with up to 10 current systematic reviews from independent author groups, this