Wellness, and Mental Health. In addition, we added categories for Other Indications and for Adverse Events. General acupuncture reviews that could not be categorized as addressing pain, wellness, or mental health were included in the Other Indication domain. Topics of other indications were only eligible for synthesis if at least 3 systematic reviews or recent large RCTs were available for the specific topic. Topic grouping into the priority domains was guided by a technical expert panel. All reviews focusing on pain regardless of the underlying condition were assigned to the Pain domain. The Wellness domain was used as a broad category covering a wide range of clinical indications and outcomes. This included reviews of indication-unspecific outcomes such as quality of life, reviews of treatments for chronic conditions that reported on symptoms that could be experienced by generally healthy people such as nausea, and reviews of very common conditions such as insomnia. The Mental Health domain covered core mental health conditions and chronic fatigue syndrome due to the use of mental health outcomes in the review. Topics were classified as Other Indication if they did not fit into the VA priority groups. Reviews on adverse Evidence Map of Acupuncture Evidence-based Synthesis Program 4 events were assigned to the Adverse Event category if they did not report on the therapeutic effectiveness of acupuncture as well. Where possible, reviews were assigned to one topic only based on the primary focus of the review rather than incorporated multiple times into the evidence synthesis. BUBBLE PLOTS The evidence base was distilled into a visual overview of each of the 3 VA priority areas using a bubble plot format. In order to be included in the bubble plots, reviews had to report effect sizes for patient health outcomes for each included study or a pooled result across included studies; present the citations for included studies so that the evidence was identifiable; report on RCT data; and report the effects of passive-controlled studies. We extracted the specific topic (eg, depression treatment), the number of included RCTs, and the size of the treatment effect for the main patient outcomes according to passive-controlled RCT data, from each included systematic review with bubble plot-relevant data. We also extracted additional review characteristics such as whether the review was a Cochrane review or an independent patient data (IPD) review, whether the review showed a positive treatment effect in assessor-blinded RCTs, and whether a majority of studies included in the review not indexed in PubMed. The bubble plots displays information about the research area in 3 dimensions: the estimated literature size (y-axis), the estimated treatment effect (x-axis), and the confidence in the reported effect (bubble size). Given the format, the large number of existing reviews, and the scope of this project, the bubble plots can only represent limited information. Literature size First, the bubble plots provide an overview of the research volume or quantity for the included topics in each priority area. For this estimate, we used the number of included RCTs per review, selecting the systematic review with the most included acupuncture RCTs for the individual topic as the research volume estimate. Reviews vary in their inclusion criteria for study designs (for example whether or not they include observational studies) and providing the volume for a well-established research design such as RCT that is always likely to be included should provide a broad estimate. Furthermore, the number of RCTs should provide an indicator of the overall research volume sufficient for this map of the literature. A pilot test showed that an alternative method, cumulatively adding all studies included in reviews on a particular clinical indication to a database to determine the complete research pool, is immensely time consuming and not feasible for large-scale evidence maps. In the case of acupuncture research, hundreds of individual studies need to be cross-checked against dozens of reviews to prevent duplication, but the lack of unique study identifiers and differences in translation of study titles make such crosschecking impractical within the project timeframe and resources. Clinical effectiveness Secondly, the bubble plots provide a broad estimate of the clinical effectiveness of acupuncture for each differentiated clinical indication. This estimate of clinical effectiveness should ideally be a continuous measure representing the summary effect size for the clinical indication. However, in trying to apply this display method to reviews of acupuncture, we were unable to Evidence Map of Acupuncture Evidence-based Synthesis Program 5 use a continuous measure such as effect size. Because the studies included in individual reviews may overlap, results of reviews cannot be pooled across reviews and meta-analyses (included studies are not all independent units, and individual studies may be included in more than one review). In addition, different reviews use different summary measures, such as weighted mean differences, odds ratios, or relative risks to summarize treatment effects; individual reviews focused on a variety of different condition-specific continuous or categorical outcome measures (e.g., treatment response, Beck Depression Inventory, Hamilton Depression Rating