k. PUTTING IT ALL TOGETHER: From this forest plot meta-analysis, utilize the information about the number of studies, heterogeneity results, CI precision, and the overall effect with its statistical significance to generate a conclusion statement about the overall effect of this intervention versus the control group on the outcome of interest. Translate the numerical values for the statistical measures into words (see the Stats tip Sheet) that peers and patients can understand. Interpret the statistical measures such as the Risk Ratio. Study or subgroup Shared decision making Usual care log[Risk Ratio] Risk Ratio Weight Risk Ratio N N (SE) IV, Random, 95% CI IV, Random, 95% CI Francis 2009 256 272-0.8 (0.421) 1.84% 0.46[0.2,1.04] Briel 2006 259 293-0.2 (0.262) 4.77% 0.86[0.51,1.44] Lgar 2012 181 178-0.7 (0.261) 4.82% 0.5[0.3,0.83] Lgar 2011 81 70-0.4 (0.204) 7.87% 0.69[0.46,1.03] Cals 2009 201 230-0.7 (0.19) 9.07% 0.5[0.35,0.73] Altiner 2007 1021 1143-0.7 (0.167) 11.79% 0.5[0.36,0.69] Little 2013 2332 1932-0.4 (0.125) 20.91% 0.69[0.54,0.88] Welschen 2004 905 818-0.5 (0.092) 38.92% 0.62[0.52,0.74] Total (95% CI) 100% 0.61[0.55,0.68] Heterogeneity: Taue=0; Chie=6.62, df=7(P=0.47); Ie=0% Test for overall effect: Z=8.63(P