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\textbf{Heterogeneity Evaluation Practices}  Fifty percent (91/182) of all meta-analyses used at least one heterogeneity test (Table 1). The most widely reported statistic was I2 (41.21\%; 75/182) followed by X2 (24.18\%; 44/182). In combination, X2 and I2 (13.19\%; 24/182) were reported with greatest frequency followed by Q and I2 (12.64\%; 23/182). Authors selected a random effects model most frequently (25\%; 46/182), followed by use of both fixed and random-effect models (21\%; 39/182). Fixed effects models were reported in 4\% (8/182) of studies and a mixed effects model was used in only one study. The remaining 50\% (90/182) did not report the type of model used for analysis. Twenty-four percent (43/182) used the random-effects model without considering the results of a heterogeneity test to confirm the need for such an analysis; fifteen percent (27/182) changed from the fixed to random effects based on results of a heterogeneity test.The level of statistical significance for heterogeneity tests was reported in some  systematic reviews. The most frequently reported p-value was p < .05 (16\%, 29/182) followed by p< .01 (\%), p < .10 (\%), and p < .2 used in only one study. A forest plot was the most common heterogeneity plot (42\%, 76/182). Only 2\% (3/182) used a L’Abbé to graphically represent heterogeneity. Forty-three percent (78/182) of systematic reviews contained heterogeneity plots published as figures in the article. The significance level most used was a 5\% p-value with a 16\% (29/182) occurrence and 0.1\%, 1\%, 10\% p-values as the least frequently used with 0.5\% (1/182), 0.5\% (1/182), and 8\% (14/182) occurrences respectively. A forest plot was the most used heterogeneity plot with 42\% (76/182) while 2\% (3/182) utilized a L’Abbé to graphically represent heterogeneity. Out of the manuscripts which created a heterogeneity plot 43\% (78/182) actually presented them. Of the three tests designed to investigate heterogeneity (Subgroup, Meta-regression, and Sensitivity Analyses), Subgroup analysis was used the most 21\% (39/182), Sensitivity analysis was second 18\% (33/182), and Meta-regression was used the least 9\% (17/182) (Table 1). It was found that 20\% (36/182) of the available manuscripts wrote about heterogeneity, but never actually calculated it. 58\% (105/182) of manuscripts did not find significant heterogeneity, 3\% (5/182) found enough evidence of heterogeneity to disregard “some” of the meta-analysis, 4\% (8/182) found significant heterogeneity, and 35\% (64/182) did not know whether or not there was too much heterogeneity present to perform a meta-analysis.  
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