Although systematic reviews are considered the primary means for generating cumulative knowledge and their results are often used to inform evidence-based practice, the robustness of their meta-analytic summary estimates is rarely investigated. Consequently, the results of published systematic reviews and, by extension, our cumulative knowledge have come under scrutiny. Using a comprehensive approach to sensitivity analysis, we examined the impact of outliers and publication bias, as well as their combined effect, on meta-analytic results on employee turnover. Our analysis of 205 distributions from seven recently published meta-analyses revealed that meta-analytic results on turnover are often affected by publication bias and, less frequently, outliers. Moreover, we observed that 33% of the recommendations for practice provided in the original systematic reviews on turnover were not robust to outliers and/or publication bias, which, if implemented by practitioners, could yield unexpected consequences and, thus, widen the science-practice gap. We argue that practitioners should be skeptical about implementing practices recommended by meta-analytic studies that do not include sensitivity analyses. To improve sensitivity analysis reporting rates and, thus, the transparency of meta-analytic findings and recommendations for practice, we introduce an open-access software (metasen.shinyapps.io/gen1/) that conducts all analyses performed in the current study. We provide guidelines and recommendations for future turnover studies and sensitivity analyses in the meta-analytic context.

尽管系统评价被认为是产生累积知识的主要手段，其结果通常用于为循证实践提供信息，但很少研究其荟萃分析总结估计的稳健性。因此，公开发表的系统评价的结果以及扩展的我们的累积知识都受到了审查。使用全面的敏感性分析方法，我们研究了异常值和发布偏倚的影响以及它们对员工流动率的荟萃分析结果的综合影响。我们对7个最近发表的荟萃分析对205个分布的分析表明，关于营业额的荟萃分析结果通常受出版偏见的影响，而离群值则较少见。而且，我们观察到，原始的系统性营业额评论中提供的33％的实践建议对异常值和/或出版偏倚并不稳健，如果由从业人员实施，可能会产生意想不到的后果，从而扩大科学与实践之间的差距。我们认为，从业者应该对不包括敏感性分析的荟萃分析研究所建议的实施做法持怀疑态度。为了提高敏感性分析的报告率，从而提高荟萃分析的结果和实践建议的透明度，我们引入了一种开放式访问软件（metasen.shinyapps.io/gen1/），该软件可以进行当前研究中进行的所有分析。我们为荟萃分析中的未来营业额研究和敏感性分析提供指导和建议。