通过范围综述、文献计量学和替代性影响力指标丰富元分析：可视化研究特征、隐性偏倚风险、社会影响与研究转化
Enriching meta-analyses through scoping review, bibliometrics, and alternative impact metrics: Visualizing study characteristics, hidden risk of bias, societal influence, and research translation
AI总结：
本文提出结合范围综述、文献计量学与替代性影响力指标的框架，以可视化研究特征、隐性偏倚风险和社会影响，从而丰富元分析并促进研究转化。
摘要：
我们提出了一个由三种方法组成的框架，可用于增强元分析：1）范围综述（证据图谱），2）文献计量学，以及3）替代性影响力指标。这三种“丰富化”方法有助于对定量和定性证据以及学术和非学术影响进行综合研究。元分析产生定量洞见（例如总体估计值），而丰富化分析则提供关于证据基础的用户友好型定性信息摘要。范围综述可以可视化研究特征，揭示知识空白和方法学差异。文献计量分析提供对非独立证据的视觉化评估，例如超主导作者和国家以及资金来源，可能为偏倚风险提供信息。影响力指标分析采用替代性指标来衡量元分析中研究的社会影响和研究转化（例如政策和专利引用）。为说明该框架的应用，我们提供了示例可视化和R代码。
英文摘要：
We present a framework consisting of three approaches that can enhance meta-analyses: 1) scoping reviews (evidence map), 2) bibliometrics, and 3) alternative impact metrics. These three "enrichment" approaches facilitate the research synthesis of both quantitative and qualitative evidence, along with academic and non-academic influences. While the meta-analysis yields quantitative insights (e.g., overall estimates), the enrichment analyses provide user-friendly summaries of qualitative information on the evidence base. Scoping reviews can visualize study characteristics, unravelling knowledge gaps and methodological differences. Bibliometric analysis offers a visual assessment of the non-independent evidence, such as hyper-dominant authors and countries, and funding sources, potentially informing the risk of bias. Impact metric analysis employs alternative metrics to gauge societal influence and research translation (e.g., policy and patent citations) of studies in the meta-analysis. To illustrate the application of this framework, we provide sample visualizations and R code.
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