全球卫生社会科学研究的同行评议:从给《柳叶刀》的信函看

V. Fan, Rachel Silverman, D. Roodman, W. Savedoff
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引用次数: 0

摘要

近年来,全球卫生的跨学科性质模糊了医学和社会科学之间的界限。由于医学期刊发表关于社会政策或宏观干预的非实验性研究文章,社会科学家批评医学期刊文章的严谨性和质量,对方法问题的频率和特征以及研究偏差和错误的普遍性和严重性提出了一般性问题,因此引起了争议。已发表的通信信件可用于确定跨学科全球卫生研究中的共同争议领域,并寻求解决这些争议的战略。在某种程度上,这些信件可以被视为对已发表文章进行公开同行评审的一种“众包”(但由编辑控制)方式,从中可以收集到一些偏见和错误的特征。2012年12月,我们使用《柳叶刀》网络版系统地识别了2008年至2012年出版的每期的相关通信。我们对这些信件中提出的共同争议领域进行总结和分类。通信信件中最常提到的五个问题是:测量误差(占论文的51%);遗漏变量和混淆因素(45%);不可信和缺乏外部效度(43%);缺失或低质量数据(32%);方法缺乏透明度(30%)。我们建议用清单和指南更好地记录潜在偏倚的领域,以促进更严格的同行评议,聘请具有计量经济学专业知识的专家作为评议人,并明确和彻底地将所有通信信件与《柳叶刀》上的原始文章联系起来。最重要的是,我们建议《柳叶刀》采用复制标准,即至少向期刊提供用于产生估计的数据和编码,以便审稿人分析和复制作者报告的估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Peer Review of Social Science Research in Global Health: A View Through Correspondence Letters to 'The Lancet'
In recent years, the interdisciplinary nature of global health has blurred the lines between medicine and social science. As medical journals publish non-experimental research articles on social policies or macro-level interventions, controversies have arisen when social scientists have criticized the rigor and quality of medical journal articles, raising general questions about the frequency and characteristics of methodological problems and the prevalence and severity of research bias and error. Published correspondence letters can be used to identify common areas of dispute within interdisciplinary global health research and seek strategies to address them. To some extent, these letters can be seen as a "crowd-sourced" (but editor-gated) approach to public peer review of published articles, from which some characteristics of bias and error can be gleaned. In December 2012, we used the online version of The Lancet to systematically identify relevant correspondence in each issue published between 2008 and 2012. We summarize and categorize common areas of dispute raised in these letters. The five concerns most frequently cited in correspondence letters are as follows: measurement error (51% of papers); omitted variables and confounding (45%); implausibility and lack of external validity (43%); missing or low-quality data (32%); and lack of transparency of methods (30%). We recommend better documentation of areas of potential bias with checklists and guidelines to facilitate more rigorous peer review, drawing on experts with econometric expertise as reviewers, and explicitly and thoroughly linking all correspondence letters to the original articles in The Lancet. Most importantly, we recommend The Lancet adopts the replication standard, whereby the data and the coding used to produce the estimates are provided at least to the journal, for reviewers to analyze and replicate the estimates reported by the authors.
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