Birko Stanislav, Dove Edward S, Özdemir Vural
Centre of Genomics and Policy, Department of Human Genetics, Faculty of Medicine, McGill University, Montreal, QC, Canada.
J. Kenyon Mason Institute for Medicine, Life Sciences and the Law, University of Edinburgh School of Law, Edinburgh, United Kingdom.
PLoS One. 2015 Aug 13;10(8):e0135162. doi: 10.1371/journal.pone.0135162. eCollection 2015.
The extent of consensus (or the lack thereof) among experts in emerging fields of innovation can serve as antecedents of scientific, societal, investor and stakeholder synergy or conflict. Naturally, how we measure consensus is of great importance to science and technology strategic foresight. The Delphi methodology is a widely used anonymous survey technique to evaluate consensus among a panel of experts. Surprisingly, there is little guidance on how indices of consensus can be influenced by parameters of the Delphi survey itself. We simulated a classic three-round Delphi survey building on the concept of clustered consensus/dissensus. We evaluated three study characteristics that are pertinent for design of Delphi foresight research: (1) the number of survey questions, (2) the sample size, and (3) the extent to which experts conform to group opinion (the Group Conformity Index) in a Delphi study. Their impacts on the following nine Delphi consensus indices were then examined in 1000 simulations: Clustered Mode, Clustered Pairwise Agreement, Conger's Kappa, De Moivre index, Extremities Version of the Clustered Pairwise Agreement, Fleiss' Kappa, Mode, the Interquartile Range and Pairwise Agreement. The dependency of a consensus index on the Delphi survey characteristics was expressed from 0.000 (no dependency) to 1.000 (full dependency). The number of questions (range: 6 to 40) in a survey did not have a notable impact whereby the dependency values remained below 0.030. The variation in sample size (range: 6 to 50) displayed the top three impacts for the Interquartile Range, the Clustered Mode and the Mode (dependency = 0.396, 0.130, 0.116, respectively). The Group Conformity Index, a construct akin to measuring stubbornness/flexibility of experts' opinions, greatly impacted all nine Delphi consensus indices (dependency = 0.200 to 0.504), except the Extremity CPWA and the Interquartile Range that were impacted only beyond the first decimal point (dependency = 0.087 and 0.083, respectively). Scholars in technology design, foresight research and future(s) studies might consider these new findings in strategic planning of Delphi studies, for example, in rational choice of consensus indices and sample size, or accounting for confounding factors such as experts' variable degrees of conformity (stubbornness/flexibility) in modifying their opinions.
新兴创新领域专家之间的共识程度(或缺乏共识的程度)可作为科学、社会、投资者和利益相关者协同或冲突的先决条件。自然地,我们如何衡量共识对科技战略预见至关重要。德尔菲法是一种广泛使用的匿名调查技术,用于评估专家小组之间的共识。令人惊讶的是,关于德尔菲调查本身的参数如何影响共识指数,几乎没有相关指导。我们基于聚类共识/分歧的概念模拟了经典的三轮德尔菲调查。我们评估了与德尔菲预见研究设计相关的三个研究特征:(1)调查问题的数量,(2)样本量,以及(3)在德尔菲研究中专家符合群体意见的程度(群体一致性指数)。然后在1000次模拟中检验了它们对以下九个德尔菲共识指数的影响:聚类众数、聚类成对一致性、康格卡方、德莫弗指数、聚类成对一致性的极值版本、弗莱斯卡方、众数、四分位距和成对一致性。共识指数对德尔菲调查特征的依赖性从0.000(无依赖性)到1.000(完全依赖性)表示。调查中问题的数量(范围:6至40)没有显著影响,依赖性值保持在0.030以下。样本量的变化(范围:6至50)对四分位距、聚类众数和众数显示出前三大影响(依赖性分别为0.396、0.130、0.116)。群体一致性指数,一种类似于衡量专家意见固执/灵活性的结构,对所有九个德尔菲共识指数都有很大影响(依赖性为0.200至0.504),除了极值CPWA和四分位距仅在小数点后第一位受到影响(依赖性分别为0.087和0.083)。技术设计、预见研究和未来研究领域的学者在德尔菲研究的战略规划中可能会考虑这些新发现,例如,在合理选择共识指数和样本量时,或在考虑诸如专家在修改意见时不同程度的一致性(固执/灵活性)等混杂因素时。