Department of Hygiene and Epidemiology, University of Ioannina Medical School, University Campus, Ioannina 45110, Greece.
J Clin Epidemiol. 2012 Dec;65(12):1274-81. doi: 10.1016/j.jclinepi.2012.06.009. Epub 2012 Sep 6.
To examine whether perceived information gain (IG) drives the publication of randomized trials in high-impact factor (IF) journals.
We estimated IG as the Kullback-Leibler divergence, quantifying how much a new finding changes established knowledge. We used 67 meta-analyses (964 randomized trials) that include one or more trials from any of the three highest IF general medical journals (NEJM, JAMA, and Lancet). We calculated IG for the presence of a non-null effect (IG(1)) and IG for the effect size magnitude (IG(2)).
Across meta-analyses, the summary correlation coefficient of IF was 0.23 (95% confidence interval [CI]: 0.14, 0.31) for IG(1) and 0.35 (95% CI: 0.25, 0.46) for IG(2). IF also correlated with the P-value of the results (r=0.18), order of publication (r=-0.13), and number of events in the trial (r=0.36). Multivariate regression including IG, order of publication, P-value, and the number of events showed that IG is an independent correlate of IF. IG(2) explained a substantially larger proportion of the variance in IF than IG(1).
Publication in journals with high IF is driven by how extensively the results of a study change prior perceptions of the evidence, independently of the statistical significance and size of the study.
检验感知信息增益（IG）是否会促使高影响因子（IF）期刊发表随机试验。
我们将 IG 估计为 Kullback-Leibler 散度，量化新发现对既定知识的改变程度。我们使用了 67 项荟萃分析（964 项随机试验），其中包括来自三个最高 IF 一般医学期刊（新英格兰医学杂志、美国医学会杂志和柳叶刀）中的一项或多项试验。我们计算了存在非零效应（IG(1)）和效应大小幅度（IG(2)）的 IG。
在荟萃分析中，IF 的汇总相关系数为 0.23（95%置信区间：0.14，0.31），IG(1)为 0.35（95%置信区间：0.25，0.46）。IF 还与结果的 P 值（r=0.18）、发表顺序（r=-0.13）和试验中的事件数（r=0.36）相关。包括 IG、发表顺序、P 值和事件数的多元回归表明，IG 是 IF 的独立相关因素。IG(2)比 IG(1)解释了 IF 方差的更大比例。
发表在 IF 较高的期刊上的文章，主要取决于研究结果在多大程度上改变了人们对现有证据的看法，而与研究的统计学意义和规模无关。
