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文献计量分析影响引文的手稿特征:六大精神病学期刊的比较。

Bibliometric analysis of manuscript characteristics that influence citations: A comparison of six major psychiatry journals.

机构信息

Capital Medical University, No. 10 Xitoutiao, You An Men Wai, Fengtai District, Beijing, 100069, PR China.

Department of Radiology, Vancouver General Hospital, Vancouver, BC, Canada.

出版信息

J Psychiatr Res. 2019 Jan;108:90-94. doi: 10.1016/j.jpsychires.2018.07.010. Epub 2018 Jul 20.

Abstract

In this study we investigated the characteristics of psychiatry manuscript that influence its citation rate. We conducted a cross-sectional study of published articles (n = 545), from January to June 2007, from 6 major psychiatry journals with the highest 5-year impact-factor. Citation count for these articles was retrieved from Web Of Science (by Clarivate Analytics) and 22 article characteristics were tabulated manually. We then predicted the citation rate by performing univariate analysis, spearman rank-order correlation, and multiple regression model on the collected variables. Using spearman rank-order correlation, we found the following variables to have significant positive correlation with citations: abstract character count (r and p-value, 0.22 and 0.001 respectively), number of references (0.2, 0.01), abstract word count (0.17, 0.0005), number of pages (0.15, 0.003), open access (0.06, 0.05), study design reported in title (0.04, 0.0001), total number of words (0.03, 0.01) and structured abstract (0.03, 0.0009). In a multivariate linear regression model, the following variables predicted increased citation rates (p < 0.001, R = 0.38): reporting of study design in title, structured abstract and open access. Editors and authors of psychiatry journals can improve the impact of their journals and articles by utilizing this bibliometric study when assembling their manuscript.

摘要

在这项研究中,我们调查了影响精神病学文献引用率的特征。我们对 2007 年 1 月至 6 月发表在 6 种影响因子最高的精神病学期刊上的已发表文章(n=545)进行了横断面研究。这些文章的引用计数是从科睿唯安的 Web of Science 中检索到的,并且手动列出了 22 个文章特征。然后,我们通过对收集到的变量进行单变量分析、斯皮尔曼等级相关分析和多元回归模型来预测引文率。通过斯皮尔曼等级相关分析,我们发现以下变量与引文有显著正相关:摘要字符数(r 和 p 值分别为 0.22 和 0.001)、参考文献数量(0.2,0.01)、摘要字数(0.17,0.0005)、页数(0.15,0.003)、开放获取(0.06,0.05)、标题中报告的研究设计(0.04,0.0001)、总字数(0.03,0.01)和结构化摘要(0.03,0.0009)。在多元线性回归模型中,以下变量预测引文率增加(p<0.001,R=0.38):标题中报告的研究设计、结构化摘要和开放获取。精神病学期刊的编辑和作者在整理稿件时可以利用这项文献计量研究来提高其期刊和文章的影响力。

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