Author: Pan Zhenglun
Position: Attending doctor, MD
Institution: Rheumatology department,Shandong provincial hospital,China,Jinan,250021.
E-mail: panzhenglun@hotmail.com
Additional Authors: Jin Gao
Submitted Date: June 24, 2006
Published Date: June 26, 2006
This comment was originally posted as a “Reader Response” on the publication date indicated above. All Reader Responses are now available as comments.

We read with great interest your editorial "The Impact Factor Game". We noticed that many of the journals indexed by SCI pay considerable attention to impact factor and declare their figure on their journal's website. We believe the game has become a most inflential one in today's scientific evalution system. For example, some of China's universities have adopted it as an core factor in the evaluation of the quality of research articles and recomend that students who are persuing a doctorate must publish at least one so-called "SCI-indexed paper".

In total, 6090 journals are indexed by SCI, most of which are published in English. However there are many more scientific journals in the world. Over 6300 local scientific journals are published here in China, but Chinese journals are rare in the SCI database and most of them have no impact factor.

Some may argue that SCI database only includes the high-quality journals, but this is not necessarily the case. As a paper published in PLoS Medicine (1) has shown, "PubMed-indexed Chinese studies did worse than Chinese studies not indexed in PubMed in defining disease with specific criteria (17/20 [85%] versus 137/141 [97%], respectively; exact p = 0.042), and in ascertaining the eligibility of controls (13/20 [65%] versus 129/141 [92%], respectively". The quality of an article is not determined by its language of publication.

Language accounts for much in today's database, especially when we are searching it for evidence. Language bias should not be negelected. A language revolution could contribute to scientific progress.

Reference

1. Pan Z, Trikalinos TA, Kavvoura FK, Lau J, Ioannidis JP (2005) Local Literature Bias in Genetic Epidemiology: An Empirical Evaluation of the Chinese Literature. PLoS Med 2(12): e334. [http://medicine.plosjourn...]