Exploring the Relationship Between Impact Factor and Manuscript Rejection Rates in Radiologic Journals1
Rationale and Objectives
Stratifying candidates objectively on the merit of publication portfolios is an onerous and difficult task. Institutional committees are under increasing pressure to rank applicants based on previous achievements for appointments/promotions, funding, and awards, and must do so within unforgiving time constraints. The journal impact factor (IF) has been loosely adopted in many circles for assessing article “quality,” circumventing detailed review of individual articles. The premise supporting such practice often hinges on assuming that high-IF journals are harder to publish in, for example, have higher rejection rates (RRs), and therefore, authors achieving publication in such periodicals should be “recognized” for their achievement. There is no evidence of previous research linking IF and RR.
Materials and Methods
A subset of Institute for Scientific Information (ISI)-listed radiology journals, for which IF data were available, was identified and a direct-contact survey approach (63.3% response rate) used to ascertain journal manuscript RR.
Results
Of the sample reviewed, the ISI-listed IF values ranged from 4.759 to 0.056 (mean 1.491), and editor-reported manuscript RRs from 80.0% to 8.0% (mean 47.8%). Statistical comparison of IF and RR using linear regression yielded an r 2 value of 0.223.
Conclusions
In summary, this study demonstrates poor linear agreement between IF and RR for manuscripts submitted to peer-reviewed radiology journals. This suggests that journal IF is a poor predictor of RR, and vice versa. This finding may be of interest to institutional committees who have adopted the IF as an indicator of merit in reviewing publication curriculum vitae, and may encourage rethinking of currently practiced candidate assessment approaches.
Key Words: Citation analysis , Impact factor , Manuscript rejection rate
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The authors would like to offer their sincere thanks to the respective editors of the journals who responded to our study, for their support and willingness to share this potentially-sensitive journal information with us, and also thank statistician Ms. Kylie Lange, of Flinders University (Adelaide, South Australia), for her input in the appropriate selection of statistical methods employed in the analysis of data generated in this study.
PII: S1076-6332(05)00676-8
doi:10.1016/j.acra.2005.08.016
© 2006 AUR. Published by Elsevier Inc. All rights reserved.
