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Abstract

There is currently a paucity of evidence-based strategies that have been shown to increase citations of peer-reviewed articles following their publication. We conducted a 12-month randomized controlled trial to examine whether the promotion of article links in an online cross-publisher distribution platform (TrendMD) affects citations. In all, 3,200 articles published in 64 peer-reviewed journals across eight subject areas were block randomized at the subject level to either the TrendMD group (n = 1,600) or the control group (n = 1,600) of the study. Our primary outcome compares the mean citations of articles randomized to TrendMD versus control after 12 months. Articles randomized to TrendMD showed a 50% increase in mean citations relative to control at 12 months. The difference in mean citations at 12 months for articles randomized to TrendMD versus control was 5.06, 95% confidence interval [2.87, 7.25], was statistically significant (p?<?.001) and found in three of eight subject areas. At 6 months following publication, articles randomized to TrendMD showed a smaller, yet statistically significant (p = .005), 21% increase in mean citations, relative to control. To our knowledge, this is the first randomized controlled trial to demonstrate how an intervention can be used to increase citations of peer-reviewed articles after they have been published.

Date

12. 9.2020 20:40:33

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Abstract

In recent years there has been an explosion of biological data stored in large central databases, tools to handle the data, and educational programs to train scientists in using bioinformatics resources. Still, the diffusion of bioinformatics within the biological cornmunity has yet to be extensively studied. In this study, the diffusion of two bioinformatics-related practices-using genomic databases and analyzing DNA and protein sequences-was investigated by analyzing MEDLINE records of 12 journals, representing various fields of biology. The diffusion of these practices between 1970 and 2003 follows an S-shaped curve typical of many innovations, beginning with slow growth, followed by a period of rapid linear growth, and finally reaching saturation. Similar diffusion patterns were found for both the use of genomic databases and biological sequence analysis, indicating the strong relationship between these practices. This study presents the surge in the use of genomic databases and analysis of biological sequences and proposes that these practices are fully diffused within the biological community. Extrapolating from these results, it suggests that taking a diffusion of innovations approach may be useful for researchers as well as for providers of bioinformatics applications and support services.