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Rising publication delays inflate journal impact factors.

ABSTRACT: Journal impact factors have become an important criterion to judge the quality of scientific publications over the years, influencing the evaluation of institutions and individual researchers worldwide. However, they are also subject to a number of criticisms. Here we point out that the calculation of a journal's impact factor is mainly based on the date of publication of its articles in print form, despite the fact that most journals now make their articles available online before that date. We analyze 61 neuroscience journals and show that delays between online and print publication of articles increased steadily over the last decade. Importantly, such a practice varies widely among journals, as some of them have no delays, while for others this period is longer than a year. Using a modified impact factor based on online rather than print publication dates, we demonstrate that online-to-print delays can artificially raise a journal's impact factor, and that this inflation is greater for longer publication lags. We also show that correcting the effect of publication delay on impact factors changes journal rankings based on this metric. We thus suggest that indexing of articles in citation databases and calculation of citation metrics should be based on the date of an article's online appearance, rather than on that of its publication in print.

SUBMITTER: Tort AB

PROVIDER: S-EPMC3534064 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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Rising publication delays inflate journal impact factors.

Tort Adriano B L AB Targino Zé H ZH Amaral Olavo B OB

PloS one 20121231 12

Journal impact factors have become an important criterion to judge the quality of scientific publications over the years, influencing the evaluation of institutions and individual researchers worldwide. However, they are also subject to a number of criticisms. Here we point out that the calculation of a journal's impact factor is mainly based on the date of publication of its articles in print form, despite the fact that most journals now make their articles available online before that date. We ...[more]

PMID: 23300920

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Project description:BackgroundSystematic reviews are important for informing clinical practice and health policy. The aim of this study was to examine the bibliometrics of systematic reviews and to determine the amount of variance in citations predicted by the journal impact factor (JIF) alone and combined with several other characteristics.MethodsWe conducted a bibliometric analysis of 1,261 systematic reviews published in 2008 and the citations to them in the Scopus database from 2008 to June 2012. Potential predictors of the citation impact of the reviews were examined using descriptive, univariate and multiple regression analysis.ResultsThe mean number of citations per review over four years was 26.5 (SD ± 29.9) or 6.6 citations per review per year. The mean JIF of the journals in which the reviews were published was 4.3 (SD ± 4.2). We found that 17% of the reviews accounted for 50% of the total citations and 1.6% of the reviews were not cited. The number of authors was correlated with the number of citations (r = 0.215, P < 0.001). Higher numbers of citations were associated with the following characteristics: first author from the United States (36.5 citations), an ICD-10 chapter heading of Neoplasms (31.8 citations), type of intervention classified as Investigation, Diagnostics or Screening (34.7 citations) and having an international collaboration (32.1 citations). The JIF alone explained more than half of the variation in citations (R(2) = 0.59) in univariate analysis. Adjusting for both JIF and type of intervention increased the R2 value to 0.81. Fourteen percent of reviews published in the top quartile of JIFs (? 5.16) received citations in the bottom quartile (eight or fewer), whereas 9% of reviews published in the lowest JIF quartile (? 2.06) received citations in the top quartile (34 or more). Six percent of reviews in journals with no JIF were also in the first quartile of citations.ConclusionsThe JIF predicted over half of the variation in citations to the systematic reviews. However, the distribution of citations was markedly skewed. Some reviews in journals with low JIFs were well-cited and others in higher JIF journals received relatively few citations; hence the JIF did not accurately represent the number of citations to individual systematic reviews.

Project description:Importance:The complete and timely dissemination of clinical trial data is essential to all fields of medicine, with delayed or incomplete data release having potentially deleterious effects on both patient care and scientific inquiry. While prior analyses have noted a substantial lag in the reporting of final clinical study results, we sought to refine these observations through use of a novel starting point for the measurement of dissemination delays: the date of a corporate press release regarding a phase 3 study's results. Objective:To measure the length of time elapsed between when a sponsor had results of study findings they deemed important to announce, and when the medical community had access to them. Design and Setting:Covering the years 2011 through 2016, we measured the delay from when 8 large pharmaceutical companies issued a press release announcing completed analyses of phase 3 clinical trials in oncology, and the public sharing of those results either on ClinicalTrials.gov or in a peer-reviewed biomedical journal as found via PubMed or Google Scholar. Press releases announcing regulatory steps and presentation schedules for conferences were excluded, as were those announcing results from preclinical trials, follow-up analyses, and studies of supportive care therapies or various modes of infusion for the same therapy. Main Outcomes and Measures:Time to public dissemination of clinical trial data. Results:Of the 100 press releases in our sample, 70 (70%) reported positive results, but only 31 (31%) included the magnitude of study findings. Through the end of follow-up, 99 (99%) of press releases had an associated peer-reviewed publication, complete data posting to ClinicalTrials.gov, or both, with a median time to reporting of 300 days (95% CI, 263-348 days). Positive findings were reported more quickly than negative ones (median of 272; 95% CI, 211-318 days vs 407; 95% CI, 298-705 days; log-rank P < .001). Conclusions and Relevance:Even for the most pressing study findings, median publication delays approach 1 year. As publication delays hinder research progress and advancements in clinical care, policies that enable early preprint release or public posting of completed data analysis should be pursued.

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Rising publication delays inflate journal impact factors.

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Rising publication delays inflate journal impact factors.

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