Correction: Trend analysis of journal metrics: a new academic library service?
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PROVIDER: S-EPMC5764591 | biostudies-other | 2018 Jan
REPOSITORIES: biostudies-other
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Correction: Trend analysis of journal metrics: a new academic library service?
Journal of the Medical Library Association : JMLA 20180102 1
[This corrects the article on p. 240 in vol. 105, PMID: 28670211.]. ...[more]
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Project description:BackgroundQuantitative survey of research articles, as an application of bibliometrics, is an effective tool for grasping overall trends in various medical research fields. This type of survey has been also applied to infectious disease research; however, previous studies were insufficient as they underestimated articles published in non-English or regional journals.MethodsUsing a combination of Scopus and PubMed, the databases of scientific literature, and English and non-English keywords directly linked to infectious disease control, we identified international and regional infectious disease journals. In order to ascertain whether the newly selected journals were appropriate to survey a wide range of research articles, we compared the number of original articles and reviews registered in the selected journals to those in the 'Infectious Disease Category' of the Science Citation Index Expanded (SCI Infectious Disease Category) during 1998-2006. Subsequently, we applied the newly selected journals to survey the number of original articles and reviews originating from 11 Asian countries during the same period.ResultsOne hundred journals, written in English or 7 non-English languages, were newly selected as infectious disease journals. The journals published 14,156 original articles and reviews of Asian origin and 118,158 throughout the world, more than those registered in the SCI Infectious Disease Category (4,621 of Asian origin and 66,518 of the world in the category). In Asian trend analysis of the 100 journals, Japan had the highest percentage of original articles and reviews in the area, and no noticeable increase in articles was revealed during the study period. China, India and Taiwan had relatively large numbers and a high increase rate of original articles among Asian countries. When adjusting the publication of original articles according to the country population and the gross domestic product (GDP), Singapore and Taiwan were the most productive.ConclusionA survey of 100 selected journals is more sensitive than the SCI Infectious Disease Category from the viewpoint of avoiding underestimating the number of infectious disease research articles of Asian origin. The survey method is applicable to grasp global trends in disease research, although the method may require further development.
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Project description:BackgroundSARS-CoV-2, the virus that caused the global COVID-19 pandemic, has severely impacted Central Asia; in spring 2020, high numbers of cases and deaths were reported in this region. The second wave of the COVID-19 pandemic is currently breaching the borders of Central Asia. Public health surveillance is necessary to inform policy and guide leaders; however, existing surveillance explains past transmissions while obscuring shifts in the pandemic, increases in infection rates, and the persistence of the transmission of COVID-19.ObjectiveThe goal of this study is to provide enhanced surveillance metrics for SARS-CoV-2 transmission that account for weekly shifts in the pandemic, including speed, acceleration, jerk, and persistence, to better understand the risk of explosive growth in each country and which countries are managing the pandemic successfully.MethodsUsing a longitudinal trend analysis study design, we extracted 60 days of COVID-19-related data from public health registries. We used an empirical difference equation to measure the daily number of cases in the Central Asia region as a function of the prior number of cases, level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R.ResultsCOVID-19 transmission rates were tracked for the weeks of September 30 to October 6 and October 7-13, 2020, in Central Asia. The region averaged 11,730 new cases per day for the first week and 14,514 for the second week. Infection rates increased across the region from 4.74 per 100,000 persons to 5.66. Russia and Turkey had the highest 7-day moving averages in the region, with 9836 and 1469, respectively, for the week of October 6 and 12,501 and 1603, respectively, for the week of October 13. Russia has the fourth highest speed in the region and continues to have positive acceleration, driving the negative trend for the entire region as the largest country by population. Armenia is experiencing explosive growth of COVID-19; its infection rate of 13.73 for the week of October 6 quickly jumped to 25.19, the highest in the region, the following week. The region overall is experiencing increases in its 7-day moving average of new cases, infection, rate, and speed, with continued positive acceleration and no sign of a reversal in sight.ConclusionsThe rapidly evolving COVID-19 pandemic requires novel dynamic surveillance metrics in addition to static metrics to effectively analyze the pandemic trajectory and control spread. Policy makers need to know the magnitude of transmission rates, how quickly they are accelerating, and how previous cases are impacting current caseload due to a lag effect. These metrics applied to Central Asia suggest that the region is trending negatively, primarily due to minimal restrictions in Russia.
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Project description:This data article presents a corpus (i.e. a selection of a big number of words in an electronic form) and a concordancer (i.e. a tool to show the word in its context of use) of academic journal articles. As the title suggests, the data were collected from research articles published in academic journals. The corpus contains 5,686,428 words selected from 895 journal articles published by Elsevier in 2011-2015. The corpus is classified into four subject areas: Health sciences, Life sciences, Physical Sciences, and Social Sciences, following the classifications of Scopus, which is the largest abstract and citation database of peer-reviewed scientific journals, books and conference proceedings. To ease the access and utilization of the corpus, a program to produce the key word in context (KWIC) and word frequency was created and placed on the website: corpus.kwary.net. The corpus is a valuable resource for researchers, teachers, and translators working on academic English.
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Project description:To correct the incongruence of document types between the numerator and denominator in the traditional impact factor (IF), we make a corresponding adjustment to its formula and present five corrective IFs: IFTotal/Total, IFTotal/AREL, IFAR/AR, IFAREL/AR, and IFAREL/AREL. Based on a survey of researchers in the fields of ophthalmology and mathematics, we obtained the real impact ranking of sample journals in the minds of peer experts. The correlations between various IFs and questionnaire score were analyzed to verify their journal evaluation effects. The results show that it is scientific and reasonable to use five corrective IFs for journal evaluation for both ophthalmology and mathematics. For ophthalmology, the journal evaluation effects of the five corrective IFs are superior than those of traditional IF: the corrective effect of IFAR/AR is the best, IFAREL/AR is better than IFTotal/Total, followed by IFTotal/AREL, and IFAREL/AREL. For mathematics, the journal evaluation effect of traditional IF is superior than those of the five corrective IFs: the corrective effect of IFTotal/Total is best, IFAREL/AR is better than IFTotal/AREL and IFAREL/AREL, and the corrective effect of IFAR/AR is the worst. In conclusion, not all disciplinary journal IF need correction. The results in the current paper show that to correct the IF of ophthalmologic journals may be valuable, but it seems to be meaningless for mathematic journals.
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Project description:Using journal metrics, this paper explores whether Annals of Pediatric Endocrinology & Metabolism has internationalized 4 years after changing its language to English only.From the journal's website and the Web of Science Core Collection, the following metrics were counted or calculated: Number of citable articles, countries of authors and editorial board members, total citations, impact factor, countries of citing authors, citing journal titles, and Hirsch index.From 2012 to 2017, 208 articles were citable. The authors had affiliations in 7 countries and the editorial board members in 14 countries. From 2014 to 2017, the total citations each year were 8, 81, 141, and 61; and the impact factors from 2014 to 2016 were calculated as 0.05, 0.987, and 1.165. The citing authors were from 60 countries, among which the United States, China, South Korea, Italy, and Germany were most common. The journal was cited by 215 journal titles. The Hirsch index was 7.These journal metrics showed that the journal achieved international status 4 years after changing the journals' language into English only. The journal's language policy successfully enabled the journal to rebrand as an international journal.
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Project description:We analyzed how often and in what ways the Journal Impact Factor (JIF) is currently used in review, promotion, and tenure (RPT) documents of a representative sample of universities from the United States and Canada. 40% of research-intensive institutions and 18% of master's institutions mentioned the JIF, or closely related terms. Of the institutions that mentioned the JIF, 87% supported its use in at least one of their RPT documents, 13% expressed caution about its use, and none heavily criticized it or prohibited its use. Furthermore, 63% of institutions that mentioned the JIF associated the metric with quality, 40% with impact, importance, or significance, and 20% with prestige, reputation, or status. We conclude that use of the JIF is encouraged in RPT evaluations, especially at research-intensive universities, and that there is work to be done to avoid the potential misuse of metrics like the JIF.
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