Dataset Information

A Metric for Evaluating a Transformation of Subscription-Based Journals into Open-Access Journals.

ABSTRACT: Open Access is an upcoming paradigm to communicate scientific knowledge. The Trans-O-MIM Project works on strategies, models, and evaluation metrics for the goal-oriented, stepwise, sustainable, and fair transformation of established subscription-based scientific journals into open-access-based journals. This research intends to present an evaluation metric and the associated identified appropriate parameters for such transformations. To develop the evaluation metric, it has been implemented in the context of a business management method for planning, steering and controlling action and corporate strategies. The central element was a 3-step procedure for developing the metric. In stage 1 necessary preconditions for a transformation were considered. Stage 2 is the actual elaboration of the evaluation metric by means of a scenario analysis and stage 3 comprises the exemplary testing at the journal Methods of Information in Medicine. The three methodological steps have primarily resulted in 5 scenarios with 9 different final states from the scenario analysis. Thus, the metric is now composed of these 5 scenarios, which can be used to evaluate the success or failure of a transformation. A list of 65 suitable parameters to measure changes in scenario were compiled. So, it is possible to evaluate the transformation and to find the current final state. Parameters like submissions, publications, and time as well as the scenario states could be applied to the transformation process of the Methods of Information in Medicine journal. The proposed evaluation metric can be used to evaluate the transformation processes of subscription-based journals into open-access-based journals.

SUBMITTER: Mielke C

PROVIDER: S-EPMC7538413 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Metric for Evaluating a Transformation of Subscription-Based Journals into Open-Access Journals.

Mielke Corinna C Kuballa Stefanie S Schulze Mareike M Haux Reinhold R

Journal of medical systems 20201006 11

Open Access is an upcoming paradigm to communicate scientific knowledge. The Trans-O-MIM Project works on strategies, models, and evaluation metrics for the goal-oriented, stepwise, sustainable, and fair transformation of established subscription-based scientific journals into open-access-based journals. This research intends to present an evaluation metric and the associated identified appropriate parameters for such transformations. To develop the evaluation metric, it has been implemented in ...[more]

PMID: 33025300

Similar Datasets

Project description:IntroductionAlong with the proliferation of Open Access (OA) publishing, the interest for comparing the scientific quality of studies published in OA journals versus subscription journals has also increased. With our study we aimed to compare the methodological quality and the quality of reporting of primary epidemiological studies and systematic reviews and meta-analyses published in OA and non-OA journals.MethodsIn order to identify the studies to appraise, we listed all OA and non-OA journals which published in 2013 at least one primary epidemiologic study (case-control or cohort study design), and at least one systematic review or meta-analysis in the field of oncology. For the appraisal, we picked up the first studies published in 2013 with case-control or cohort study design from OA journals (Group A; n = 12), and in the same time period from non-OA journals (Group B; n = 26); the first systematic reviews and meta-analyses published in 2013 from OA journals (Group C; n = 15), and in the same time period from non-OA journals (Group D; n = 32). We evaluated the methodological quality of studies by assessing the compliance of case-control and cohort studies to Newcastle and Ottawa Scale (NOS) scale, and the compliance of systematic reviews and meta-analyses to Assessment of Multiple Systematic Reviews (AMSTAR) scale. The quality of reporting was assessed considering the adherence of case-control and cohort studies to STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) checklist, and the adherence of systematic reviews and meta-analyses to Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) checklist.ResultsAmong case-control and cohort studies published in OA and non-OA journals, we did not observe significant differences in the median value of NOS score (Group A: 7 (IQR 7-8) versus Group B: 8 (7-9); p = 0.5) and in the adherence to STROBE checklist (Group A, 75% versus Group B, 80%; p = 0.1). The results did not change after adjustment for impact factor. The compliance with AMSTAR and adherence to PRISMA checklist were comparable between systematic reviews and meta-analyses published in OA and non-OA journals (Group C, 46.0% versus Group D, 55.0%; p = 0.06), (Group C, 72.0% versus Group D, 76.0%; p = 0.1), respectively).ConclusionThe epidemiological studies published in OA journals in the field of oncology approach the same methodological quality and quality of reporting as studies published in non-OA journals.

Project description:In this paper we present the first comprehensive bibliometric analysis of eleven open-access mega-journals (OAMJs). OAMJs are a relatively recent phenomenon, and have been characterised as having four key characteristics: large size; broad disciplinary scope; a Gold-OA business model; and a peer-review policy that seeks to determine only the scientific soundness of the research rather than evaluate the novelty or significance of the work. Our investigation focuses on four key modes of analysis: journal outputs (the number of articles published and changes in output over time); OAMJ author characteristics (nationalities and institutional affiliations); subject areas (the disciplinary scope of OAMJs, and variations in sub-disciplinary output); and citation profiles (the citation distributions of each OAMJ, and the impact of citing journals). We found that while the total output of the eleven mega-journals grew by 14.9% between 2014 and 2015, this growth is largely attributable to the increased output of Scientific Reports and Medicine. We also found substantial variation in the geographical distribution of authors. Several journals have a relatively high proportion of Chinese authors, and we suggest this may be linked to these journals' high Journal Impact Factors (JIFs). The mega-journals were also found to vary in subject scope, with several journals publishing disproportionately high numbers of articles in certain sub-disciplines. Our citation analsysis offers support for Björk & Catani's suggestion that OAMJs's citation distributions can be similar to those of traditional journals, while noting considerable variation in citation rates across the eleven titles. We conclude that while the OAMJ term is useful as a means of grouping journals which share a set of key characteristics, there is no such thing as a "typical" mega-journal, and we suggest several areas for additional research that might help us better understand the current and future role of OAMJs in scholarly communication.

Project description:Background. Open access (OA) journals allows access to research papers free of charge to the reader. Traditionally, biomedical researchers use databases like MEDLINE and EMBASE to discover new advances. However, biomedical OA journals might not fulfill such databases' criteria, hindering dissemination. The Directory of Open Access Journals (DOAJ) is a database exclusively listing OA journals. The aim of this study was to investigate DOAJ's coverage of biomedical OA journals compared with the conventional biomedical databases. Methods. Information on all journals listed in four conventional biomedical databases (MEDLINE, PubMed Central, EMBASE and SCOPUS) and DOAJ were gathered. Journals were included if they were (1) actively publishing, (2) full OA, (3) prospectively indexed in one or more database, and (4) of biomedical subject. Impact factor and journal language were also collected. DOAJ was compared with conventional databases regarding the proportion of journals covered, along with their impact factor and publishing language. The proportion of journals with articles indexed by DOAJ was determined. Results. In total, 3,236 biomedical OA journals were included in the study. Of the included journals, 86.7% were listed in DOAJ. Combined, the conventional biomedical databases listed 75.0% of the journals; 18.7% in MEDLINE; 36.5% in PubMed Central; 51.5% in SCOPUS and 50.6% in EMBASE. Of the journals in DOAJ, 88.7% published in English and 20.6% had received impact factor for 2012 compared with 93.5% and 26.0%, respectively, for journals in the conventional biomedical databases. A subset of 51.1% and 48.5% of the journals in DOAJ had articles indexed from 2012 and 2013, respectively. Of journals exclusively listed in DOAJ, one journal had received an impact factor for 2012, and 59.6% of the journals had no content from 2013 indexed in DOAJ. Conclusions. DOAJ is the most complete registry of biomedical OA journals compared with five conventional biomedical databases. However, DOAJ only indexes articles for half of the biomedical journals listed, making it an incomplete source for biomedical research papers in general.

Project description:Citation is one of the important metrics that are used in measuring the relevance and the impact of research publications. The potentials of citation analytics may be exploited to understand the gains of publishing scholarly peer-reviewed research outputs in either Open Access (OA) sources or Subscription-Based (SB) sources in the bid to increase citation impact. However, relevant data required for such comparative analysis must be freely accessible for evidence-based findings and conclusions. In this data article, citation scores (CiteScores) of 2542 OA sources and 15,040 SB sources indexed in Scopus from 2014 to 2016 were presented and analyzed based on a set of five inclusion criteria. A robust dataset, which contains the CiteScores of OA and SB publication sources included, is attached as supplementary material to this data article to facilitate further reuse. Descriptive statistics and frequency distributions of OA CiteScores and SB CiteScores are presented in tables. Boxplot representations and scatter plots are provided to show the statistical distributions of OA CiteScores and SB CiteScores across the three sub-categories (Book Series, Journal, and Trade Journal). Correlation coefficient and p-value matrices are made available within the data article. In addition, Probability Density Functions (PDFs) and Cumulative Distribution Functions (CDFs) of OA CiteScores and SB CiteScores are computed and the results are presented using tables and graphs. Furthermore, Analysis of Variance (ANOVA) and multiple comparison post-hoc tests are conducted to understand the statistical difference (and its significance, if any) in the citation impact of OA publication sources and SB publication source based on CiteScore. In the long run, the data provided in this article will help policy makers and researchers in Higher Education Institutions (HEIs) to identify the appropriate publication source type and category for dissemination of scholarly research findings with maximum citation impact.

Project description:ImportanceHepatitis C virus (HCV) can be cured with direct-acting antiviral medications, but state Medicaid programs often restrict access to these lifesaving medications owing to their high costs. Subscription-based payment models (SBPMs), wherein states contract with a single manufacturer to supply prescriptions at a reduced price, may offer a solution that increases access. Whether SBPMs are associated with changes in HCV medication use is unknown.ObjectiveTo estimate changes in Medicaid-covered HCV prescription fills after Louisiana and Washington implemented SBPMs on July 1, 2019.Design setting and participantsThis cross-sectional study examined trends in prescription fills of Medicaid-covered direct-acting antiviral HCV medications in Louisiana and Washington after implementation of SBPMs. A synthetic control approach was used to compare changes in HCV prescription fills between states that did and did not implement SBPMs. The unit of analysis was state-quarter. Outpatient direct-acting antiviral HCV prescription fills from the Medicaid State Drug Utilization Data files were obtained from all 50 US states and the District of Columbia from January 1, 2017, to June 30, 2020.ExposuresImplementation of SBPMs for Medicaid-covered direct-acting antiviral HCV medications.Main outcomes and measuresDirect-acting antiviral HCV prescriptions filled per 100 000 Medicaid enrollees.ResultsIn the year preceding SBPM implementation, the mean (SD) rate of quarterly HCV prescription fills per 100 000 Medicaid enrollees was 43.1 (8.6) prescriptions in Louisiana and 50.1 (4.1) in Washington. After SBPM implementation, the mean (SD) rate of quarterly HCV prescription fills per 100 000 enrollees was 206.0 (51.2) prescriptions in Louisiana and 53.9 (11.0) in Washington. In synthetic control models, SBPM implementation in Louisiana was associated with an increase of 173.5 (95% CI, 74.3-265.3) quarterly prescription fills per 100 000 Medicaid enrollees during the following year, a relative increase of 534.5% (95% CI, 228.7%-1125.0%). Washington did not experience a significant change in prescription fills following SBPM implementation.Conclusions and relevanceIn this cross-sectional study, Louisiana experienced substantial increases in HCV medication use among its Medicaid-enrolled population following SBPM implementation, whereas Washington did not. These differences may partially be explained by state-level variation in SBPM implementation, historical restrictions on access to HCV medications, and responses to the COVID-19 pandemic.

Dataset Information

A Metric for Evaluating a Transformation of Subscription-Based Journals into Open-Access Journals.

Publications

A Metric for Evaluating a Transformation of Subscription-Based Journals into Open-Access Journals.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets