Peer review and journal impact factor: the two pillars of contemporary medical publishing

Hippokratia 2010; 14 (Suppl 1): 5-12

S. Triaridis, A. Kyrgidis

Abstract

The appraisal of scientific quality is a particularly difficult problem. Editorial boards resort to secondary criteria including crude publication counts, journal prestige, the reputation of authors and institutions, and estimated importance and relevance of the research field, making peer review a controversial rather than a rigorous process. On this background different methods for evaluating research may become required, including citation rates and journal impact factors (IF), which are thought to be more quantitative and objective indicators, directly related to published science. The aim of this review is to go into the two pillars of contemporary medical publishing, that is the peer review process and the IF. Qualified experts??? reviewing the publications appears to be the only way for the evaluation of medical publication quality. To improve and standardise the principles, procedures and criteria used in peer review evaluation is of great importance. Standardizing and improving training techniques for peer reviewers, would allow for the magnification of a journal???s impact factor. This may be a very important reason that impact factor and peer review need to be analyzed simultaneously. Improving a journal???s IF would be difficult without improving peer-review efficiency. Peer-reviewers need to understand the fundamental principles of contemporary medical publishing, that is peer-review and impact factors. The current supplement of the Hippokratia for supporting its seminar for reviewers will help to fulfil some of these scopes.

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Methods and Biostatistics: a concise guide for peer reviewers

Hippokratia 2010; 14 (Suppl 1): 13-22

A. Kyrgidis, S. Triaridis

Abstract

The purpose of the Materials and Methods section of a scientific manuscript is to provide information in sufficient detail, so that another scientist working in the same field of endeavor is able to repeat the experiments and reproduce the results. Authors are entitled to a justified decision on the publication or not of their work. Thus, reviewers need to assure the authors that they have studied, correctly interpreted and fairly judged their work. This can be done by writing a short introductory paragraph in their critique, mentioning the type of study, the subjects recruited, the time and places the study was conducted, the interventions, the outcome measures and the statistical tests. All these information should be found in the methods section. If the reviewer cannot find these information, he needs not to read the whole article. Reading through the abstract and the methods section, he can reject the article on good grounds. If the methods section is appropriate, then the whole article need to be further reviewed. In this manuscript we shall discuss several critical aspects of the methods and statistics from the reviewer's perspective to provide reviewers the knowledge basis to write the aforementioned introductory paragraph of their critique.

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Introduction to Multivariate Regression Analysis

Hippokratia 2010; 14 (Suppl 1): 23-28

EC. Alexopoulos

Abstract

Statistics are used in medicine for data description and inference. Inferential statistics are used to answer questions about the data, to test hypotheses (formulating the lternative or null hypotheses), to generate a measure of effect, typically a ratio of rates or risks, to describe associations (correlations) or to model relationships (regression) within the data and, in many other functions. Usually point estimates are the measures of associations or of the magnitude of effects. Confounding, measurement errors, selection bias and random errors make unlikely the point estimates to equal the true ones. In the estimation process, the random error is not avoidable. One way to account for is to compute p-values for a range of possible parameter values (including the null). The range of values, for which the p-value exceeds a specified alpha level (typically 0.05) is called confidence interval. An interval estimation procedure will, in 95% of repetitions (identical studies in all respects except for random error), produce limits that contain the true parameters. It is argued that the question if the pair of limits produced from a study contains the true parameter could not be answered by the ordinary (frequentist) theory of confidence intervals. Frequentist approaches derive estimates by using probabilities of data (either p-values or likelihoods) as measures of compatibility between data and hypotheses, or as measures of the relative support that data provide hypotheses. Another approach, the Bayesian, uses data to improve existing (prior) estimates in light of new data. Proper use of any approach requires careful interpretation of statistics .

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Meta-analysis in medical research

Hippokratia 2010; 14 (Suppl 1): 29-37

AB. Haidich

Abstract

The objectives of this paper are to provide an introduction to meta-analysis and to discuss the rationale for this type of research and other general considerations. Methods used to produce a rigorous meta-analysis are highlighted and some aspects of presentation and interpretation of meta-analysis are discussed. Meta-analysis is a quantitative, formal, epidemiological study design used to systematically assess previous research studies to derive conclusions about that body of research. Outcomes from a meta-analysis may include a more precise estimate of the effect of treatment or risk factor for disease, or other outcomes, than any individual study contributing to the pooled analysis. The examination of variability or heterogeneity in study results is also a critical outcome. The benefits of meta-analysis include a consolidated and quantitative review of a large, and often complex, sometimes apparently conflicting, body of literature. The specification of the outcome and hypotheses that are tested is critical to the conduct of meta-analyses, as is a sensitive literature search. A failure to identify the majority of existing studies can lead to erroneous conclusions; however, there are methods of examining data to identify the potential for studies to be missing; for example, by the use of funnel plots. Rigorously conducted meta-analyses are useful tools in evidence-based medicine. The need to integrate findings from many studies ensures that meta-analytic research is desirable and the large body of research now generated makes the conduct of this research feasible.

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Revisiting Information Technology tools serving authorship and editorship: a case-guided tutorial to statistical analysis and plagiarism detection

Hippokratia 2010; 14 (Suppl 1): 38-48

Pd. Bamidis, C. Lithari, St. Konstantinidis

Abstract
With the number of scientific papers published in journals, conference proceedings, and international literature ever increasing, authors and reviewers are not only facilitated with an abundance of information, but unfortunately continuously confronted with risks associated with the erroneous copy of another???s material. In parallel, Information Communication Technology (ICT) tools provide to researchers novel and continuously more effective ways to analyze and present their work. Software tools regarding statistical analysis offer scientists the chance to validate their work and enhance the quality of published papers. Moreover, from the reviewers and the editor???s perspective, it is now possible to ensure the (text-content) originality of a scientific article with automated software tools for plagiarism detection. In this paper, we provide a step-bystep demonstration of two categories of tools, namely, statistical analysis and plagiarism detection. The aim is not to come up with a specific tool recommendation, but rather to provide useful guidelines on the proper use and efficiency of either category of tools. In the context of this special issue, this paper offers a useful tutorial to specific problems concerned with scientific writing and review discourse. A specific neuroscience experimental case example is utilized to illustrate the young researcher???s statistical analysis burden, while a test scenario is purpose-built using open access journal articles to exemplify the use and comparative outputs of seven plagiarism detection software pieces.

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