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A reporting guideline can be defined as “a checklist, flow diagram, or structured text to guide authors in reporting a specific type of research, developed using explicit methodology.” A reporting guideline outlines the bare minimum of information that must be presented in a research report in order to provide a transparent and understandable explanation of what was done and what was discovered. Many reporting guidelines have been developed, and it has become important to select the most appropriate reporting guideline for a manuscript. Herein, I propose an algorithm for the selection of reporting guidelines. This algorithm was developed based on the research design classification system and the content presented for major reporting guidelines through the EQUATOR (Enhancing the Quality and Transparency of Health Research) network. This algorithm asks 10 questions: “is it a protocol,” “is it secondary research,” “is it an in vivo animal study,” “is it qualitative research,” “is it economic evaluation research,” “is it a diagnostic accuracy study or prognostic research,” “is it quality improvement research,” “is it a non-comparative study,” “is it a comparative study between groups,” and “is it an experimental study?” According to the responses, 16 appropriate reporting guidelines are suggested. Using this algorithm will make it possible to select reporting guidelines rationally and transparently.

Purpose It aimed to investigate how many retracted articles indexed in KoreaMed were cited in both the Scopus and the Korea Medical Citation Index (KoMCI) databases and to investigate whether the frequency of post-retraction citations was different according to the presence of a retraction mark. Methods Retracted articles from the KoreaMed database were collected on January 28, 2016. Scopus and KoMCI were searched for post-retraction citations, which were defined as citations 1 year after the retraction, excluding retraction-related citations. Results The 114 retracted articles were found in KoreaMed. The proportion of retracted articles in KoreaMed, the Korean medical journal database, through January 2016 was 0.04% (114/256,000). On the journal homepage, a retraction mark was present for 49 of the 114 retracted articles. Of the 114 retracted articles, 45 were cited in Scopus 176 times. Of the 176 citations, 109 (of 36 retracted articles) were post-retraction citations. The number of citations in KoMCI, except for citations of retraction notices, was 33 (of 14 retracted articles). Of those citations, the number of post-retraction citations in KoMCI was 14 (of 8 retracted articles). The presence of a retraction mark did not influence post-retraction citations (P>0.05). Post-retraction citations were frequent in the range of 1 to 3 years. Conclusion Post-retraction citations that were found in both Scopus and the KoMCI occurred frequently for retracted articles in KoreaMed. Adoption of Crossmark is recommended as one choice to prevent post-retraction citations.

Purpose This study analyzed the present status of data sharing polices and attitudes towards such policies through a web-based survey of editors of scholarly journals published in Korea. Methods From December 26, 2018 to January 3, 2019, a survey was distributed to 1,055 persons listed in the member directories of both the Korean Council of Science Editors and the Korean Federation of Science & Technology Societies. The survey contained four items on subjects’ information, three items that gathered information about the journals, and two further items on reasons for adopting or not adopting a data sharing policy and further opinions about such policies. Results Of the 100 respondents (from 100 journals), 13 stated that their journals had already adopted a data sharing policy. The strength of the policy was recommendation-only in 10 of those 13 journals. The most frequent reason for adopting a data sharing policy was to follow international trends. The repository sites were the Harvard Dataverse for two journals and Mendeley Data for one. The most common reasons for not adopting a data sharing policy were a lack of knowledge on data sharing, the possibility that submitters would not want to share their data, and the questionable effect of data sharing on scientific development. Conclusion Data sharing policies were uncommon among Korean scholarly journals. The advantages and disadvantages of adopting such policies should be discussed more actively among editors and researchers. Furthermore, data sharing infrastructure and training courses are required for data sharing policies to be established in scholarly journals in Korea.

This study compared the patterns of duplicate articles between KoreaMed and PubMed journals based on a division of duplicate publications into the 4 categories of ‘copy,’ ‘salami’ (fragmentation), ‘imalas’ (disaggregation), and ‘others,’ as well as in terms of the 11 subcategories suggested by Bae et al., which further elaborate on those 4 main categories. We hypothesized that these 2 groups of articles would show different patterns of duplication. Duplicate publications were identified in a random sample of 5% of the articles from the KoreaMed database published between 2004 and 2009, while all articles with the publication type of ‘duplicate publication’ were selected from PubMed over the same period. The selected articles were classified based on the 4 categories and 11 subcategories of duplicate publications, and the data from the 2 groups were compared. A total of 108 articles were selected from KoreaMed and 45 articles were obtained from PubMed. The category of copy was the most common in both databases. The next most frequent pattern was imalas (disaggregation). Pattern of duplicate publication between 2 databases showed no correlation (P = 0.8754). Although the 108 articles from KoreaMed were allocated to all 11 Bae et al.’s subcategories, those from PubMed were allocated to only 8. The above results showed that the articles in the 2 databases had different patterns of duplication, as defined in terms of the 11 subcategories. The use of these 11 subcategories will help journal editors to develop an appropriate framework for considering a variety of duplication types.