Purpose: Resilience is an essential concept used to describe the ability to cope and adapt effectively in the face of loss, hardship, or adversity by patients, nurses, and nursing students. The purpose of this study was to identify research trends on resilience related to nursing and patients.Methods: The Web of Science Core Collection database was searched on February 21, 2023, with the terms “resilienc*” in the title and “nurs* and “patient* in the topic. A total of 361 documents were extracted. A web-based analysis in R prepared using web-r.org was used to generate visualizations of publishing trends, journal ranks, authorship analysis, the most prolific nations, author collaboration patterns, a KeyWords Plus analysis, trend themes, and the most cited articles.Results: Research reports on resilience related to nursing and patients were first published in 2007 and have shown a substantial increase since 2019, with more than 30 publications per year. The largest amount of related literature was published in the <i>Journal of Nursing Management</i>, and the <i>Journal of Advanced Nursing</i> included the largest number of citations. Rushton CH was the most prolific author, with six publications, and she was the author of the most cited study. The most productive country was the United States. The most frequently encountered KeyWords Plus terms were “burnout,” “stress,” and “health.”Conclusion: The findings of this study can offer information to future researchers as well as the opportunity to conduct more novel studies on resilience in nursing.

Purpose: Wordvice AI Proofreader is a recently developed web-based artificial intelligence-driven text processor that provides real-time automated proofreading and editing of user-input text. It aims to compare its accuracy and effectiveness to expert proofreading by human editors and two other popular proofreading applications—automated writing analysis tools of Google Docs, and Microsoft Word. Because this tool was primarily designed for use by academic authors to proofread their manuscript drafts, the comparison of this tool’s efficacy to other tools was intended to establish the usefulness of this particular field for these authors.Methods: We performed a comparative analysis of proofreading completed by the Wordvice AI Proofreader, by experienced human academic editors, and by two other popular proofreading applications. The number of errors accurately reported and the overall usefulness of the vocabulary suggestions was measured using a General Language Evaluation Understanding metric and open dataset comparisons.Results: In the majority of texts analyzed, the Wordvice AI Proofreader achieved performance levels at or near that of the human editors, identifying similar errors and offering comparable suggestions in the majority of sample passages. The Wordvice AI Proofreader also had higher performance and greater consistency than that of the other two proofreading applications evaluated.Conclusion: We found that the overall functionality of the Wordvice artificial intelligence proofreading tool is comparable to that of a human proofreader and equal or superior to that of two other programs with built-in automated writing evaluation proofreaders used by tens of millions of users: Google Docs and Microsoft Word.

Purpose: This study aimed to develop a decision-support tool to quantitatively determine authorship in clinical trial publications.Methods: The tool was developed in three phases: consolidation of authorship recommendations from the Good Publication Practice (GPP) and International Committee of Medical Journal Editors (ICMJE) guidelines, identifying and scoring attributes using a 5-point Likert scale or a dichotomous scale, and soliciting feedback from editors and researchers.Results: The authorship criteria stipulated by the ICMJE and GPP recommendations were categorized into 2 Modules. Criterion 1 and the related GPP recommendations formed Module 1 (sub-criteria: contribution to design, data generation, and interpretation), while Module 2 was based on criteria 2 to 4 and the related GPP recommendations (sub-criteria: contribution to manuscript preparation and approval). The two modules with relevant sub-criteria were then differentiated into attributes (n = 17 in Module 1, n = 12 in Module 2). An individual contributor can be scored for each sub-criterion by summing the related attribute values; the sum of sub-criteria scores constituted the module score (Module 1 score: 70 [contribution to conception or design of the study, 20; data acquisition, 7; data analysis, 27; interpretation of data, 16]; Module 2 score: 50 [content development, 27; content review, 18; accountability, 5]). The concept was integrated into Microsoft Excel with adequate formulae and macros. A threshold of 50% for each sub-criterion and each module, with an overall score of 65%, is predefined as qualifying for authorship.Conclusion: This authorship decision-support tool would be helpful for clinical trial sponsors to assess and provide authorship to deserving contributors.

Purpose: This study explored changes in the journal publishing market by publisher and access type using the major journals that publish about 95% of Journal Citation Reports (JCR) articles.Methods: From JCR 2016, 2018, and 2020, a unique journal list by publisher was created in Excel and used to analyze the compound annual growth rate by pivot tables. In total, 10,953 major JCR journals were analyzed, focusing on publisher type, open access (OA) status, and mega journals (publishing over 1,000 articles per year).Results: Among the 19 publishers that published over 10,000 articles per year, in JCR 2020, six large publishers published 59.6% of the articles and 13 publishers 22.5%. The other publishers published 17.9%. Large and OA publishers increased their article share through leading mega journals, but the remaining publishers showed the opposite tendency. In JCR 2020, mega journals had a 26.5% article share and an excellent distribution in terms of the Journal Impact Factor quartile. Despite the high growth (22.6%) and share (26.0%) of OA articles, the natural growth of non-OA articles (7.3%) and total articles (10.7%) caused a rise in journal subscription fees. Articles, citations, the impact factor, and the immediacy index all increased gradually, and the compound annual growth rate of the average immediacy index was almost double than that of the average impact factor in JCR 2020.Conclusion: The influence of OA publishers has grown under the dominance of large publishers, and mega journals may substantially change the journal market. Journal stakeholders should pay attention to these changes.

This article aims to explain the key metadata elements listed in Participation Reports, why it’s important to check them regularly, and how Crossref members can improve their scores. Crossref members register a lot of metadata in Crossref. That metadata is machine-readable, standardized, and then shared across discovery services and author tools. This is important because richer metadata makes content more discoverable and useful to the scholarly community. It’s not always easy to know what metadata Crossref members register in Crossref. This is why Crossref created an easy-to-use tool called Participation Reports to show editors, and researchers the key metadata elements Crossref members register to make their content more useful. The key metadata elements include references and whether they are set to open, ORCID iDs, funding information, Crossmark metadata, licenses, full-text URLs for text-mining, and Similarity Check indexing, as well as abstracts. ROR IDs (Research Organization Registry Identifiers), that identify institutions will be added in the future. This data was always available through the Crossref ’s REST API (Representational State Transfer Application Programming Interface) but is now visualized in Participation Reports. To improve scores, editors should encourage authors to submit ORCIDs in their manuscripts and publishers should register as much metadata as possible to help drive research further.

What is the objective for science journals to publish research papers? Would it be enough to collect research manuscripts and simply publish them in print or on the web? Science journal publishers have always strived to find ways of disseminating journal content to as many readers as possible. It is now time for science journal publishers to think about why a journal should be published; whether it is acceptable for valuable scientific findings to lie dormant in a journal’s archive; and whether traditional science communication is still effective. The present article suggests that science journals should transform themselves into science storytellers to improve the visibility and discoverability of their research findings. First, a new communication network between journals, authors, peers, the public, and policymakers is required. Second, conversion of media from academic language to plain language is critical to broadening the audience. Third, audio-visual content should be introduced into journal publishing to facilitate easy comprehension of the content. Fourth, research-focused channels, including EurekAlert, Medium, and social networking service channels are recommended as new media to propagate journals’ content to researchers. Improving visibility and discoverability is an urgent mission, especially for small society journals. To achieve this mission, science journals should be adapted to become storytellers and science communicators, as suggested above. A small society journal’s editor is not merely an editor, but an editor-publisher; therefore, editors should understand and take on this role.

The flood of research output and increasing demands for peer reviewers have necessitated the intervention of artificial intelligence (AI) in scholarly publishing. Although human input is seen as essential for writing publications, the contribution of AI slowly and steadily moves ahead. AI may redefine the role of science communication experts in the future and transform the scholarly publishing industry into a technology-driven one. It can prospectively improve the quality of publishable content and identify errors in published content. In this article, we review various AI and other associated tools currently in use or development for a range of publishing obligations and functions that have brought about or can soon leverage much-demanded advances in scholarly communications. Several AI-assisted tools, with diverse scope and scale, have emerged in the scholarly market. AI algorithms develop summaries of scientific publications and convert them into plain-language texts, press statements, and news stories. Retrieval of accurate and sufficient information is prominent in evidence-based science publications. Semantic tools may empower transparent and proficient data extraction tactics. From detecting simple plagiarism errors to predicting the projected citation impact of an unpublished article, AI’s role in scholarly publishing is expected to be multidimensional. AI, natural language processing, and machine learning in scholarly publishing have arrived for writers, editors, authors, and publishers. They should leverage these technologies to enable the fast and accurate dissemination of scientific information to contribute to the betterment of humankind.

With the goal of improving the publishing ecosystem and promoting transparency in journal publishing, we describe some recent cases in scientific publishing in Korea. The current article summarizes ethical inquiries from domestic journals and publishers, most of whom are members of the Korean Council of Science Editors. We selected 15 representative questions asked during the last 4 years. Those inquiries were classified into hot topics such as plagiarism, duplicate publications, multiple submission, and others (informed consent, copyright, compliance with journal regulations, authors’ responsibilities, and voluntary retraction requests). When plagiarism is suspected, editors and reviewers should assess the situation following the relevant rules and procedures, and if necessary, the manuscript should be rejected. Cases of duplicate publication should be clearly stated in both papers based on the explicit agreement of the editor-in-chief of both journals. As a general rule, the entire content of an article should be published in one issue, but if the article is too long, it may need to be published in two issues. Permission from both journals is required. The abstract and references should be separated accordingly. In cases of copyright conflict, voluntary withdrawal of a paper, or non-compliance with publishing regulations, the manuscript must be withdrawn according to specific procedures (referring to the COPE flow chart). All correspondence regarding a manuscript should be with the corresponding author, who communicates directly with the journal. We hope that these recommendations will help readers in the field of scientific publishing to address issues related to publication ethics.