Investigating academic nurse researchers' knowledge, experience, and attitude toward predatory journals.

BACKGROUND: Selecting a journal with an appropriate scope and breadth, well-respected by other scholars in the field, and widely indexed and accessible to readers is an integral part of publishing. Academic publishing has recently seen a significant shift away from traditional print publications and toward open access journals and online publications. OBJECTIVE: The aim of this study was to investigate academic nurse researchers' knowledge, experience, and attitudes regarding predatory journals. METHODS: A descriptive cross-sectional quantitative study design was conducted using Predatory Journals Questionnaire to collect the data from academic nurse educators working at X and XX University. RESULTS: Almost two-thirds (68.6 %) of participants had previous knowledge of the term "predatory journal." As well as, the majority of academic educators had previous experience as they had used predatory journals before, as by being asked to publish in their journal (84.3 %) or serve on its editorial board (24.3 %), participants were more likely to receive requests to submit an article to a predatory journal (52.9 %) via email, mail, or phone. In addition, academic nurse researchers had a moderate perspective (mean = 3.87 ± 1.06; mean % score = 71.71) toward predatory journals. CONCLUSION: Publishing in a predatory journal, whether done knowingly or unknowingly, can harm authors' reputations as academics, their capacity to submit to other journals, and the quality of their work. According to the results of our study, many researchers still lacked a thorough understanding of the predatory journal publishing model, which is a phenomenon that demands an increasing amount of research, despite hearing about the phenomenon of a predatory journal and having previously attended training.

ChatGPT and Corporations of Mega-journals Jeopardize the Norms That Underpin Academic Publishing.

Those who participate in and contribute to academic publishing are affected by its evolution. Funding bodies, academic institutions, researchers and peer-reviewers, junior scholars, freelance language editors, language-editing services, and journal editors are to enforce and uphold the ethical norms on which academic publishing is founded. Deviating from such norms will challenge and threaten the scholarly reputation, academic careers, and institutional standing; reduce the publishers' true impacts; squander public funding; and erode the public trust to the academic enterprise. Rigorous review is paramount because peer-review norms guarantee that scientific findings are scrutinized before being publicized. Volunteer peer-reviewers and guest journal editors devote an immense amount of unremunerated time to reviewing papers, voluntarily serving the scientific community, and benefiting the publishers. Some mega-journals are motivated to mass-produce publications and attract the funded projects instead of maintaining the scientific rigor. The rapid development of mega-journals may diminish some traditional journals by outcompeting their impacts. Artificial intelligence (AI) tools/algorithms such as ChatGPT may be misused to contribute to the mass-production of publications which may have not been rigorously revised or peer-reviewed. Maintaining norms that guarantee scientific rigor and academic integrity enable the academic community to overcome the new challenges such as mega-journals and AI tools.

Impact analysis of primary and secondary research in radiology journals.

INTRODUCTION: Primary and secondary studies are considered the two major research categories. In this study, we examined the scientific and social media impact of primary and secondary publication types in papers published radiological journals during 2010-2020. MATERIALS AND METHODS: PubMed publication type tags were used to filter original articles and systematic review and meta-analysis (SR/MA) articles. Clarivate Web of Science was utilized to obtain a list of all radiology journals from the category "Radiology, Nuclear Medicine and Imaging" in Science Citation Index Expanded (SCIE). Automated approach was developed for programmatic extraction of bibliometric and Altmetric yearly citations of each included article using Dimensions API and Altmetric API with Python. Statistical analysis was performed to compare the citation rates between primary and secondary research articles. RESULTS: A total of 96,684 published articles from 2010 to 2020 were identified and their meta-data collected. The mean 2-year citation count following publication year was 5.8 for primary research and 10.2 for SR/MA articles (p < 0.001). Between 2010 and 2020, the mean number of citations per SR/MA article was 51.3 compared to 30.5 per primary research article (p < 0.001). Mean Altmetric score was 8.2 in SR/MA compared to 3.7 for primary research articles (p < 0.001). CONCLUSION: Secondary research studies have been increasing in impact in both academia and social media compared to primary research. Our results highlight the importance and impact of systematic reviews and meta-analysis articles as a scientifically influential study type in radiology.

Inteligencia artificial y lenguaje médico (III) / Artificial intelligence and medical language (III)

A principios de enero de 2023, la revista Nature se hacía eco de un artículo3 subido a finales de diciembre, sin revisión, al servidor bioRxiv. Los autores pidieron a GePeTo que redactara sendos resúmenes de 50 artículos publicados en cinco revistas biomédicas punteras: The Journal of the American Medical Association (JAMA), The New England Journal of Medicine, The British Medical Journal (BMJ), The Lancet y Nature Medicine. Cuando pasaron un detector automático de plagio a estos resúmenes generados por GePeTo, el resultado fue de un 100% de originalidad. A continuación, presentaron estos 50 resúmenes creados con IA y los 50 resúmenes originales publicados en las revistas a un grupo de científicos con experiencia como revisores externos para importantes publicaciones, y les pidieron que trataran de adivinar cuáles eran humanos y cuáles generados por IA. Un chimpancé tecleando a ciegas (o lanzando al aire una moneda) obtendría una tasa esperable de aciertos del 50%. Los revisores humanos identificaron correctamente como obra de GePeTo apenas el 68% de los resúmenes generados, y reconocieron erróneamente como escritos por IA un 14% de los resúmenes originales publicados. No está nada mal, la verdad, para un bot con menos de un mes de vida; todo apunta a que en los años venideros lo irá haciendo cada vez mejor, y que a corto plazo los textos generados por IA serán indistinguibles de los textos humanos para el común de los lectores. (AU)

Análisis bibliométrico de las revistas oficiales de sociedades de medicina interna en Europa / Bibliometric analysis of the official journals of internal medicine societies in Europe

Introducción La bibliometría evalúa la calidad de las revistas biomédicas. El objetivo de este estudio ha sido comparar los principales índices bibliométricos de las revistas oficiales de sociedades científicas de medicina interna en Europa. Material y métodos Se obtuvo información bibliométrica de las bases de datos Web of Science (WoS) y Scopus. Se analizaron tanto métricas de impacto (Journal Impact Factor [JIF], CiteScore) como normalizadas (Journal Citation Indicator [JCI], Normalized Eigenfactor, Source Normalized Impact per Paper [SNIP] y SCImago Journal Rank [SJR]) de las revistas para el año 2022, y se observó su evolución en la última década. Resultados Se evaluaron 23 revistas oficiales de 33 sociedades científicas. Ocho revistas estaban incluidas en WoS y 11 en Scopus. Las revistas mejor posicionadas en 2022 fueron: 1) European Journal of Internal Medicine, que ocupó el primer cuartil (Q1) de las métricas JIF, CiteScore y JCI, superando valores de uno en las métricas Normalized Eigenfactor y SNIP; 2) Internal and Emergency Medicine, en Q1 para las métricas CiteScore y JCI, y con valores >1 en las métricas Normalized Eigenfactor y SNIP; 3) Polish Archives of Internal Medicine, con Q1 en la métrica JCI; 4) Revista Clínica Española, con Q2 para las métricas JIF, CiteScore y JCI; y 5) Acta Medica Belgica, con Q2 en las métricas CiteScore y JCI. Estas revistas incrementaron sus métricas de impacto en los últimos 3 años, coincidiendo con la pandemia COVID. Conclusiones Cinco revistas oficiales de sociedades europeas de medicina interna, entre ellas Revista Clínica Española, cumplen altos estándares de calidad. (AU)

Introduction Bibliometrics evaluates the quality of biomedical journals. The aim of this study has been to compare the main bibliometric indexes of the official journals of scientific societies of internal medicine in Europe. Material and methods Bibliometric information was obtained from the Web of Science (WoS) and Scopus databases. Both impact metrics (Journal Impact Factor [JIF], CiteScore) and normalized metrics (Journal Citation Indicator [JCI], Normalized Eigenfactor, Source Normalized Impact per Paper [SNIP] and SCImago Journal Rank [SJR]) of the journals for the year 2022 were analyzed, and their evolution over the last decade was described. Results Twenty-three official journals from 33 scientific societies were evaluated. Eight journals were included in WoS and 11 in Scopus. The best positioned journals in 2022 were: 1) European Journal of Internal Medicine, which ranked in the first quartile (Q1) for JIF, CiteScore and JCI metrics, exceeding values of 1 in Normalized Eigenfactor and SNIP metrics; 2) Internal and Emergency Medicine, with Q1 for CiteScore and JCI metrics, and with values >1 in Normalized Eigenfactor and SNIP metrics; 3) Polish Archives of Internal Medicine, with Q1 for JCI metrics; 4) Revista Clínica Española, with Q2 for JIF, CiteScore and JCI metrics; and 5) Acta Medica Belgica, Q2 for CiteScore and JCI metrics. These journals increased their impact metrics in the last 3 years, in parallel with the COVID pandemic. Conclusions Five official journals of European Internal Medicine societies, including Revista Clínica Española, meet high quality standards. (AU)