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Honesty of publications is fundamental in science. Unfortunately, science has an increasing fake paper problem with multiple cases having surfaced in recent years, even in renowned journals. There are companies, the so-called paper mills, which professionally fake research data and papers. However, there is no easy way to systematically identify these papers. Here, we show that scanning for exchanged authors in resubmissions is a simple approach to detect potential fake papers. We investigated 2056 withdrawn or rejected submissions to Naunyn-Schmiedeberg's Archives of Pharmacology (NSAP), 952 of which were subsequently published in other journals. In six cases, the stated authors of the final publications differed by more than two thirds from those named in the submission to NSAP. In four cases, they differed completely. Our results reveal that paper mills take advantage of the fact that journals are unaware of submissions to other journals. Consequently, papers can be submitted multiple times (even simultaneously), and authors can be replaced if they withdraw from their purchased authorship. We suggest that publishers collaborate with each other by sharing titles, authors, and abstracts of their submissions. Doing so would allow the detection of suspicious changes in the authorship of submitted and already published papers. Independently of such collaboration across publishers, every scientific journal can make an important contribution to the integrity of the scientific record by analyzing its own pool of withdrawn and rejected papers versus published papers according to the simple algorithm proposed in the present paper., (© 2023. The Author(s).)

As the field of ophthalmology has evolved in the last several decades, so has the gender distribution of ophthalmologists. We conducted a narrative review to further characterise the status of women in the realm of publication, presentations, editorial positions, grants, academic promotion, and financial compensation. While the proportion of women publishing, presenting, and filling academic and editorial roles has increased over time, it still does not match that of men. Women are more likely to be first authors instead of senior authors, have lower average h-indices, and are awarded fewer grants. The magnitude of some of these differences is smaller when adjusted for women's shorter career duration on average. Despite increased representation of women in ophthalmology, women continue to receive less compensation for the same work. This review highlights that more can be done to improve gender parity in ophthalmology., (© 2024 Royal Australian and New Zealand College of Ophthalmologists.)

Women are underrepresented in senior academic positions within microbiology globally. Studies show that gender bias affects the progression of women in academia, but there is evidence that improving conscious awareness of bias can improve equity in this regard. Here we analyse the publication data associated with review articles within the microbiology field to investigate the statistical associations with author gender. We analyse the data from review articles published between 2010 and 2022 in three leading microbiology review journals: Nature Reviews Microbiology , Trends in Microbiology and Annual Review of Microbiology . We find a significant association between the gender of the lead author and the gender of co-authors in multi-author publications. Review articles with men lead authors have a significantly reduced proportion of women co-authors compared to reviews with women lead authors. Given the existing differences in the proportions of men and women in lead author positions, this association may have important consequences for the relative visibility of women in microbiology, along with negative impacts on scientific output relating to reduced collaboration diversity.

While much of the scholarly work on ethics relating to academic authorship examines the fair distribution of authorship credit, none has yet examined situations where a researcher contributes significantly to the project, but whose contributions do not make it into the final manuscript. Such a scenario is commonplace in collaborative research settings in many disciplines and may occur for a number of reasons, such as excluding research in order to provide the paper with a clearer focus, tell a particular story, or exclude negative results that do not fit the hypothesis. Our concern in this paper is less about the reasons for including or excluding data from a paper and more about distributing credit in this type of scenario. In particular, we argue that the notion 'substantial contribution', which is part of the International Committee of Medical Journal Editors (ICMJE) authorship criteria, is ambiguous and that we should ask whether it concerns what ends up in the paper or what is a substantial contribution to the research process leading up to the paper. We then argue, based on the principles of fairness, due credit, and ensuring transparency and accountability in research, that the latter interpretation is more plausible from a research ethics point of view. We conclude that the ICMJE and other organizations interested in authorship and publication ethics should consider including guidance on authorship attribution in situations where researchers contribute significantly to the research process leading up to a specific paper, but where their contribution is finally omitted.

Competing Interests: Competing interests: None declared.

The COVID-19 pandemic has resulted in school closures and distancing requirements that have disrupted both work and family life for many. Concerns exist that these disruptions caused by the pandemic may not have influenced men and women researchers equally. Many medical journals have published papers on the pandemic, which were generated by researchers facing the challenges of these disruptions. Here we report the results of an analysis that compared the gender distribution of authors on 1893 medical papers related to the pandemic with that on papers published in the same journals in 2019, for papers with first authors and last authors from the United States. Using mixed-effects regression models, we estimated that the proportion of COVID-19 papers with a woman first author was 19% lower than that for papers published in the same journals in 2019, while our comparisons for last authors and overall proportion of women authors per paper were inconclusive. A closer examination suggested that women's representation as first authors of COVID-19 research was particularly low for papers published in March and April 2020. Our findings are consistent with the idea that the research productivity of women, especially early-career women, has been affected more than the research productivity of men., Competing Interests: JA, MN, NS No competing interests declared, RL Founder of TIME'S UP Healthcare, a non-profit initiative that advocates for safety and equity in healthcare; advisor for FeminEM.org, a website that supports the careers of women in medicine. RJ Has stock options as compensation for her advisory board role in Equity Quotient, a company that evaluates culture in health care companies; has received personal fees from Amgen and Vizient and grants for unrelated work from the National Institutes of Health, the Doris Duke Foundation, the Greenwall Foundation, the Komen Foundation, and Blue Cross Blue Shield of Michigan for the Michigan Radiation Oncology Quality Consortium; has a contract to conduct an investigator-initiated study with Genentech; has served as an expert witness for Sherinian and Hasso and Dressman Benzinger LaVelle; uncompensated founding member of TIME'S UP Healthcare; member of the Board of Directors of ASCO., (© 2020, Andersen et al.)

Background: Many previous papers have investigated most-cited articles or most productive authors in academics, but few have studied most-cited authors. Two challenges are faced in doing so, one of which is that some different authors will have the same name in the bibliometric data, and the second is that coauthors' contributions are different in the article byline. No study has dealt with the matter of duplicate names in bibliometric data. Although betweenness centrality (BC) is one of the most popular degrees of density in social network analysis (SNA), few have applied the BC algorithm to interpret a network's characteristics. A quantitative scheme must be used for calculating weighted author credits and then applying the metrics in comparison., Objective: This study aimed to apply the BC algorithm to examine possible identical names in a network and report the most-cited authors for a journal related to international mobile health (mHealth) research., Methods: We obtained 676 abstracts from Medline based on the keywords "JMIR mHealth and uHealth" (Journal) on June 30, 2018. The author names, countries/areas, and author-defined keywords were recorded. The BCs were then calculated for the following: (1) the most-cited authors displayed on Google Maps; (2) the geographical distribution of countries/areas for the first author; and (3) the keywords dispersed by BC and related to article topics in comparison on citation indices. Pajek software was used to yield the BC for each entity (or node). Bibliometric indices, including h-, g-, and x-indexes, the mean of core articles on g(Ag)=sum (citations on g-core/publications on g-core), and author impact factor (AIF), were applied., Results: We found that the most-cited author was Sherif M Badawy (from the United States), who had published six articles on JMIR mHealth and uHealth with high bibliometric indices (h=3; AIF=8.47; x=4.68; Ag=5.26). We also found that the two countries with the highest BC were the United States and the United Kingdom and that the two keyword clusters of mHealth and telemedicine earned the highest indices in comparison to other counterparts. All visual representations were successfully displayed on Google Maps., Conclusions: The most cited authors were selected using the authorship-weighted scheme (AWS), and the keywords of mHealth and telemedicine were more highly cited than other counterparts. The results on Google Maps are novel and unique as knowledge concept maps for understanding the feature of a journal. The research approaches used in this study (ie, BC and AWS) can be applied to other bibliometric analyses in the future., (©Wei-Chih Kan, Willy Chou, Tsair-Wei Chien, Yu-Tsen Yeh, Po-Hsin Chou. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 07.05.2020.)

In research, outcomes are often categorized as primary and secondary. The primary outcome is the most important one; it determines whether the study is considered 'successful' or not. Secondary outcomes are chosen because they provide supporting evidence for the results of the primary outcome or additional information about the subject being studied. For reasons that are explained in this paper, secondary outcomes should be cautiously interpreted. There are varying practices regarding publishing secondary outcomes. Some authors publish these separately, while others include them in the main publication. In some contexts, the former can lead to concerns about the quality and relevance of the data being published. In this article, we discuss primary and secondary outcomes, the importance and interpretation of secondary outcomes, and considerations for publishing multiple outcomes in separate papers. We also discuss the special case of secondary analyses and post hoc analyses and provide guidance on good publishing practices. Throughout the article, we use relevant examples to make these concepts easier to understand. While the article is primarily aimed at early career researchers, it offers insights that may be helpful to researchers, reviewers, and editors across all levels of expertise. [ABSTRACT FROM AUTHOR]

Multidisciplinary approach to malaria research remain important to the national malaria control program in Benin. To unravel the mechanism underlying the establishment of research collaboration ties in malaria research in Benin, we model the complexity and dynamics of the malaria research co-authorship network of Benin using Exponential Random Graph models (ERGMs) and Temporal ERGMs (TERGMs). The network contains co-authorship information from January 1996 to December 2016. We fit ERGMs and TERGMs to the network as a function of nodal, dyadic and structural statistics terms, accounting for important principles of graph theory such as homophily and structural equivalence. The final ERGM and TERGM showed that the mechanistic phenomenon driving collaboration ties in malaria research in Benin is driven by homophily on the type of affiliation and by membership to a research group. Our study is one of a few to take a model-based approach to the study ofco-authorship networks.

With the growth of research collaborations, the average number of authors per article and the phenomenon of equally important authorships have increased. The essence of the phenomenon of equally important authorships is the approximately equal importance of authors, both because of the difficulties in comparing authors' contributions to a paper and some actual research evaluation practices, which (approximately) give full paper credit only to the most important authors. A mechanism for indicating that various authors contributed equally is required to maintain and strengthen collaboration. However, the phenomenon of multiple important authors can cause unfair comparisons among the research contributions and abilities of authors of different papers. This loophole may be exploited. Normalizing the credit assigned to a given paper's authors is an easy way to solve this ethical dilemma. This approach enables fair comparisons of the contributions by the authors of different articles and suppresses unethical behaviour in author listings. Bibliometric researchers have proposed mature methods of normalized paper credit assignment that would be easy to use given the current level of computer adoption.

This paper concerns the responsibility of co-authors in cases of scientific misconduct. Arguments in research integrity guidelines and in the bioethics literature concerning authorship responsibilities are discussed. It is argued that it is unreasonable to claim that for every case where a research paper is found to be fraudulent, each author is morally responsible for all aspects of that paper, or that one particular author has such a responsibility. It is further argued that it is more constructive to specify what task responsibilities come with different roles in a project and describe what kinds of situations or events call for some kind of action, and what the appropriate actions might be.

Purpose: The health professions education (HPE) community is a crossroad of scholars from various disciplines with potentially conflicting views on who qualifies as author. Established HPE scholars are expected to model ethical research conduct, but no research has investigated the extent to which authorship criteria are understood and applied by leaders in the field. This study investigated what leading scholars consider appropriate criteria for authorship and how often these criteria are ignored., Method: Directors of research and editors of HPE journals completed an anonymous survey between September 2015 and August 2016 with questions about authorship practices they experienced and recommended, common authorship criteria, and how often they had encountered unethical authorship decisions., Results: Out of 82 invited scholars, 46 participated in the survey (response rate = 56.0%). They reported a stark contrast between current and recommended authorship practices. Twenty-two (51.2%) had experienced unethical pressure regarding authorship order, 15 (34.9%) had not been included as author when they qualified, and 25 (58.1%) had seen authors included who did not qualify. A slight majority (n = 25; 58.1%) correctly identified authorship standards widely adopted by biomedical journals., Conclusions: A surprising proportion of leaders in the HPE field had encountered unethical authorship practices. Despite widely disseminated authorship criteria, the findings suggest that offering authorship to those who do not qualify, or arguably worse, excluding those who should have been included, remains a common practice. The authors offer strategies to scholars, editors, and tenure and promotion committees to combat these practices.

Abstract Objective The aim of this study was to identify and analyze the gender breakdown of first authorship contributing to the most‐cited papers in the field of otolaryngology, with a goal of identifying trends in gender representation in publishing. Methods The top 150 most‐cited papers were identified using the Science Citation Index of the Institute for Scientific Information. Among the first authors, gender, h‐index, percentage of first, last, and corresponding authorship positions, total publications, and citations were analyzed. Results The majority of papers were in the English language, from the United States, of clinical nature, and on otologic topics. Eighty‐one percent of papers (n = 122) had men who were first authors, although there was no difference in h‐index score, authorship position, number of publications, citations, and average citations/year between men and women first authors. Upon subgroup analysis by decade (1950s–2010s), there was no difference in the number of articles by women first authors (P = 0.11); however, there was a statistically significant increase in the percentage of women authors (P = 0.001) in papers published later compared to those published earlier. Conclusions While a promising number of women otolaryngologists are publishing high‐powered articles, future initiatives to promote academic inclusivity of women should be considered.

Key points: Academia is already witnessing the abuse of authorship in papers with text generated by large language models (LLMs) such as ChatGPT.LLM‐generated text is testing the limits of publishing ethics as we traditionally know it.We alert the community to imminent risks of LLM technologies, like ChatGPT, for amplifying the predatory publishing 'industry'.The abuse of ChatGPT for the paper mill industry cannot be over‐emphasized.Detection of LLM‐generated text is the responsibility of editors and journals/publishers. [ABSTRACT FROM AUTHOR]

Honorary authorship is the inclusion of an author on an article whose contribution does not warrant authorship. We conducted an Internet-based survey among first authors publishing in Indian biomedical journals from 2012 to 2013 to study the frequency and factors associated with honorary authorship. The response rate was 27% (245/908) with the prevalence of perceived, International Committee of Medical Journal Editors (ICMJE)-defined, and unperceived honorary authorship of 20.9% (50/239), 60% (147/245), and 46.9% (115/245), respectively. Those residing in India were found to list more honorary authors. We hope to increase awareness of the ICMJE authorship guidelines and the general issue of honorary authorship among researchers in India and elsewhere.

Many researchers used National Health Insurance database to publish medical papers which are often retrospective, population-based, and cohort studies. However, the author's research domain and academic characteristics are still unclear.By searching the PubMed database (Pubmed.com), we used the keyword of [Taiwan] and [National Health Insurance Research Database], then downloaded 2913 articles published from 1995 to 2017. Social network analysis (SNA), Gini coefficient, and Google Maps were applied to gather these data for visualizing: the most productive author; the pattern of coauthor collaboration teams; and the author's research domain denoted by abstract keywords and Pubmed MESH (medical subject heading) terms.Utilizing the 2913 papers from Taiwan's National Health Insurance database, we chose the top 10 research teams shown on Google Maps and analyzed one author (Dr. Kao) who published 149 papers in the database in 2015. In the past 15 years, we found Dr. Kao had 2987 connections with other coauthors from 13 research teams. The cooccurrence abstract keywords with the highest frequency are cohort study and National Health Insurance Research Database. The most coexistent MESH terms are tomography, X-ray computed, and positron-emission tomography. The strength of the author research distinct domain is very low (Gini < 0.40).SNA incorporated with Google Maps and Gini coefficient provides insight into the relationships between entities. The results obtained in this study can be applied for a comprehensive understanding of other productive authors in the field of academics.

Background: Compulsory submission of a checklist from the relevant reporting guideline is one of the most widespread journal requirements aiming to improve completeness of reporting. However, the current suboptimal levels of adherence to reporting guidelines observed in the literature may indicate that this journal policy is not having a significant effect., Findings: We explored whether authors provided the appropriate CONSORT checklist extension for their study and whether there were inconsistencies between what authors claimed on the submitted checklist and what was actually reported in the published paper. We randomly selected 12 randomized trials from three journals that provide the originally submitted checklist and analyzed six core CONSORT items. Only one paper used the appropriate checklist extension and had no inconsistencies between what was claimed in the submitted checklist and what was reported in the published paper., Conclusion: Journals should take further actions to take full advantage of the requirement for the submission of fulfilled CONSORT checklists, thus ensuring that these checklists reflect what is reported in the manuscript.

Gender and sex analysis is increasingly recognized as a key factor in creating better medical research and health care 1-7 . Using a sample of more than 1.5 million medical research papers, our study examined the potential link between women's participation in medical science and attention to gender-related and sex-related factors in disease-specific research. Adjusting for variations across countries, disease topics and medical research areas, we compared the participation of women authors in studies that do and do not involve gender and sex analysis. Overall, our results show a robust positive correlation between women's authorship and the likelihood of a study including gender and sex analysis. These findings corroborate discussions of how women's participation in medical science links to research outcomes, and show the mutual benefits of promoting both the scientific advancement of women and the integration of gender and sex analysis into medical research.

Authorship of peer-reviewed journal articles and abstracts has become the primary currency and reward unit in academia. Such a reward is crucial for students and postdocs who are often under-compensated and thus highly value authorship as an incentive. While numerous scientific and publishing organizations have written guidelines for determining author qualifications and author order, there remains much ambiguity when it comes to how these criteria are weighed by research faculty. Here, we sought to provide some initial insight on how faculty view the relative importance of 11 criteria for scientific authorship. We distributed an online survey to 564 biomedical engineering, biology, and bioengineering faculty members at 10 research institutions across the United States. The response rate was approximately 18%, resulting in a final sample of 102 respondents. Results revealed an agreement on some criteria, such as time spent conducting experiments, but there was a lack of agreement regarding the role of funding procurement. This study provides quantitative assessments of how faculty members in the biosciences evaluate authorship criteria. We discuss the implications of these findings for researchers, especially new graduate students, to help navigate the discrepancy between official policies for authorship and the contributions that faculty truly value.

In the rapid evolving landscape of artificial intelligence (AI), scientific publishing is experiencing significant transformations. AI tools, while offering unparalleled efficiencies in paper drafting and peer review, also introduce notable ethical concerns. This study delineates AI's dual role in scientific publishing: as a co-creator in the writing and review of scientific papers and as an ethical challenge. We first explore the potential of AI as an enhancer of efficiency, efficacy, and quality in creating scientific papers. A critical assessment follows, evaluating the risks vs. rewards for researchers, especially those early in their careers, emphasizing the need to maintain a balance between AI's capabilities and fostering independent reasoning and creativity. Subsequently, we delve into the ethical dilemmas of AI's involvement, particularly concerning originality, plagiarism, and preserving the genuine essence of scientific discourse. The evolving dynamics further highlight an overlooked aspect: the inadequate recognition of human reviewers in the academic community. With the increasing volume of scientific literature, tangible metrics and incentives for reviewers are proposed as essential to ensure a balanced academic environment. AI's incorporation in scientific publishing is promising yet comes with significant ethical and operational challenges. The role of human reviewers is accentuated, ensuring authenticity in an AI-influenced environment. As the scientific community treads the path of AI integration, a balanced symbiosis between AI's efficiency and human discernment is pivotal. Emphasizing human expertise, while exploit artificial intelligence responsibly, will determine the trajectory of an ethically sound and efficient AI-augmented future in scientific publishing. [ABSTRACT FROM AUTHOR]

Moderate-to-severe psoriasis is associated with significant comorbidity, an impaired quality of life, and increased medical costs, including those associated with treatments. Systematic reviews (SRs) and meta-analyses (MAs) of randomized clinical trials are considered two of the best approaches to the summarization of high-quality evidence. However, methodological bias can reduce the validity of conclusions from these types of studies and subsequently impair the quality of decision making. As co-authorship is among the most well-documented forms of research collaboration, the present study aimed to explore whether authors' collaboration methods might influence the methodological quality of SRs and MAs of psoriasis. Methodological quality was assessed by two raters who extracted information from full articles. After calculating total and per-item Assessment of Multiple Systematic Reviews (AMSTAR) scores, reviews were classified as low (0-4), medium (5-8), or high (9-11) quality. Article metadata and journal-related bibliometric indices were also obtained. A total of 741 authors from 520 different institutions and 32 countries published 220 reviews that were classified as high (17.2%), moderate (55%), or low (27.7%) methodological quality. The high methodological quality subnetwork was larger but had a lower connection density than the low and moderate methodological quality subnetworks; specifically, the former contained relatively fewer nodes (authors and reviews), reviews by authors, and collaborators per author. Furthermore, the high methodological quality subnetwork was highly compartmentalized, with several modules representing few poorly interconnected communities. In conclusion, structural differences in author-paper affiliation network may influence the methodological quality of SRs and MAs on psoriasis. As the author-paper affiliation network structure affects study quality in this research field, authors who maintain an appropriate balance between scientific quality and productivity are more likely to develop higher quality reviews.