bims-skolko Biomed News
on Scholarly communication
Issue of 2026–06–07
forty-five papers selected by
Thomas Krichel, Open Library Society
  1. The NIH 2025 Public Access Policy: Immediate access, unequal costs.
  2. First and last authors more likely to be men in leading science journals.
  3. Two economies of medical knowledge: The publishing oligopoly and the clinical trial shadow profession.
  4. The Strong Get Stronger: The Matthew Effect in Academic Publishing.
  5. Is it time to 'cap and trade' credits for research-funding proposals?
  6. What's behind China's historically high counts of corresponding authors?
  7. Conflicts of interest and interpretive authority in oncology.
  8. Pediatricians Facing Industry-Sponsored Pressures: Key Ethical Considerations.
  9. Diversity Science in Perioperative Medicine: Key Concepts and Guidance for Publishing and Reviewing.
  10. The UN SDGs as a global 'directive shift' and the institutionalization of sustainability research.
  11. Generative AI: Opportunities, risks, and responsibilities for oral sciences.
  12. Artificial Intelligence-Assisted Writing and Editing, and the Rise of "Tortured Phrases" in Nursing Literature.
  13. It cannot be that suddenly all research is more transformative and produces greater insights: The influence of AI on scientific writing.
  14. Plagiarism in the Age of Generative Artificial Intelligence: The advent of generative artificial intelligence (GenAI) tools is challenging the scientific community's understanding of the meaning and significance of plagiarism. A new definition of research misconduct is needed that specifically addresses the use of GenAI writing tools.
  15. Artificial Intelligence Policies in Human Anatomy Journals: A Comparative Analysis and Recommendations.
  16. Scientific publishing in the era of artificial intelligence: Integrity and responsibility.
  17. Editorial policies for ethical use of artificial intelligence in rheumatology journals.
  18. Linguistic shifts in dental scientific writing in the large language model era.
  19. Use of artificial intelligence tools in the publishing process: expectations from publishers through author guidelines.
  20. In Defense of AI as an 'Author' Ethical Implications for Scientific Authors, Reviewers, Editors, and Publishing Policies.
  21. Preserving scientific integrity in academic publishing: Navigating artificial intelligence, journal policies, and the impact factor as a quality indicator.
  22. AI in peer review: the elephant in the editorial room.
  23. Large Language Model Authorship in Ophthalmic Publications.
  24. AI hallucinations in academic writing: implications for research integrity.
  25. Polished reviews are not enough: Assessing durable learning in mentor-guided AI writing.
  26. Will the widespread use of large language models in scientific writing undermine scientists' critical thinking?
  27. Susceptibility of large language models to hidden nudge injection during simulated medical peer review: a quasi-experimental study.
  28. Strengthening Peer Review: Strategic Approaches for Authors, Reviewers, Editors, Journals, and Academic Institutions.
  29. The Lack of Reviewers Pandemic (LRP) - what can be done?
  30. Scientific Fraud: How Do We Ensure Sound Medical Literature?
  31. The Human Value of Peer Review in Nursing.
  32. EQUATOR reporting guideline use and editorial enforcement in four medical specialties: a cross-sectional study of 20 high-impact journals.
  33. Attitudes of Longitudinal Study Participants and Members of the Public Towards Data Sharing for Secondary Research: A Survey Based Approach.
  34. Research integrity and transparency in CAM journals: an analysis of publication bias and reporting practices (1995-2023) in four leading journals.
  35. With qualitative research, the risks of data sharing can outweigh the rewards.
  36. Case reports in clinical medicine: why it matters and how to do it.
  37. Data sharing in stepped-wedge cluster randomized trials: suboptimal data availability despite "data available upon request".
  38. Preparing to Prepare a Manuscript.
  39. How Did You Get There? The Value of Segues for Illustrating Your Logic.
  40. Aligning incentives for open science in biomedical research: Navigating funder and institutional perspectives.
  41. Improving acknowledgments sections to better credit research contributors.
  42. Creating a smoother path to scientific publication.
  43. Psychiatrists Must Address Predatory Journals with Trainees and Early-Career Collaborators.
  44. Who pays for participation? Hidden personal costs in (exercise) physiology.
  45. Advancing Academic Gastroenterology: Reflections From a Social Media Ambassador for ACG Case Reports Journal.
  1. PLoS Med. 2026 Jun;23(6): e1005124
    The NIH 2025 Public Access Policy: Immediate access, unequal costs.
    Caitlin R Ryus, Caroline Raymond King, Edward R Melnick.
      The NIH 2025 Public Access Policy eliminates embargo periods for federally funded research, expanding who can read science. Yet without addressing article processing charges and market concentration, the policy risks creating new barriers to who can afford to perform and publish their science.
    DOI:  https://doi.org/10.1371/journal.pmed.1005124
  2. Nature. 2026 Jun 02.
    First and last authors more likely to be men in leading science journals.
    Rachel Nuwer, Vera Nienaber.
      
    Keywords:  Authorship; Careers; Publishing; Research data
    DOI:  https://doi.org/10.1038/d41586-026-01495-8
  3. Account Res. 2026 Jun 01. 2678608
    Two economies of medical knowledge: The publishing oligopoly and the clinical trial shadow profession.
    Arif Hakan Önder.
      Contemporary medical knowledge is generated within two interconnected economies that are often examined separately. First, the publishing market has become increasingly oligopolistic, transforming unpaid academic labour and public funding into substantial profits through subscription models and article processing charges. Second, a parallel clinical research economy has emerged around industry-sponsored trials, where per-patient payments and investigator fees can create a shadow profession that provides both income and prestige to physicians. This article argues that these systems do not merely coexist but mutually reinforce and obscure one another. The normalization of industry-mediated clinical advantages weakens awareness of publisher-mediated extraction, while the opacity of publishing finances renders the incentive structures of clinical trials ethically unremarkable. Using the metaphor of "mud" to describe the gradual internalization of structural distortions, the article examines how silence emerges at the intersection of prestige dependence, organizational conflicts of interest, and the entrepreneurial transformation of academic identity. Finally, it proposes practical individual-, institutional-, and policy-level measures, including greater transparency regarding trial-related income and support for community-governed publishing models, to strengthen ethical visibility and accountability in medical research.
    Keywords:  Medical publishing; academic capitalism; article processing charges; clinical trial economy; conflict of interest; open access
    DOI:  https://doi.org/10.1080/08989621.2026.2678608
  4. Balkan Med J. 2026 Jun 01. 43(6): 294-296
    The Strong Get Stronger: The Matthew Effect in Academic Publishing.
    Selçuk Korkmaz, Servet Altay.
      
    DOI:  https://doi.org/10.4274/balkanmedj.galenos.2026.2026.150426
  5. Nature. 2026 Jun;654(8117): 290
    Is it time to 'cap and trade' credits for research-funding proposals?
    Neil M Davies, David Bann, Matthew Keller, Marcus Munafò.
      
    Keywords:  Funding; Machine learning; Publishing
    DOI:  https://doi.org/10.1038/d41586-026-01777-1
  6. Nature. 2026 Jun 04.
    What's behind China's historically high counts of corresponding authors?
    Dalmeet Singh Chawla.
      
    Keywords:  Authorship; Institutions; Policy; Publishing
    DOI:  https://doi.org/10.1038/d41586-026-01623-4
  7. Eur J Cancer. 2026 May 28. pii: S0959-8049(26)00625-8. [Epub ahead of print]243 116844
    Conflicts of interest and interpretive authority in oncology.
    Saroj Niraula, Samuel X Stevens, Tito Fojo, Ian F Tannock.
      Disclosure alone may not adequately address conflicts of interest in oncology. The significance of financial relationships differs between primary research and interpretive articles that shape clinical narratives and standards of care. We argue that journals should assess whether the pattern and magnitude of conflicts are proportionate to the manuscript's interpretive role, particularly for articles addressing commercially important therapies.
    Keywords:  Conflict of interest; Editorial policy; Financial relationships; Interpretive articles; Oncology publishing
    DOI:  https://doi.org/10.1016/j.ejca.2026.116844
  8. Indian Pediatr. 2026 Jun 01.
    Pediatricians Facing Industry-Sponsored Pressures: Key Ethical Considerations.
    Dhanya Dharmapalan, T Jacob John, Yeshwant K Amdekar, Piyush Gupta.
      Interactions between physicians and pharmaceutical companies are common for mutual exchange of medical knowledge; pediatric field is no exception. However, vested commercial interests could encourage irrational prescribing behavior. The pharmaceutical industry can offer free drug samples, gifts, travel expenses and honoraria to physicians in addition to sponsorship for academic events, access to medical softwares or academic activities in return for promoting and endorsing their products. Given that pediatricians care for a particularly vulnerable population, they bear an added responsibility to uphold the highest standards of ethical professional conduct. Financial transparency, protection of data confidentiality, stricter framework by the journal editors in evaluating possible gift authorships and industry-facilitated research and careful vigil by professional bodies (Academies/Societies/Associations) are a few solutions that could ensure that their members adhere to ethical standards and regulatory guidelines.
    Keywords:  DPDP Act; National Medical Commission; Pharmaceuticals; Sponsorship; Uniform Code of Pharmaceutical Marketing Practices
    DOI:  https://doi.org/10.1007/s13312-026-00361-0
  9. Anesth Analg. 2026 Jun 01.
    Diversity Science in Perioperative Medicine: Key Concepts and Guidance for Publishing and Reviewing.
    Molly B Kraus, Avareena E Schools-Cropper, Abimbola O Faloye, Matthew C Wixson, Tanjala S Purnell.
      
    DOI:  https://doi.org/10.1213/ANE.0000000000007999
  10. PLoS One. 2026 ;21(6): e0348507
    The UN SDGs as a global 'directive shift' and the institutionalization of sustainability research.
    Alesia A Zuccala, Anna Leoncini, Andrea Bonaccorsi.
      This paper examines how the UN Sustainable Development Goals (SDGs) shape the institutionalization of sustainability research within scholarly publishing. We argue that the SDGs operate as a globally endorsed form of external research agenda-setting, constituting a "directive shift" in science. Focusing on SDG 04 (Quality Education), SDG 08 (Decent Work and Economic Growth), and SDG 13 (Climate Action), we analyse changes in Scopus-indexed journals from 1990 to 2024. Using large-scale bibliometric data, we classify (n = 30,604) journals by activity level, age (newborn, young, mature, established), disciplinarity, publishing model, and long-term survival across publication thresholds (k = 1, 3, 5, 10). Results reveal a sustained increase in journal participation related to SDG-related publishing, with pronounced entry surges around major international agreements in 2005 and 2015. Participation is driven primarily by young and mature journals, while established journals contribute a comparatively small share of new entrants. Further analysis of established titles reveals that top-ranked (Q1) core journals are more prominent in SDG 13 than in SDG 04 and SDG 08, suggesting uneven integration across disciplinary hierarchies. Multidisciplinary and open-access journals dominate entry patterns, and survival rates increase at higher publication thresholds, indicating sustained engagement over time. Overall, these structural dynamics suggest that the SDGs operate as a directive shift, contributing to the progressive consolidation of sustainability research within the journal system.
    DOI:  https://doi.org/10.1371/journal.pone.0348507
  11. JADA Found Sci. 2025 ;4 100056
    Generative AI: Opportunities, risks, and responsibilities for oral sciences.
    Falk Schwendicke, Sharanbir K Sidhu, Jack L Ferracane, Antonin Tichy, Nicholas S Jakubovics.
      Generative artificial intelligence (AI) has the capability to generate new content-including text, code, imagery, video, and speech-based on human prompts and is entering dental and oral research. By retrieving, analyzing, summarizing, and contextualizing vast datasets, generative AI offers substantial potential to enhance scientific workflows. It can improve documentation, communication, and reproducibility while saving time and accelerating discovery. However, its integration into research brings significant ethical, societal, and scientific challenges. Concerns include embedded data biases, automation bias, overreliance, and error propagation, all requiring critical human oversight. Furthermore, generative AI raises complex issues around plagiarism, fraud, attribution, and reproducibility, compounded by the potential for AI "hallucinations" or fabricated content. Addressing these concerns demands transparency, robust verification processes, ethical compliance, and clear documentation distinguishing synthetic from real-world data. Several scientific and regulatory bodies have published guidelines to support responsible AI use. Recommendations relevant to scientists in dental, oral, and craniofacial research include transparent disclosure of AI tools and methods, thorough verification of AI outputs, ethical oversight, and active monitoring. Scientists are urged to work collaboratively with stakeholders to enforce these principles and engage the public in the evolving discourse. The risk of misuse, particularly through fraudulent AI-generated publications, is growing. Paper mills exploiting generative AI can produce fabricated or manipulated articles, which may mislead the scientific community and distort evidence bases. Coordinated action, involving journals, institutions, and ethics bodies, is essential to combat these threats. As generative AI continues to evolve, adaptive and harmonized guidelines wil be necessary to safeguard scientific integrity. Researchers, reviewers, and editors must play a proactive role in ensuring that AI serves to advance-not undermine-the quality and trustworthiness of dental and oral science.
    Keywords:  Artificial intelligence; large language models; peer review; reproducibility of results; responsible artificial intelligence; scientific misconduct
    DOI:  https://doi.org/10.1016/j.jfscie.2025.100056
  12. Nurs Health Sci. 2026 Jun;28(2): e70366
    Artificial Intelligence-Assisted Writing and Editing, and the Rise of "Tortured Phrases" in Nursing Literature.
    Jaime A Teixeira da Silva, Marilyn H Oermann.
      
    Keywords:  accountability; artificial intelligence; jargon; linguistic; scientific; technical accuracy
    DOI:  https://doi.org/10.1111/nhs.70366
  13. J Appl Physiol (1985). 2026 Jun 01.
    It cannot be that suddenly all research is more transformative and produces greater insights: The influence of AI on scientific writing.
    Jaume Padilla, Francisco I Ramirez-Perez.
      
    DOI:  https://doi.org/10.1152/japplphysiol.00359.2026
  14. Nat Mach Intell. 2026 May 18.
    Plagiarism in the Age of Generative Artificial Intelligence: The advent of generative artificial intelligence (GenAI) tools is challenging the scientific community's understanding of the meaning and significance of plagiarism. A new definition of research misconduct is needed that specifically addresses the use of GenAI writing tools.
    David Resnik, Mohammad Hosseini.
      
    DOI:  https://doi.org/10.1038/s42256-026-01247-3
  15. Clin Anat. 2026 Jun 04.
    Artificial Intelligence Policies in Human Anatomy Journals: A Comparative Analysis and Recommendations.
    Brittany Luckett, Grace Acosta, Eric Bixler, Christopher Bobier.
      Professional organizations in human anatomy have not yet issued guidance on the use of artificial intelligence (AI) in scholarship, leaving decisions about its permissibility to individual journals and publishers. To date, however, journal and publisher AI policies in the field of human anatomy have not been systematically examined. This study compares AI policies across human anatomy journals and their publishers. Fifty-two human anatomy journals were identified using the 2024 SCImago Journal Rank. Nine journals were excluded due to non-English-only publication or classification as book series, leaving 43 journals for analysis. Journal websites were manually reviewed for statements addressing AI use. For journals without a journal-specific AI policy, affiliated publisher websites were searched for relevant policies; if none were found, the journal's editor was contacted. Fifteen journals had journal-specific AI policies, and 20 journals were affiliated with publishers that maintained publicly available AI policies. All policies permitted AI use provided authors retained full responsibility for submitted content and disclosed AI involvement. Nineteen policies exempted disclosure when AI was used solely for editorial purposes, while 16 required disclosure of every AI use. There is no uniform guidance regarding AI use in human anatomy scholarship. We therefore propose three recommendations: (1) Human anatomy professional associations should develop and disseminate guidelines collaboratively. (2) Editors of human anatomy journals should establish uniform AI policies across journals. (3) Each journal's AI policy should be embedded within its author guidelines.
    DOI:  https://doi.org/10.1002/ca.70151
  16. Rev Port Cardiol. 2026 Jun 03. pii: S0870-2551(26)00173-3. [Epub ahead of print]
    Scientific publishing in the era of artificial intelligence: Integrity and responsibility.
    Mário M Oliveira.
      
    DOI:  https://doi.org/10.1016/j.repc.2026.06.002
  17. Semin Arthritis Rheum. 2026 Jun 01. pii: S0049-0172(26)00055-7. [Epub ahead of print]79 152966
    Editorial policies for ethical use of artificial intelligence in rheumatology journals.
    Yuliya Fedorchenko, Ahmet Usen, Birzhan Seiil, Olena Zimba, Mariusz Korkosz.
       BACKGROUND: The integration of artificial intelligence (AI) into research and publishing poses ethical challenges. Global editorial associations, including the International Committee of Medical Journal Editors (ICMJE), have updated their recommendations to safeguard transparency and accountability for AI use. The extent to which these recommendations have been enforced in specialist journals remains unknown.
    OBJECTIVE: The aim of our study was to analyze the extent to which indexed rheumatology journals have adopted AI-related editorial policies, the scope of these policies, and their alignment with ICMJE recommendations.
    METHODS: A total of 58 impact-factor rheumatology journals were analyzed in view of their AI-related editorial policies. Author instructions, ethics statements, and publisher guidelines were overviewed for (1) AI-related instructions; (2) alignment with ICMJE recommendations; (3) provisions regulating AI use by authors, peer reviewers, and editors; and (4) regulations concerning generative text, images, data, and analytical outputs.
    RESULTS: Of the 58 journals, 45 (77.6%) presented explicit AI editorial policies, while 13 (22.4%) lacked any AI-related guidance. The majority of journals (98.2%) endorsed ICMJE points on AI. High-impact journals-Nature Reviews Rheumatology, The Lancet Rheumatology, and Annals of the Rheumatic Diseases-demonstrated the most stringent governance, prohibiting AI use for analytical and creative roles, mandating detailed disclosure of AI tools and prompts, and banning AI use for peer review and editorial decision-making. The guidance on AI use by peer reviewers and editors was present in 45 journals (77.6%). Permissive uses of AI were largely confined to language editing under human supervision. Generative or substantive uses-such as producing figures, conceptual contents, or data-were broadly restricted.
    CONCLUSIONS: Indexed rheumatology journals demonstrate variable editorial policies of enforcing AI guidance. While the adoption of AI-related policies is mostly improving, a marked heterogeneity still exists, particularly between top-tier and lower-tier journals. Upgrades of editorial policies are warranted to safeguard the integrity and transparency of rheumatology sources.
    Keywords:  Artificial intelligence; Editorial policies; Publication ethics; Rheumatology
    DOI:  https://doi.org/10.1016/j.semarthrit.2026.152966
  18. Res Integr Peer Rev. 2026 Jun 04.
    Linguistic shifts in dental scientific writing in the large language model era.
    Hadar Better, Doron Haim, Thabet Asbi, Gavriel Chaushu, Keren Better.
       BACKGROUND: The integrity of scientific literature depends on transparent authorship and authentic communication of research findings. The release of ChatGPT in November 2022 introduced powerful AI writing assistance that may be changing how dental researchers write manuscripts. However, systematic evidence documenting this shift and its implications for research integrity remains limited. Traditional detection tools and self-reported surveys have proven unreliable, requiring alternative approaches to assess AI's influence on published literature.
    OBJECTIVE: To detect and quantify linguistic changes in dental scientific abstracts by comparing pre-ChatGPT (2021) and post-ChatGPT (2025) periods, providing empirical evidence of AI adoption patterns and their implications for scientific communication integrity.
    METHODS: We analyzed 2,770 abstracts from six major dental journals using vocabulary-based linguistic analysis. Following computational linguistics methods validated in biomedical literature, we extracted six AI-associated features and computed composite detection scores. This observational text-based approach avoids reporting bias while providing quantifiable evidence of linguistic shifts.
    RESULTS: AI detection scores increased significantly across all journals (mean: 12.01 to 14.46; + 20.4%), with individual journal increases ranging from +10.0% to +34.5%. The mean number of AI marker words per abstract rose from 0.69 to 0.97 (+41.1%), while high-suspicion abstracts (score ≥ 20) increased from 18.0% to 25.8% (+43%). Changes were consistent across journal specialty, geography, and impact factor, suggesting field-wide adoption.
    CONCLUSIONS: Dental scientific writing has undergone measurable linguistic changes coinciding with widespread AI availability. The consistency and magnitude of these changes raise questions about transparency in AI use, maintaining authorial voice, and preserving the integrity of scientific communication. These findings provide an empirical foundation for evidence-based policies on AI disclosure and appropriate use in academic publishing, grounded in observed changes to scientific communication rather than speculative concern.
    Keywords:  Artificial intelligence; Authorship transparency; ChatGPT; Large language models; Publication ethics; Research integrity; Scientific writing
    DOI:  https://doi.org/10.1186/s41073-026-00226-x
  19. Front Res Metr Anal. 2026 ;11 1740510
    Use of artificial intelligence tools in the publishing process: expectations from publishers through author guidelines.
    Josiline Chigwada, Patrick Ngulube.
       Introduction: The rapid integration of artificial intelligence (AI) into scholarly publishing has prompted publishers to develop policies that guide its ethical and practical use. This study explored the question, "What do publishers expect on the use of AI as portrayed in the author guidelines and AI publisher policies?" The investigation was guided by internationally recognized frameworks, including the STM ethical and practical guidelines on AI use, the Committee on Publication Ethics, the World Association of Medical Editors (WAME) recommendations on chatbots and generative AI in scholarly publishing, and the International Committee of Medical Journal Editors (ICMJE) standards.
    Methods: A qualitative research approach was employed, drawing from AI-related guidelines and policies from major scholarly publishers. Four publishers were purposively selected based on their global reach, relevance across multiple disciplines, and established AI policies. Data collection was conducted through document and web content analysis, which systematically extracted relevant information from publishers' websites.
    Results: A qualitative research approach was employed, drawing from AI-related guidelines and policies from major scholarly publishers. Four publishers were purposively selected based on their global reach, relevance across multiple disciplines, and established AI policies. Data collection was conducted through document and web content analysis, which systematically extracted relevant information from publishers' websites. The findings revealed that AI policies are not standardized across publishers; instead, each adopts its own unique rules regarding AI-assisted writing, authorship, peer review, and disclosure.
    Discussion: While prior studies have documented the prevalence of disclosure requirements and authorship prohibitions, the present study moves beyond inventory to critically examine how international frameworks are reflected, adapted, and contested within individual publisher policies, and to surface tensions around enforceability, equity, and disciplinary variability that remain underexplored in existing literature. Consequently, researchers are required to carefully consult the specific policies of their target publishers before submission. The study recommends that all stakeholders in the publishing process be informed about AI-related policies relevant to their roles. Authors should ensure that AI outputs are accurate, reviewers must remain vigilant about unauthorized AI use, and publishers should proactively communicate best practices to maintain integrity and transparency in the scholarly publishing process.
    Keywords:  artificial intelligence tools; author guidelines; cope; digital publishing; scholarly communication
    DOI:  https://doi.org/10.3389/frma.2026.1740510
  20. Head Neck Pathol. 2026 Jun 06. pii: 63. [Epub ahead of print]20(1):
    In Defense of AI as an 'Author' Ethical Implications for Scientific Authors, Reviewers, Editors, and Publishing Policies.
    Adam C Puche, Ahmed S Sultan.
       BACKGROUND: The rapid integration of generative artificial intelligence (AI) into scientific writing has ignited intense debate across biomedical publishing, with journals adopting divergent and often contradictory policies ranging from outright prohibition to conditional acceptance with disclosure.
    PURPOSE: In this Perspective, we examine the ethical and practical implications of AI‑assisted authorship specifically as they relate to Head & Neck Pathology and Springer Nature publishing policies. We examine whether AI‑assisted writing truly represents an ethical threat to scientific integrity, or whether the current controversy reflects a misplaced focus on the mechanics of writing rather than on scientific substance.
    DISCUSSION: We argue that efforts to regulate AI use are fundamentally undermined by the inability to reliably detect AI‑generated text and by the growing convergence between human and machine writing styles. More importantly, we contend that authorship should remain grounded in intellectual contribution, intent, and responsibility for scientific claims and not in the tools used to draft prose. By contextualizing generative AI as a natural extension of long‑accepted assistive technologies, we highlight the ethical risks of over‑enforcement, including false accusations and barriers to dissemination of valid science.
    CONCLUSION: Ultimately, we call for a recalibration of editorial priorities toward scientific rigor, accountability, and public benefit, rather than fixation on the provenance of text.
    Keywords:  AI-assisted scientific writing; Editorial standards; Generative artificial intelligence; Publication ethics; Scientific authorship; Scientific integrity
    DOI:  https://doi.org/10.1007/s12105-026-01924-0
  21. Osteoarthr Cartil Open. 2026 Jun;8(2): 100661
    Preserving scientific integrity in academic publishing: Navigating artificial intelligence, journal policies, and the impact factor as a quality indicator.
    Mahmut Enes Kayaalp, Stefano Zaffagnini, Michael A Mont, Jon Karlsson, Bruce Reider, Olufemi Ayeni, Thomas Heyse, Henning Madry, Elmar Herbst, Giuseppe Milano, Volker Musahl, Roland Becker, Michael T Hirschmann.
      The integration of artificial intelligence (AI), the rise of mega-journals, and the manipulation of impact factors present challenges to scientific integrity. These trends threaten the core principles of objectivity, reproducibility, and transparency. This editorial highlights two categories of threats: (1) external pressures, such as AI misuse and metric-driven publishing models, and (2) internal systemic flaws, including the 'publish or perish' culture and methodological fragility. Mega-journals, characterized by high-volume publishing and broad interdisciplinary scopes, improve accessibility and accelerate dissemination. However, the emphasis on publication volume might weaken the rigor of peer review. To navigate these challenges, the authors propose a balanced approach that harnesses innovation without compromising scientific integrity. Proposed solutions include mandating AI transparency through frameworks like CONSORT-AI, and redefining impact metrics to emphasize reproducibility, mentorship, and societal impact alongside citations. Scientific journals should promote career opportunities less on publication quantity and more on quality. Global cooperation, via initiatives like the San Francisco Declaration on Research Assessment (DORA) and the Committee on Publication Ethics (COPE), is essential to standardize ethics and address resource disparities. This editorial proposes solutions for researchers, journals, and policymakers to realign academic incentives and uphold the ethical foundation of the science. By fostering transparency, accountability, and equity, the scientific community can preserve its ethical foundations while embracing transformative tools-ultimately advancing knowledge and serving society.
    Level of evidence: 5.
    Keywords:  Artificial; Bibliometrics; Ethics in publishing; Intelligence; Peer reviews; Periodicals as topic
    DOI:  https://doi.org/10.1016/j.ocarto.2025.100661
  22. Evid Based Dent. 2026 Jun 04.
    AI in peer review: the elephant in the editorial room.
    Giusy Rita Maria La Rosa, Mona Nasser.
      
    DOI:  https://doi.org/10.1038/s41432-026-01227-x
  23. Ophthalmology. 2026 Jun 03. pii: S0161-6420(26)00385-4. [Epub ahead of print]
    Large Language Model Authorship in Ophthalmic Publications.
    Christopher R Fortenbach, Yue S Wu, Parth M Mungra, Russell N Van Gelder.
       PURPOSE: To assess for the likely presence of artificial intelligence (AI)-generated text in the published ophthalmology literature.
    METHODS: Abstract text from 27,142 research articles published in 22 journals between May 2020 and May 2025 were evaluated for changes in word-frequency usage with a focus on stylistic words previously found to be associated with LLM-generated text. Four commercial AI-detection services (ZeroGPT, Writer.com, Winston AI, GPTZero) were first validated against control articles with GPTZero showing the best performance, which was then used to detect the presence of AI-generated text in 50 full articles from each journal. For the large-scale screening, research articles and commentary publications (e.g., editorials) were scored at the section and sentence level and compared in the pre- versus post-ChatGPT publication time periods.
    RESULTS: Since the release of ChatGPT in 2022, a marked increase in previously rarely used stylistic words was observed with at least a two-fold usage increase observed in 20% of ophthalmology abstracts. With full article text evaluation, GPTZero scores increased after the release of ChatGPT across all research article sections (e.g., abstract, introduction, etc) and commentary articles. By 2025, 25.7% of sampled research articles and 21.6% of commentary articles contained AI-likelihood scores of >2 standard deviations above the baseline. Sentence-level analysis showed that among those publications containing outlier scores, 22.3% of sentences in research articles and 90% of sentences in commentary articles were likely written by AI. AI use was not disclosed among any of the publications with outlier scores.
    CONCLUSIONS: AI brings significant promise in its ability to facilitate both scientific and medical advances. As these tools become more powerful, disclosure regarding the manner of their use becomes increasingly important. Here we show that LLM-generated text is increasingly present in the ophthalmic literature and is rarely disclosed. Without disclosure requirements and editorial oversight, there is a significant risk that undisclosed LLM usage will continue to increase and may jeopardize authorship integrity and long-term reliability of published findings.
    Keywords:  AI detection; ChatGPT; Large language models; artificial intelligence; ophthalmology
    DOI:  https://doi.org/10.1016/j.ophtha.2026.05.037
  24. Naunyn Schmiedebergs Arch Pharmacol. 2026 May 30.
    AI hallucinations in academic writing: implications for research integrity.
    Louie Giray, Md Emdadul Islam, John Arvin Glo.
      As artificial intelligence becomes deeply embedded in scholarly practice, a critical and underexamined threat to research integrity has emerged: AI hallucinations. AI hallucinations refer to outputs generated by large language models that are factually incorrect, fabricated, or logically inconsistent with verifiable knowledge, produced not through genuine understanding but through statistical pattern prediction. This paper examines how these hallucinations manifest in academic writing and analyzes their specific consequences for scholarly work. The paper identifies the principal causes of hallucination, including training data gaps, monofacts, named entity errors, and prompt design failures, and documents their most common forms in academic contexts, among them citation fabrication, factual distortion, logical inconsistency, and propagation errors. The paper then examines how these failures undermine the accuracy and reliability of research and disrupt peer review processes in ways that traditional editorial mechanisms are not equipped to detect. Ethical dimensions are addressed directly: AI hallucinations create conditions of distributed epistemic responsibility that complicate established definitions of research misconduct and authorship, yet accountability remains fully with human authors. Also, it discusses mitigation strategies, including detection tools, institutional policy frameworks, and AI literacy curricula, arguing that human verification is irreplaceable and that literacy-based approaches offer the most sustainable institutional response. Equity concerns are highlighted throughout, as hallucination rates vary by language and disciplinary domain. The paper concludes that responsible AI use in scholarship requires transparency, systematic verification, and human oversight as non-negotiable ethical obligations.
    Keywords:  AI hallucinations; Academic writing; Large language models; Research ethics; Research integrity; Scientific publishing
    DOI:  https://doi.org/10.1007/s00210-026-05494-4
  25. Med Teach. 2026 Jun 05. 1
    Polished reviews are not enough: Assessing durable learning in mentor-guided AI writing.
    Kenneth Ian Talosig Batac.
      
    DOI:  https://doi.org/10.1080/0142159X.2026.2681970
  26. PLoS Biol. 2026 Jun;24(6): e3003801
    Will the widespread use of large language models in scientific writing undermine scientists' critical thinking?
    Lucas M Bietti, Adrian Bangerter.
      Artificial intelligence (AI) is rapidly transforming scientific writing by expanding access and efficiency, yet it risks decoupling writing from thinking. Scientific writing is a core cognitive and epistemic practice that must be cultivated and preserved alongside AI use.
    DOI:  https://doi.org/10.1371/journal.pbio.3003801
  27. Res Integr Peer Rev. 2026 Jun 03.
    Susceptibility of large language models to hidden nudge injection during simulated medical peer review: a quasi-experimental study.
    Bruno Martins Tomazini, Larissa Bianchini, Lucas Tramujas, Natalia Vieira Rodrigues, Felipe Guindalini Lorenzato, Mariana Silveira de Alcantara Chaud, Karoline Cordeiro Vercka Gervásio, Israel Silva Maia, Fernando José da Silva Ramos, Bruno Adler Maccagnan Pinheiro Besen, Alexandre Biasi Cavalcanti.
       BACKGROUND: Generative artificial intelligence (AI) technologies might offer new possibilities for the peer review process; however, AI models' possible vulnerability to hidden nudges designed to elicit positive reviews raises concerns about manipulation susceptibility, which remains unexplored. We aimed to evaluate AI model susceptibility to hidden nudges in peer review.
    METHODS: This quasi-experimental study was conducted between July and December 2025. Four commercial AI models were evaluated simultaneously: GPT-4 (OpenAI), Gemini 2.5 Flash (Google), DeepSeek-V3 (DeepSeek), and Claude Opus 4 (Anthropic). We used 90 pre-print and 90 published manuscripts in critical care and cardiology to feed the AI models. All manuscripts were converted to individual Microsoft Word files, with identifying information removed, to mimic a manuscript submitted to a journal for peer review. Each manuscript underwent three independent evaluations per model using standardized prompts requesting evaluation and recommendation on whether to accept or reject it for publication. First, we evaluated the manuscript without any nudge. Second, we inserted a hidden nudge opposing the initial recommendation (e.g., a negative nudge if initially accepted). Finally, we evaluated the nudged manuscripts using a modified prompt warning about potential hidden nudges. All recommendations were categorized as accept or reject. The main outcomes were the change rates in recommendations after nudge insertion compared to initial recommendations, and after nudge insertion with the modified prompt, analyzed separately for each AI model.
    RESULTS: Across all AI models tested, nudge insertion led to a change in the recommendation in 84.4% of the time (608/720), with Deepseek being the most susceptible model (100% of change), followed by Gemini (97.8% of change), Chat GPT (82.8% of change) and Claude (57.2% of change). Using a specific prompt to warn AI models about potential malicious nudge injections in the manuscripts did not substantially alter the results. Recommendations were still modified in 76.8% of cases (553/720).
    CONCLUSIONS: In this quasi-experimental study, all tested AI models were highly susceptible to hidden nudge insertions in manuscripts during simulated peer review. Importantly, explicitly warning AI models about potential nudge injections does not meaningfully reduce their susceptibility to manipulation.
    Keywords:  Artificial intelligence; Peer review; Vulnerability
    DOI:  https://doi.org/10.1186/s41073-026-00225-y
  28. J Athl Train. 2026 Jun;61(6): 369-373
    Strengthening Peer Review: Strategic Approaches for Authors, Reviewers, Editors, Journals, and Academic Institutions.
    Zachary Yukio Kerr, Benjamin S James, Sarah J de la Motte, Melissa K Kossman.
      
    DOI:  https://doi.org/10.4085/1062-6050-0672.25
  29. An Acad Bras Cienc. 2026 Jun 01. pii: S0001-37652026000100201. [Epub ahead of print]98(1): e20269801
    The Lack of Reviewers Pandemic (LRP) - what can be done?
    Alexander W A Kellner.
      
    DOI:  https://doi.org/10.1590/0001-3765202620269801
  30. Clin Pharmacol Drug Dev. 2026 Jun;15(6): e70068
    Scientific Fraud: How Do We Ensure Sound Medical Literature?
    Michael J Fossler, Katy P Moore.
      
    DOI:  https://doi.org/10.1002/cpdd.70068
  31. Asian Nurs Res (Korean Soc Nurs Sci). 2026 May;pii: S1976-1317(26)00036-8. [Epub ahead of print]20(2): 117-118
    The Human Value of Peer Review in Nursing.
    Kyoung Suk Lee.
      
    DOI:  https://doi.org/10.1016/j.anr.2026.04.004
  32. BMC Med Res Methodol. 2026 Jun 05.
    EQUATOR reporting guideline use and editorial enforcement in four medical specialties: a cross-sectional study of 20 high-impact journals.
    Antonio Cisneros-Barrios, Pamela Hernández-Delgado, Paloma Gradilla-Magaña, Ismael Gutierrez-Jimenez, Cesar Ramos-Remus.
       BACKGROUND: EQUATOR (Enhancing the QUAlity and Transparency Of Health Research) reporting guidelines aim to improve transparency and completeness in biomedical research; however, their adoption remains inconsistent across medical specialties. We quantified declared reporting guideline use in high-impact ophthalmology journals and assessed whether editorial policies are associated with their implementation across specialties.
    METHODS: We conducted a cross-sectional study of original research articles published in 2024 across five first-quartile ophthalmology journals. Reporting guideline use was identified through systematic full-text searches. An "advisable use rate" was defined as the proportion of articles declaring guideline use among those for which use was methodologically appropriate. Journal enforcement policies were characterized through analysis of instructions for authors. Guideline use in ophthalmology was contextualized through comparison with previously published datasets from orthopedics, rheumatology, and infectious diseases.
    RESULTS: Among 794 original research articles, reporting guidelines were deemed advisable for 672 (84.6%). Of these, 192 articles (28.6%) declared guideline use. Advisable use rates ranged from 5% to 120% across journals. STROBE was the most frequently applicable guideline but was declared in only 27% of eligible articles. Ophthalmology guideline use exceeded orthopedics (10.2%), rheumatology (7.2%), and infectious diseases (6.3%). Although enforcement policies varied across journals, no significant correlation was observed between enforcement level and guideline use (Kendall's τ = 0.24, p > 0.05).
    CONCLUSIONS: Despite higher adoption relative to other specialties, reporting guideline use in ophthalmology remains limited. Substantial inter-journal variability and the absence of an association between enforcement policies and use highlight opportunities to better align editorial expectations with reporting practices.
    Keywords:  EQUATOR Network; Editorial Policies; Ophthalmology; Publishing; Reporting Guidelines; Research
    DOI:  https://doi.org/10.1186/s12874-026-02901-5
  33. J Empir Res Hum Res Ethics. 2026 Jun 03. 15562646261452724
    Attitudes of Longitudinal Study Participants and Members of the Public Towards Data Sharing for Secondary Research: A Survey Based Approach.
    Nicola Howe, Thomas Chadwick, Dorothy Newbury-Birch, Elaine McColl.
      Most research funders and journals now require researchers to make their data available for sharing. There is a growing body of literature on research participants' attitudes towards health data sharing, but less evidence regarding views of participants taking part in longitudinal studies, clinical trials or public health research.1,664 respondents from the UK (participants in longitudinal studies ALSPAC and ACONF and members of Patient and Public Involvement (PPI) groups completed a questionnaire survey exploring attitudes towards data sharing, including consent and data storage. Respondents were most concerned about privacy and data security and highlighted concerns about open access and sharing with commercial organisations.
    Keywords:  ALSPAC; Data sharing; informed consent; longitudinal study; participants; patient perspective; secondary use
    DOI:  https://doi.org/10.1177/15562646261452724
  34. Res Integr Peer Rev. 2026 Jun 06.
    Research integrity and transparency in CAM journals: an analysis of publication bias and reporting practices (1995-2023) in four leading journals.
    Stephen Neilson, Kevin Smith.
       BACKGROUND: Complementary and alternative medicine (CAM) remains widely used worldwide, yet longstanding concerns persist regarding the balance and reliability of the evidence presented in CAM journals.
    OBJECTIVE: To examine long-term trends in publication practices within leading CAM journals, with particular attention to changes in publication types and the prevalence of positive versus negative study outcomes as indirect indicators of potential publication bias.
    METHODS: We conducted a complete census of articles published in four leading CAM journals at two contemporary time points (2018 and 2023), replicating the design and classification framework of a seminal 2001 analysis covering 1995 and 2000. Articles were categorised by publication type, subject area, and author-reported study outcome (positive, negative, or inconclusive, corresponding to the "open" category used in the original 2001 study). Descriptive analyses were used to compare trends over time and with earlier findings.
    RESULTS: The total number of published articles increased substantially between the earlier and contemporary periods. The proportion of empirical studies, particularly clinical trials, rose over time. However, the prevalence of positive outcomes also increased markedly, with positive findings accounting for over 80% of published articles in the contemporary period, compared with 49% in the earlier study. Negative and inconclusive outcomes remained relatively infrequent.
    CONCLUSIONS: Despite growth in publication volume and a shift toward empirical study designs, CAM journals continue to exhibit a pronounced predominance of positive outcome reporting. These findings suggest that longstanding concerns regarding publication bias in CAM publishing have not diminished over time and appear to have intensified, with selective publication and related reporting and dissemination practices plausibly contributing to the observed patterns. This has important implications for research integrity and evidence-based decision-making in medical practice.
    Keywords:  Alternative medicine; Complementary medicine; Integrative medicine; Journal analysis; Positive outcomes; Publication bias
    DOI:  https://doi.org/10.1186/s41073-026-00221-2
  35. Proc Natl Acad Sci U S A. 2026 Jun 09. 123(23): e2614324123
    With qualitative research, the risks of data sharing can outweigh the rewards.
    Jessica Calarco.
      
    DOI:  https://doi.org/10.1073/pnas.2614324123
  36. Intern Med J. 2026 Jun 03.
    Case reports in clinical medicine: why it matters and how to do it.
    Isaac K S Ng, An Jian Leung, Wilson G W Goh, Charlotte S L Tan, Li Feng Tan, Desmond B Teo.
      A medical case report is a form of scholarly writing describing unique clinical vignettes that offer important learning points in patient management and generate hypotheses to spur further research. Despite its long-standing tradition dating back to 400-1600 BC, the case report has fallen out of favour in modern medical journals due to perceived lower status in the evidence hierarchy and concerns of limited citation potential affecting journal impact factors. In this commentary, we argue for the enduring relevance of case reports in contemporary medical practice, specifically in four main areas: (1) serving as catalysts for scientific discovery, (2) contributions to clinical diagnosis/management, (3) educational value in cultivating clinical reasoning skills and (4) accessibility as a scholarly design for junior medical trainees. We then describe practical strategies for medical trainees and practitioners pertaining to case selection, consent-taking processes, co-author inclusion and writing styles to improve the chances of successful case report publication.
    Keywords:  case report; clinical medicine; medical education
    DOI:  https://doi.org/10.1111/imj.70467
  37. J Clin Epidemiol. 2026 Jun 03. pii: S0895-4356(26)00228-3. [Epub ahead of print] 112353
    Data sharing in stepped-wedge cluster randomized trials: suboptimal data availability despite "data available upon request".
    Cory E Goldstein, Anna Catharina V Armond, Kelly D Cobey, Emily C Voldal, Yutong Chen, Kylie Tingley, Julia F Shaw, Patrick J Heagerty, Karla Hemming, Avi Kenny, Fan Li, Yongdong Ouyang, Fan Xia, David Moher, James P Hughes, Monica Taljaard.
       BACKGROUND: Data sharing enhances transparency, facilitates reproducibility, and promotes innovation in health research. For statisticians, access to data from real trials is essential to develop, validate, and refine statistical methods.
    OBJECTIVES: Within a collection of published stepped-wedge cluster randomized trials (SW-CRTs), we aimed to describe the prevalence and types of data sharing statements; the actual availability of data after emailing authors; and factors associated with data obtainment.
    METHODS: We identified SW-CRTs published between 2016-2022 from a previous systematic review and updated that search to include studies published through 31 December 2023. Data sharing statements, when provided, were classified as indicating data were publicly available, available upon request, or not available. Authors were emailed to request datasets. Associations between trial characteristics and data obtainment were explored using bivariable logistic regression and results reported as Odds Ratio (OR) with 95% Confidence Interval (CI).
    RESULTS: Of 217 SW-CRTs identified, 98 (45%) had no clear data sharing statements, 89 (41%) indicated data were available upon request, 16 (7%) indicated data were not available, and 14 (7%) indicated data were publicly available. Datasets were ultimately obtained for 76 (35%) SW-CRTs. Data obtainment did not differ between studies with no data sharing statement and those indicating data were available upon request (both 34%). The odds of data obtainment were significantly higher among trials conducted in low- and middle-income countries (OR=2.9, 95% CI 1.5-5.4). The odds of data obtainment increased with years since publication (OR=1.13; 95% CI 0.99-1.29) and years since trial initiation (OR=1.11; 95% CI 1.00-1.23) although confidence intervals overlapped with the null. There was no clear evidence of an association with having positive primary trial results (OR=0.62; 95% CI 0.35-1.10), nor with journal impact factor, trial size, type of design, region of corresponding author, and funding source.
    CONCLUSION: Data sharing practices in SW-CRTs are suboptimal. The presence of a data sharing statement is not predictive of actual data availability. There is significant regional variation in whether data were obtained but few other characteristics explain variation in data obtainment. Clear guidance and dedicated resources to facilitate data sharing in research are required.
    Keywords:  cluster randomized trials; data sharing; open data; stepped-wedge trials
    DOI:  https://doi.org/10.1016/j.jclinepi.2026.112353
  38. Clin Nurse Spec. 2026 Jul-Aug 01;40(4):40(4): 121-122
    Preparing to Prepare a Manuscript.
    Janet S Fulton.
      
    DOI:  https://doi.org/10.1097/NUR.0000000000000973
  39. Perspect Med Educ. 2026 ;15(1): 460-464
    How Did You Get There? The Value of Segues for Illustrating Your Logic.
    Kevin W Eva.
      In the writer's craft section we offer simple tips to improve your writing in one of three areas: Energy, Clarity and Persuasiveness. Each entry focuses on a key writing feature or strategy, illustrates how it commonly goes wrong, teaches the grammatical underpinnings necessary to understand it and offers suggestions to wield it effectively.
    DOI:  https://doi.org/10.5334/pme.2647
  40. J Parkinsons Dis. 2026 Jun 04. 1877718X261450352
    Aligning incentives for open science in biomedical research: Navigating funder and institutional perspectives.
    Dylan Roskams-Edris, Sam Riedijk, Natalie Terzikhan.
      As science evolves, so must the systems that support it and evaluate it. Inspired by UNESCO's open science definition, this paper explores how funders and institutions can move beyond the traditional metrics to define scientific impact and to create a more inclusive, transparent and collaborative research ecosystem. We demonstrate through practical examples how the academic landscape is moving towards more openness as the new standard. We conclude with a discussion of challenges in implementing open science practices and recommendations for funders and institutions that will help to create a more unified framework of recognition and reward of scientific work.
    Keywords:  funders; incentives; open dialogue; open engagement; open infrastructure; open knowledge; open science; research evaluation
    DOI:  https://doi.org/10.1177/1877718X261450352
  41. Account Res. 2026 Jun 02. 2681050
    Improving acknowledgments sections to better credit research contributors.
    Alex O Holcombe, Rasmus Pedersen, Malgorzata Lagisz, Pietro Pollo, Marton Kovacs, Mohammad Hosseini.
      Formal recognition of research contributions is critical for career advancement and the allocation of research funding. However, some contributions are mentioned only in the acknowledgments section, which are not indexed by scholarly databases, resulting in little recognition for those involved. We contextualize this shortfall in terms of contributorship, the movement to recognize specific research contributions rather than rely solely on authorship. Broadening the range of recognized individuals is currently advanced largely through reducing authorship restrictions and unbundling manuscripts into smaller elements, such as datasets and protocols, that receive their own attributions. Here we focus on a complementary path, enhancing the contents and metadata of acknowledgments sections. Capitalizing on existing infrastructure and standards, we propose: 1) when acknowledging individuals, authors include ORCIDs (subject to the acknowledgees' approval) and provide CRediT information where applicable; 2) publishers solicit identities of acknowledgees in a similar way to how they do so for authors in their submission portals; and 3) publishers include metadata of acknowledgees in JATS-XML files. Implementing these steps should encourage scholarly databases to index non-author contributors. The ensuing increase in visibility for research contributors, such as technicians and library professionals, should result in greater recognition of non-author roles.
    Keywords:  Authorship; accountability; contributorship; metadata; persistent identifiers
    DOI:  https://doi.org/10.1080/08989621.2026.2681050
  42. Mol Oncol. 2026 Jun;20(6): 1385-1387
    Creating a smoother path to scientific publication.
    Thomas Lemberger, Kevin M Ryan.
      After years of hard work, publishing your manuscript is a critical part of the scientific process to tell others about your findings, to allow scrutiny of your results and in addition, to show your capabilities as a scientist, helping forward your career. Often, however, the process is fraught with rejection, frustration and upset. Within this short editorial, we highlight a few suggestions and initiatives that we hope will make the process of publishing easier and more efficient.
    Keywords:  open access; review commons; reviewed preprint; scientific editors; scientific journal; scientific society publishing
    DOI:  https://doi.org/10.1002/1878-0261.70280
  43. Acad Psychiatry. 2026 Jun 04.
    Psychiatrists Must Address Predatory Journals with Trainees and Early-Career Collaborators.
    Eduardo de Castro Humes.
      
    DOI:  https://doi.org/10.1007/s40596-026-02364-2
  44. J Physiol. 2026 May 30.
    Who pays for participation? Hidden personal costs in (exercise) physiology.
    Arthur Henrique Bossi.
      
    Keywords:  academic inequality; global participation; hidden costs; language barriers; open access; publishing barriers; research equity; self‐funding
    DOI:  https://doi.org/10.1113/JP291329
  45. ACG Case Rep J. 2026 Jun;13(6): e02154
    Advancing Academic Gastroenterology: Reflections From a Social Media Ambassador for ACG Case Reports Journal.
    Taha Bin Arif, Harsimran Kalsi, Aya Akhras, Dushyant Singh Dahiya, Daniyal Abbas.
      
    DOI:  https://doi.org/10.14309/crj.0000000000002154
This page is being maintained by Thomas Krichel. It was last updated on 2026‒06‒08 at 23:42.