Research integrity and peer review最新文献

{"title":"Comment on: Potential reverse spin of cannabinoids vs. pharmaceutical analgesics for pain treatment: a systematic review based critical interpretive synthesis of meta-analyses.","authors":"Andrew Moore, Emma Fisher, Sebastian Straube, Geert Crombez, Christopher Eccleston","doi":"10.1186/s41073-026-00264-5","DOIUrl":"10.1186/s41073-026-00264-5","url":null,"abstract":"","PeriodicalId":74682,"journal":{"name":"Research integrity and peer review","volume":"11 1","pages":""},"PeriodicalIF":9.6,"publicationDate":"2026-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13737618/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149336382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Does lower citation mean lower value of an AI-assisted comment?","authors":"Shigeki Matsubara","doi":"10.1186/s41073-026-00267-2","DOIUrl":"10.1186/s41073-026-00267-2","url":null,"abstract":"","PeriodicalId":74682,"journal":{"name":"Research integrity and peer review","volume":"11 1","pages":""},"PeriodicalIF":9.6,"publicationDate":"2026-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13729630/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149328328","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Attitudes and perceptions toward the use of artificial intelligence chatbots for peer review in medical journals: a large-scale, international cross-sectional survey.","authors":"Jeremy Y Ng, Daivat Bhavsar, Neha Dhanvanthry, Lex Bouter, Teresa Chan, Holger Cramer, Annette Flanagin, Alfonso Iorio, Cynthia Lokker, Hervé Maisonneuve, Ana Marušić, David Moher","doi":"10.1186/s41073-026-00256-5","DOIUrl":"https://doi.org/10.1186/s41073-026-00256-5","url":null,"abstract":"<p><strong>Background: </strong>Artificial intelligence chatbots (AICs) are increasingly being considered for use in scholarly peer review to assist with tasks such as identifying methodological issues, verifying references, and improving language clarity. However, concerns remain regarding their reliability, ethical implications, and transparency. Evidence on how medical journal peer reviewers perceive the role and impact of AICs is limited. This study explored reviewers' familiarity with AICs, perceived benefits and challenges, ethical concerns, and anticipated future roles in peer review.</p><p><strong>Methods: </strong>We conducted a cross-sectional online survey of medical journal peer reviewers. Corresponding author information was extracted from MEDLINE-indexed articles added to PubMed within a six-week period. A total of 72,851 authors were invited via email to participate; those who self-identified as peer reviewers were eligible. The 29-item survey assessed familiarity with AICs and perceptions of their benefits and limitations in peer review. The survey was administered via SurveyMonkey from April 28 to June 16, 2025, with two reminder emails sent during the data collection period.</p><p><strong>Results: </strong>Of 66,679 email invitations, a total of 1260 respondents provided survey responses (response rate: 1.9%), of whom 1157 met the eligibility criteria, and 1077 answered the main survey questions. Most participants were familiar with AICs (86.2%) and had used them for general purposes (87.7%), though most report not using AICs for peer review purposes (70.3%). Most respondents reported that their institutions do not provide training on AIC use in peer review (69.5%), although many expressed interest in such training (60.7%). Perceptions of AIC benefits were mixed, while concerns were widely shared, particularly regarding potential algorithmic bias (80.3%) and issues related to trust and user acceptance (73.3%).</p><p><strong>Conclusions: </strong>While familiarity with AICs is high among medical journal peer reviewers, their reported use in peer review remains limited. There is clear interest in training and guidance, however, concerns related to ethics, data privacy, and research integrity persist and should be addressed before broader implementation.</p>","PeriodicalId":74682,"journal":{"name":"Research integrity and peer review","volume":"11 1","pages":""},"PeriodicalIF":9.6,"publicationDate":"2026-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13717964/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149302921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Equipping the next generation: addressing the unmet need for artificial intelligence education at research performing organizations.","authors":"Jeremy Y Ng, Wid Al-Zahraa Al-Khafaji, David Moher","doi":"10.1186/s41073-026-00250-x","DOIUrl":"10.1186/s41073-026-00250-x","url":null,"abstract":"<p><strong>Background: </strong>The integration of generative artificial intelligence (GenAI) tools into higher education is rapidly accelerating, yet the educational ecosystem appears largely unprepared for the scale and speed of adoption. Our recent international survey of over 1,200 university students and postdoctoral fellows in the medical and life sciences found that while more than 80% had used GenAI tools, the vast majority had received no formal training, and many were unaware of any institutional policies governing their use. This gap between adoption and institutional preparedness may pose risks to research integrity if left unaddressed.</p><p><strong>Main body: </strong>Existing research supports a coordinated, evidence-informed approach to AI education in research performing organizations (RPOs), grounded in principles of research integrity, equity, and critical engagement with technology. First, GenAI literacy must be embedded as a core competency in scientific and clinical education, equipping students to critically evaluate tool outputs, recognize hallucination and bias, and understand the distinction between AI-generated inaccuracy and deliberate research misconduct. Second, traditional frameworks for academic integrity would benefit from re-examination. Today, GenAI tools have fundamentally disrupted established notions of authorship, originality, and plagiarism, and the absence of coherent institutional guidance leaves students and educators navigating these questions without support. Third, RPOs must develop clear, transparent, and context-sensitive policies on GenAI use by embedding responsible AI education into curricula, equipping learners not only to use these tools effectively, but to question, verify, and critique their outputs in ways that uphold scientific standards.</p><p><strong>Conclusion: </strong>RPOs have an urgent responsibility to move beyond reactive responses and toward proactive strategies that uphold scientific standards, promote equity of access, and prepare the next generation of researchers and clinicians to engage with GenAI responsibly and ethically.</p>","PeriodicalId":74682,"journal":{"name":"Research integrity and peer review","volume":"11 1","pages":""},"PeriodicalIF":9.6,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13676008/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149208293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"'Correcting the record on \"Publication integrity and industry influences on the editorial process: a case study\" Res Integr Peer Rev. 2026;11:49.' Reply.","authors":"Evan D Kharasch, Michael M Todd, Jean-Francois Pittet, William L Lanier","doi":"10.1186/s41073-026-00255-6","DOIUrl":"10.1186/s41073-026-00255-6","url":null,"abstract":"","PeriodicalId":74682,"journal":{"name":"Research integrity and peer review","volume":"11 1","pages":""},"PeriodicalIF":9.6,"publicationDate":"2026-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13625434/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149119642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Institutional conflicts of interest in health-related research - a scoping review.","authors":"Alexander Haarmann, Charlotte M Kugler, Hengameh Goodarzi, Alexander Pachanov, Kaethe Goossen, Elie A Akl, Dawid Pieper","doi":"10.1186/s41073-026-00251-w","DOIUrl":"10.1186/s41073-026-00251-w","url":null,"abstract":"<p><strong>Background: </strong>Institutional conflicts of interest (COIs) have received less attention than individual COIs in health-related research.</p><p><strong>Objective: </strong>To explore how institutional COIs arising from affiliation with a healthcare provider have been studied or discussed in the literature on health-research involving humans.</p><p><strong>Methods: </strong>We conducted a scoping review following the JBI guidance and reported it according to PRISMA-ScR. The review included English‑ or German‑language empirical or conceptual publications that addressed institutional COIs -either independently or in conjunction with individual COI - within health‑related research involving humans conducted at institutions that deliver healthcare services. We systematically searched PubMed, Embase (Elsevier), and Google Scholar in July 2024. Two reviewers independently screened publications. One reviewer extracted data and another checked it. One author mapped and analysed included papers according to the categories of institutional and individual COIs that they addressed, which another author verified.</p><p><strong>Results: </strong>We included 48 publications published between 1998 and 2022. The majority (88%; n = 42/48) focused on North America, were empirical (67%; n = 32/48), and referred to institutions such as hospitals and clinics (58%; n = 28/48), or universities and academic institutions (58%; n = 28/48). Most institutional COIs described were linked to health-related industries (79%; n = 38/48). Almost all publications mentioned direct financial institutional COIs (98%; n = 47/48) primarily in relation to receiving gifts, endowments, or grants (94%; n = 45/48). One third of publications (n = 16/48) described indirect financial institutional COIs, most frequently through increasing services (27%; n = 13/48). Direct financial individual COI were represented in 73% (n = 35/48) of publications, and indirect financial individual COIs in 6% (n = 3/48). Half of the publications (52%; n = 25/48) illustrated non-financial COIs, particularly related to prestige and reputation (31%; n = 15/48), or career advancements and professional roles (23%; n = 11/48). All publications acknowledged that institutional COIs can have negative consequences, most frequently due to bias and distortion in the research process (94%; n = 45/48). The vast majority of publications (94%; n = 45/48) offered recommendations for managing COIs, including institutional policies (77%; n = 37/48).</p><p><strong>Conclusion: </strong>Direct financial COIs dominate the literature on institutional COIs, while indirect or non-financial COIs remain under-researched. Institutional COIs are consistently recognised as problematic and institutional policies are most frequently proposed as means to manage them.</p>","PeriodicalId":74682,"journal":{"name":"Research integrity and peer review","volume":"11 1","pages":""},"PeriodicalIF":9.6,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13584590/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148992984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Participants using GenAI in online studies: an overview and recommendations for researchers and reviewers.","authors":"Justus Mann, Jutta Stumpf-Wollersheim","doi":"10.1186/s41073-026-00247-6","DOIUrl":"10.1186/s41073-026-00247-6","url":null,"abstract":"<p><strong>Background: </strong>Participants' use of generative artificial intelligence (GenAI) to create responses in online studies can threaten data authenticity and research validity. This issue is particularly pressing in settings where participation is paid for. In response, researchers have begun to develop different approaches to prevent and detect GenAI use by participants.</p><p><strong>Objective: </strong>This comment illustrates the unintended consequences of researchers' measures to prevent and detect participants' GenAI use and aims to help researchers and reviewers better identify the potential consequences of these measures.</p><p><strong>Results: </strong>Drawing on current literature, we identify seven different levels of participants' GenAI use, differentiated by increasing degrees of technological sophistication and automation. These levels range on a continuum from the manual operation of GenAI by participants to the employment of automated GenAI agents. We discuss prevention and detection measures corresponding to these levels and how researchers' measures can cause reactions from participants. Specifically, we suggest that extensive measures can trigger an adverse selection mechanism by driving out honest participants and inviting greater sophistication in GenAI use.</p><p><strong>Conclusions: </strong>Instead of engaging in a technological cat-and-mouse game with participants through deterrence, we argue that we should focus on the incentive structure to resolve the issue. We propose a combination of better payment and an opt-in verified participation mode, i.e., video proof, to reduce participants' GenAI use in online studies and increase data quality. Building on this perspective, we provide practical recommendations for researchers and reviewers to improve research quality, maintain fairness, and save resources.</p>","PeriodicalId":74682,"journal":{"name":"Research integrity and peer review","volume":"11 1","pages":""},"PeriodicalIF":9.6,"publicationDate":"2026-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13579951/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148984400","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Applicants as reviewers: a mixed methods evaluation of the risks, benefits, and potential of distributed peer review for grant funding allocations.","authors":"Anna Butters, Melanie Benson Marshall, Stephen Pinfield, Tom Stafford, Alexander Bondarenko, Barbara Neubauer, Robert Nuske, Pierre Schwidlinski, Hanna Denecke","doi":"10.1186/s41073-026-00246-7","DOIUrl":"10.1186/s41073-026-00246-7","url":null,"abstract":"<p><strong>Background: </strong>Peer review-based funding evaluation systems are under increasing pressure. To help alleviate this, innovative approaches like Distributed Peer Review (DPR) - where applicants review proposals for the same funding call - are being explored. The Volkswagen Foundation trialled DPR alongside a conventional panel review process for an interdisciplinary call. Evaluation of this trial provides insights into the dynamics of (distributed) peer review.</p><p><strong>Methods: </strong>All proposals (N = 140) underwent both DPR and the panel review process. In DPR, applicants (N = 323) reviewed four or five proposals, providing an overall score, scores for each funding criteria, and a comment. Proposals were ranked using a trimmed mean score. Expectation and feedback surveys were administered. The panel process involved shortlisting by VWS staff, review by panellists (N = 8), and a final panel discussion. Semi-structured interviews with applicants, panellists, and VWS staff (N = 20) explored perceptions and experiences of DPR, using thematic analysis. Quantitative analysis of review data and surveys utilised bootstrapping to assess decision stability and mixed effects models for consistency between reviewers. Qualitative and quantitative results were integrated in a convergent parallel design.</p><p><strong>Results: </strong>DPR recommended ten proposals for funding, while the panel recommended eleven; three overlapped. Funding criteria strongly predicted overall score; 'Originality' was given most weight by both sets of reviewers. Stability of DPR funding decisions was modest; across 500 bootstrapped samples a mean of 5.49 out of ten previously funded proposals would still be funded. This may be explained by high inter-reviewer variability: more variance was attributable to between-reviewer differences (20.0%) than between-proposal differences (8.9%). Advantages of DPR included increased efficiency, faster decision times, detailed feedback to applicants, and democratisation of funding evaluation. Noted disadvantages were burden on applicants, absence of discussion, and perceived lack of reviewer expertise. Funders implementing DPR must consider the high initial effort, potential for 'gaming', and reduced direct influence.</p><p><strong>Conclusions: </strong>This trial demonstrates the feasibility of DPR for an interdisciplinary funding programme. Implementing DPR requires funders to accept trade-offs and that DPR may not produce the same outcomes as existing systems. Building on established peer review principles, it may offer benefits, including shortening time to funding decision, and has the potential to contribute to the democratisation of funding evaluation.</p>","PeriodicalId":74682,"journal":{"name":"Research integrity and peer review","volume":"11 1","pages":""},"PeriodicalIF":9.6,"publicationDate":"2026-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13617845/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149077016","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correcting the record on \"Publication integrity and industry influences on the editorial process: a case study\".","authors":"James P Rathmell","doi":"10.1186/s41073-026-00249-4","DOIUrl":"10.1186/s41073-026-00249-4","url":null,"abstract":"<p><p>In 2024, Anesthesiology published a systematic review and meta-analysis of liposomal bupivacaine together with four editorials presenting both strong support for its conclusions and critical perspectives, with the editorial authors' industry affiliations and financial interests disclosed. A subsequent case study in Research Integrity and Peer Review characterized this presentation as a \"retraction in situ\" and questioned whether organizational and industry relationships compromised editorial independence. This Correspondence presents additional facts relevant to evaluating those conclusions. The research article remained intact. The coordinated presentation was commissioned by the Editor-in-Chief, while a senior editor serving as acting Editor-in-Chief independently managed peer review and made the publication decisions for all four editorials. Before the case study was published, its authors had submitted to Anesthesiology a manuscript advancing a similar critique. That manuscript underwent multiple rounds of external assessment, senior editorial-board review, and discussion by the full editorial board; its rejection was not unilateral. During my tenure, neither the American Society of Anesthesiologists nor Pacira BioSciences participated in or influenced the 2024 publication decisions for the research article or accompanying editorials, or the disposition of the authors' later submission. Greater procedural clarity could have been achieved through timelier publication, fuller disclosure of organizational relationships, and complete recusal of the Editor-in-Chief from consideration of the later submission. These are legitimate procedural lessons, but they do not establish external influence or editorial misconduct. The publication record instead reflects the transparent presentation of scientific disagreement, not a disguised retraction.</p>","PeriodicalId":74682,"journal":{"name":"Research integrity and peer review","volume":"11 1","pages":""},"PeriodicalIF":9.6,"publicationDate":"2026-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13548466/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148908280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Disclosure is not documentation: an open science framework for documenting generative AI use in scholarly research and publication workflows.","authors":"Jan Christopher Cwik","doi":"10.1186/s41073-026-00245-8","DOIUrl":"https://doi.org/10.1186/s41073-026-00245-8","url":null,"abstract":"<p><strong>Background: </strong>Generative AI is increasingly used in scholarly research, writing, and publication workflows. Many journal and publisher policies ask authors to disclose relevant AI use, but disclosure alone rarely clarifies how AI-assisted work was performed, what information was entered, how outputs were evaluated, or how human responsibility was maintained. This creates a gap between AI-use disclosure as a publication requirement and AI-use documentation as an open science practice.</p><p><strong>Methods: </strong>This article develops a conceptual and practical framework for documenting generative AI use in scholarly workflows. The framework was informed by exploratory, non-systematic source and policy mapping, AI-assisted exploratory evidence mapping, manual review of selected recent literature, and development of accompanying Open Science Framework materials. These steps were used to identify recurring documentation expectations and unresolved policy gaps and to translate them into practical documentation domains, with particular attention to task specificity, proportionality, role-specific documentation, privacy-sensitive transparency, and clinically sensitive contexts.</p><p><strong>Results: </strong>The framework distinguishes disclosure from documentation and proposes documentation fields for minimal and extended AI use. Minimal documentation is intended for low-risk uses such as limited language polishing, whereas extended documentation is recommended when AI supports literature synthesis, coding, analysis, interpretation, manuscript drafting, peer-review-related work, clinical material, or research procedures. The framework is accompanied by reusable OSF materials, including documentation templates, prompt-log structures, declaration examples, checklists, clinical redaction guidance, and source-tracking materials.</p><p><strong>Conclusions: </strong>AI-use disclosure communicates that AI was used; documentation makes the AI-assisted workflow traceable, inspectable, and accountable. A task-specific, proportionate, role-specific, and privacy-sensitive documentation approach can support responsible AI use while protecting confidential, patient-related, peer-review-related, and methodologically sensitive information. The accompanying bilingual materials are openly available on OSF: https://doi.org/10.17605/OSF.IO/A439J .</p>","PeriodicalId":74682,"journal":{"name":"Research integrity and peer review","volume":"11 1","pages":""},"PeriodicalIF":9.6,"publicationDate":"2026-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13483690/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148802805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}