Accountability in Research-Policies and Quality Assurance最新文献

{"title":"Editorial expressions of concern are infrequent even for researchers with multiple retracted publications - An observational study.","authors":"Andrew Grey, Alison Avenell, Mark Bolland","doi":"10.1080/08989621.2026.2671154","DOIUrl":"10.1080/08989621.2026.2671154","url":null,"abstract":"<p><strong>Background: </strong>Early notification of journal readers of the existence of publication integrity concerns by an editorial expression of concern (EoC) can mitigate the adverse effects of unreliable research.</p><p><strong>Methods: </strong>We extracted EoCs and retraction notices from the Retraction Watch database up until the end of 2024. We assessed temporal trends in publication of each notice, the proportion of retracted papers with an associated EoC, and the timing of EoCs according to publication date and retraction status. We examined the ratio of EoCs to retractions among authors, including those with multiple retractions, and among both journals and publishers.</p><p><strong>Results: </strong>EoCs were rarely published during the 14y assessment period. Only 3.3% of retracted papers had a preceding EoC. For 56% of publications with an EoC, the EoC was the latest notice. 92% of authors had an EoC:retraction ratio < 1. Only 35% of authors with > 5 retractions had an EoC, and 99% had an EoC:retraction ratio < 1. Publication of an EoC was more common in journals which had published > 5 retractions than in those which had published < 5.</p><p><strong>Conclusions: </strong>EoCs are rarely employed during the assessment of publication integrity concerns. Journal readers are disadvantaged by delayed notification of potentially unreliable research.</p>","PeriodicalId":50927,"journal":{"name":"Accountability in Research-Policies and Quality Assurance","volume":" ","pages":"2671154"},"PeriodicalIF":4.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147943481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hallucinated citations produced by generative artificial intelligence may constitute research misconduct when citations function as data in scholarly papers.","authors":"David B Resnik, Mohammad Hosseini","doi":"10.1080/08989621.2026.2645390","DOIUrl":"10.1080/08989621.2026.2645390","url":null,"abstract":"<p><p>In this article, we discuss the growing problem of hallucinated citations produced by Generative Artificial Intelligence (GenAI) in scholarly research and writing. We argue that GenAI hallucinated citations might qualify as a provable instance of research misconduct under the U.S. federal regulations when a) the researcher uses a GenAI tool to produce hallucinated (i.e., nonexistent) citations for a research document; b) the citations function as data because they directly support research findings, as in, for example, review articles or bibliometric studies; and c) the researcher demonstrates indifference to the risk of fabrication of the data (i.e. citations) because they did not check the GenAI's output for veracity and accuracy. Other types of problematic citations such as bibliometrically incorrect citations, or contextually inaccurate citations, are indicative of poor scholarship and irresponsible behavior, but do not qualify as research misconduct. Recognizing that GenAI hallucinated citations could be regarded as research misconduct in certain cases will hopefully encourage researchers to take this problem more seriously than they do now. In partnership with scientific institutions, funders and professional societies, the scholarly community should work on establishing, promoting, and enforcing standards for responsible use of AI in research, including standards pertaining to citation practices.</p>","PeriodicalId":50927,"journal":{"name":"Accountability in Research-Policies and Quality Assurance","volume":" ","pages":"2645390"},"PeriodicalIF":4.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13051339/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147464181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"International multi-stakeholder consensus statement on patient, carer and public involvement to enhance clinical trial integrity.","authors":"Khalid Saeed Khan, Mohamed Fawzy, Balázs Juhász, Patrick Chien, Manuel Martín-Díaz, Javier Zamora, Alberto Ruano Raviña, María Núñez-Núñez, Maria Del Carmen Amezcua Prieto, Sergio Martínez Vázquez, León González Casas, Allan Pacey, Begoña Martinez de Tejada, Klejda Harasani, Yacoub Khalaf, Gamal Serour, Mohamed Aboulghar, Hassan Sallam, Vicente Martín Sánchez, Olga Ocón Hernández, Giovanni Grandi, Bassel Wattar, William Parry-Smith, Elizabeth Ball, Janneke van 't Hooft, Ali Mahran, Luciano Mignini, Mohamed Bedaiwy, Mohamed Yehia Soliman, Amr El-Shalakany, Miland Joshi, Ngawai Moss, Jeffrey A Andrews, Jun Jim Zhang, Michael Geary, Anthony Odibo, Tayyiba Wasim, Naomi Cano Ibáñez, Mohamad A Elsuity, Aurora Bueno-Cavanillas","doi":"10.1080/08989621.2026.2647346","DOIUrl":"10.1080/08989621.2026.2647346","url":null,"abstract":"<p><strong>Background: </strong>The recent update of the Declaration of Helsinki has emphasized community engagement and research integrity. Patient, carer and public involvement (PCPI) throughout the research lifecycle of randomized clinical trials (RCTs) can enhance their integrity. However, no specific PCPI guidance exists for trialists. The Cairo Consensus Group on Research Integrity, consisting of 40 stakeholders from 14 countries, developed a statement to address this gap.</p><p><strong>Methods: </strong>The project was prospectively registered at the Open Science Framework (https://osf.io/fqepb). Based on the findings of a literature review and a stakeholder consultation, an initial long list of recommendations was created. It was submitted to a two-round modified Delphi survey before being finalized in a hybrid online-face-to-face meeting.</p><p><strong>Results: </strong>The modified Delphi survey response rate was 63% (29/46) for the first round, and 65% (30/46) for the second round. The initial long list consisted of 46 statements, and nine additional statements were provided during the consensus process. The final set consolidated 39 statements, grouped into seven categories: General; Design, Approval and Funding; Conduct and Monitoring; Reporting of protocols and findings; Dissemination and Implementation; and Future Research and Development.</p><p><strong>Conclusion: </strong>This international consensus statement is expected to help organizations implement PCPI to enhance RCT integrity.</p>","PeriodicalId":50927,"journal":{"name":"Accountability in Research-Policies and Quality Assurance","volume":" ","pages":"2647346"},"PeriodicalIF":4.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147516404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identificatory underpinnings of ethical research behavior for graduate students: Evidence from a baseline sample of a university research ethics training program.","authors":"Mitch Brown, Donald F Sacco, Clyde Raible, Karl J Wallace, Jennifer L Lemacks","doi":"10.1080/08989621.2026.2659673","DOIUrl":"10.1080/08989621.2026.2659673","url":null,"abstract":"<p><strong>Background: </strong>In efforts to improve replication rates across sciences, graduate student training can foster an understanding of best practices. One consideration is to identify the psychological underpinnings that motivate early-career researchers to avoid questionable research practices (QRPs) and engage in transparent research behaviors. Recent findings demonstrate efficacy by leveraging identificatory processes, or how researchers identify with ethical science. This study examined whether the extent to which individuals incorporate ethical scientific principles into their identities can motivate disinterest in QRPs.</p><p><strong>Method: </strong>As part of a baseline data collection effort for a systemic ethics training program at a Carnegie R1 institute, graduate students provided initial measures assessing endorsement of scientific values as outlined by the National Academies of Science, Engineering, and Medicine (NASEM) and the extent to which those values are part of their identity. They also reported their perceptions of the defensibility of various QRPs, and their willingness to engage in them.</p><p><strong>Results: </strong>Greater endorsement of NASEM values was associated with less endorsement of QRPs. This association was mediated by inclusion of these values in one's own identity. Results provide initial evidence for how institutes can foster psychological profiles of an ethical researcher in developing training modules for graduate students.</p>","PeriodicalId":50927,"journal":{"name":"Accountability in Research-Policies and Quality Assurance","volume":" ","pages":"2659673"},"PeriodicalIF":4.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147700292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction.","authors":"","doi":"10.1080/08989621.2026.2710539","DOIUrl":"10.1080/08989621.2026.2710539","url":null,"abstract":"","PeriodicalId":50927,"journal":{"name":"Accountability in Research-Policies and Quality Assurance","volume":" ","pages":"2710539"},"PeriodicalIF":4.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148632536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The systemic breach of AI in academic publishing: Infrastructural failures and authorial misconduct across seven major publishers.","authors":"Yassine Ismaili","doi":"10.1080/08989621.2026.2741356","DOIUrl":"https://doi.org/10.1080/08989621.2026.2741356","url":null,"abstract":"<p><p>In academic publishing, there is a crisis that is both authorial and infrastructural; however, the discussion around the topic is heavily skewed toward the former rather than the latter. This paper presents an empirical map of both issues. Using a convenience sample of <i>N</i> = 323 retracted articles obtained from the Retraction Watch Database from seven of the major publishers: Springer Nature, Elsevier, Wiley, SAGE, Taylor & Francis, Emerald, and MDPI, we have used a mixed methods approach, namely, qualitative content analysis of the retraction notices and quantitative reporting of the coded frequencies. We coded the notices along the dimension of infrastructural vs. authorial failure. Our results show that even though algorithmic forgery (\"AIgiarism\") does represent a real and growing threat, it is dwarfed in our retraction sample by the infrastructural issues in terms of scale, such as rogue editors, syndicated paper mills, broken peer review systems, and fake human-based clinical trials. This becomes clear when examining these phenomena publisher by publisher, revealing different infrastructural vulnerabilities that cannot be fixed regardless of how rigorously the policies are enforced by individual editorial offices.</p>","PeriodicalId":50927,"journal":{"name":"Accountability in Research-Policies and Quality Assurance","volume":" ","pages":"2741356"},"PeriodicalIF":4.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149118214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coping with the impacts of generative artificial intelligence on scholarly publications.","authors":"Mohammad Hosseini, Lisa Rasmussen, David B Resnik","doi":"10.1080/08989621.2026.2737718","DOIUrl":"https://doi.org/10.1080/08989621.2026.2737718","url":null,"abstract":"","PeriodicalId":50927,"journal":{"name":"Accountability in Research-Policies and Quality Assurance","volume":" ","pages":"2737718"},"PeriodicalIF":4.4,"publicationDate":"2026-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149065679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI translation and citation irregularities.","authors":"Ka Wai Fan","doi":"10.1080/08989621.2026.2736608","DOIUrl":"https://doi.org/10.1080/08989621.2026.2736608","url":null,"abstract":"","PeriodicalId":50927,"journal":{"name":"Accountability in Research-Policies and Quality Assurance","volume":" ","pages":"2736608"},"PeriodicalIF":4.4,"publicationDate":"2026-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149018589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Subscription, open access, hybrid - and now AI: AI-induced evidence skew in scholarly work.","authors":"Sameh Eltaybani","doi":"10.1080/08989621.2026.2725029","DOIUrl":"https://doi.org/10.1080/08989621.2026.2725029","url":null,"abstract":"<p><strong>Objective: </strong>Little attention has been paid to how publication and access models influence the evidence that AI systems retrieve, process, and summarize. This article introduces the concept of AI-induced evidence skew, proposes four pathways through which it may arise, and provides a preliminary empirical illustration.</p><p><strong>Methods: </strong>Nine widely used large language models (LLMs) were prompted to generate literature-supported content. The accessibility status of the references provided was compared with the percentage of open-access records identified through searches of three scholarly databases.</p><p><strong>Results: </strong>AI-induced evidence skew is a structural distortion in AI-assisted evidence synthesis whereby outputs disproportionately represent open-access or otherwise machine-accessible literature. Four proposed pathways are differential representation of literature in training data, retrieval-access constraints, human verification practices, and system- or user-imposed access restrictions. Among 78 verifiable references generated by LLMs, a mean of 95.38% had freely available full text (87.43% were open-access), compared with a mean open-access percentage of 57.83% across scholarly database search results.</p><p><strong>Conclusions: </strong>Although exploratory and non-generalizable, these findings support the hypothesis that AI-assisted search and synthesis may overrepresent publicly accessible literature. The concern is not the quality of open-access literature, but that accessibility may become an unintended determinant of included evidence. Mitigation requires greater awareness, human oversight, transparent reporting of AI use and retrieval limitations, verification of AI-generated references, and improved transparency regarding AI evidence coverage. Further empirical investigation across disciplines, platforms, and AI tools is warranted.</p>","PeriodicalId":50927,"journal":{"name":"Accountability in Research-Policies and Quality Assurance","volume":" ","pages":"2725029"},"PeriodicalIF":4.4,"publicationDate":"2026-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148921743","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leadership to strengthen research culture and foster responsible conduct of research: A case study.","authors":"Seán Lacey, Jean Ricken, Stephen Cassidy","doi":"10.1080/08989621.2026.2730991","DOIUrl":"https://doi.org/10.1080/08989621.2026.2730991","url":null,"abstract":"<p><strong>Objective: </strong>Research performing organizations (RPOs) are increasingly expected to strengthen research culture and support the responsible conduct of research (RCR). Institutional supports are central to advancing research culture across RPOs. To inform development and evaluation of these supports, surveys were conducted within an RPO.</p><p><strong>Method: </strong>Perceptions of research culture and RCR were examined using surveys conducted in 2022 and 2024. Between surveys, accessible training and supports on good research practices were developed and deployed.</p><p><strong>Results: </strong>Awareness of research impact, authorship, and collegial support remained high (<i>p</i> > 0.05), with significant improvements in access to resources and reporting pathways for inappropriate research behaviors (<i>p</i> < 0.05). In contrast, time for professional development remained low. Knowledge of access to research supports improved significantly for open access, data management, and authorship (<i>p</i> < 0.05). Participation in targeted training was associated with improved domain-specific knowledge of research integrity, authorship, reporting mechanisms, and acess to resources (<i>p</i> < 0.05). Open-ended responses reflected a parallel shift: in 2022, participants emphasized obstacles, but by 2024, focus moved toward training, resources, and constructive practices, suggesting an evolving culture shaped by institutional supports.</p><p><strong>Conclusion: </strong>The findings suggest that leadership in developing and deploying accessible training and supports contributed to strengthened awareness of RCR and institutional support mechanisms.</p>","PeriodicalId":50927,"journal":{"name":"Accountability in Research-Policies and Quality Assurance","volume":" ","pages":"2730991"},"PeriodicalIF":4.4,"publicationDate":"2026-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148908022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}