Fraudulent Research Falsely Attributed to Credible Researchers—An Emerging Challenge for Journals?

Abstract

A recent incident highlights a potentially new form of research fraud involving articles falsely attributed to a group of legitimate researchers. Several researchers contacted us via ResearchGate with questions about a published article titled ‘Investigating the Effectiveness of Play Therapy on Reducing Despair, and Anxiety in Children with Cancer’ in Clinical Cancer Investigation Journal (Höglund et al. 2024). Upon closer examination, we discovered that the article was published with our names (making up an active research group) listed as authors without our knowledge or consent and containing fabricated data. This raises important questions: How could this happen, and is this a new form of research fraud? Traditionally, research fraud has included data fabrication, or fabrication, falsification, plagiarism, and honorary authorships. However, this incident points to another type of fraud where research is published under legitimate author names without their knowledge or contribution. This practice of fabricating data for an entire research group without their involvement may indeed be a new phenomenon. A review of the Retraction Watch Database for 2023–2024 found that out of 30 papers retracted for false/forged authorship, 16 had explanations. The main causes were fictitious authorship (8 cases) and unauthorised publications (2 cases), with other issues including unethical co-author charges, false ethics approval, data fabrication (5 cases), and complete identity fabrication (1 case). Kwee and Kwee (2023) found a 4.0% incidence of forged authorship in 192 retracted medical imaging papers from 1984 to 2021. Although none matched our exact experience, one similar case was noted (Orall 2024). Forged authorship and data fabrication pose new challenges to authorship integrity. Recent studies reveal a significant portion of scientists admit to engaging in research misconduct, including data fabrication and falsification. A 2021 survey among Dutch researchers revealed that approximately 8% confessed to falsifying or fabricating data between 2017 and 2020 (Singh 2021), and over 50% admitted to questionable research practices like selective reporting. More than 10% of medical and life-science researchers admitted to such fraud. A comprehensive study of over 4700 researchers from Denmark and other countries showed that 9 out of 10 used at least one questionable research practice, influenced by social acceptability (Schneider et al. 2024). Researchers analysed nearly 1 million papers published between 2020 and 2024, finding a steady increase in the use of generative AI in scientific papers, ranging from 6.3% to 17.5% depending on the topic (Liang et al. 2024). Retraction rates have quadrupled, rising from approximately 11 retractions per 100,000 papers in 2000 to nearly 45 per 100,000 by 2020 (Holly 2024; Freijedo-Farinas et al. 2024). Among retracted papers, nearly 67% were due to misconduct, while about 16% were for honest errors. The risk of AI-generated fake research is increasing in both volume and sophistication, making detection difficult (Elali and Rachid 2023). Therefore, scholarly researchers must discuss safeguards against this emerging threat. One possible explanation is that fraudulent editors, or journal owners, might use researchers' names to lend legitimacy to their journals. By including established names and author groups with the same research focus as the published article, the journal can be more easily accepted as legitimate by potential authors, and its impact factor can rise. This could also explain why the article got the affiliations right and listed two authors who had in fact researched this very topic before. Another possibility is that such an article may use citations to other papers published in the same journal or by the same publisher to increase their citation metrics. Technological advances in generative AI may also have made it possible and easy to generate text and content that is highly credible and difficult to distinguish from human-created content. AI-generated language models can write articles, reports and even academic papers with a certain degree of coherence and relevance (Kim et al. 2024; Ray 2024). The article in question raises several red flags indicating potential research misconduct. The primary issue is the absence of communication with the corresponding author and the lack of peer review documentation, both critical components of the publication process. Furthermore, the standard practice of providing proofs has not been followed. Ethical approval is not documented in the paper, despite the study involving children with cancer—a particularly vulnerable population. The omission of the research location questions the study's legitimacy. Additionally, the article references four unrelated studies, undermining its relevance to play therapy for children with cancer. These studies cover topics like post-surgery sleep quality in breast cancer patients, consultations in breast cancer, hope therapy for mothers of children with cancer, and an unrelated Portuguese reference. Despite raising these issues with the editor, we received no acknowledgment, compounding our concerns about the research's integrity. Whether produced in-house or by a paper mill, the journal benefits from neglecting its editorial duties. Paper mills that produce studies with fabricated data, false authorship, and manipulated peer review are a well-documented form of academic misconduct (Else and Van Noorden 2021; Parker et al. 2024). These unethical practices are frequently driven by ‘publish or perish’ culture, in which scholars face intense pressure to publish in order to secure tenure, academic positions or research funding—pressures that have been recognised as significant contributors to academic dishonesty (Ott and Cisneros 2015; Lei et al. 2024; Wu 2025). In our case, the study in question was published with fabricated data and listed us as authors, without our knowledge or consent. To our knowledge, this specific form of misconduct—unauthorised authorship of an entire research group combined with data fabrication—has not been systematically documented in the academic literature, despite a comprehensive review. Currently, evidence for this phenomenon remains anecdotal. One notable case was reported by a Japanese newspaper, where papers containing fabricated data were published under the names of three researchers—again, without their consent (The Mainichi 2025). The papers claimed that their content had been generated using artificial intelligence. Professor Sho Sato of Doshisha University, an expert on predatory publishing, observed that such articles may have been crafted to appear as if authored by credible researchers in order to gain legitimacy. He further noted, ‘While people have been on guard over the misuse of generative AI (by contributors), we didn't expect a publisher to generate articles to appear in its own journals. It's conceivable more malicious cases of misuse will emerge in the future’. This possible new type of research fraud underscores the need for vigilance and action. Academic institutions and publishers must collaborate to develop effective solutions to ensure that research remains credible and reliable. This is crucial to maintaining trust in science and protecting the integrity of our work. For example, authors should be vigilant in reporting misconduct involving journals like this to Cabells' Predatory Reports. Authors subjected to forged authorship should have a strong support in taking legal action when necessary. A broader discussion on appropriate responses is essential, as manipulating authorship is a serious violation of publication ethics that distorts the research record and undermines the credibility of the entire body of work. Preventing and addressing such fraudulent activities is critical. These unethical practices compromise the integrity of scientific research and have far-reaching consequences, such as misleading researchers, policymakers, and the public. To combat fabrication, it is necessary to implement stricter peer review processes, improve detection technologies, and fostering a culture of research integrity (Elali and Rachid 2023). This new type of research fraud poses a significant challenge for the scientific community. Fraudulent articles published under legitimate researchers' names without their consent threaten scientific integrity. Combined with data fabrication, detecting and preventing fraud becomes increasingly difficult. Enhanced vigilance, stricter peer review, and improved detection technologies are crucial. Collaboration among academic institutions, publishers, and researchers is essential to safeguard the credibility of scientific research. By fostering a culture of research integrity and implementing rigorous ethical standards, the scientific community can better combat research fraud and ensure science remains trustworthy. T.G. contributed to all stages according to CRediT. The author has nothing to report. The author has nothing to report. The author has nothing to report. The author declares no conflicts of interest. Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

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