Research integrity and peer review最新文献

Background: Quotations are crucial to science but have been shown to be often inaccurate. Quotation errors, that is, a reference not supporting the authors' claim, may still be a significant issue in scientific medical writing. This study aimed to examine the quotation error rate and trends over time in the medical literature.

Methods: A systematic search of PubMed, Web of Science, and reference lists for quotation error studies in medicine and without date or language restrictions identified 46 studies analyzing 32,000 quotations/references. Literature search, data extraction, and risk of bias assessments were performed independently by two raters. Random-effects meta-analyses and meta-regression were used to analyze error rates and trends (protocol pre-registered on OSF).

Results: 16.9% (95% CI: 14.1%-20.0%) of quotations were incorrect, with approximately half classified as major errors (8.0% [95% CI: 6.4%-10.0%]). Heterogeneity was high, and Egger's test for small study effects remained negative throughout. Meta-regression showed no significant improvement in quotation accuracy over recent years (slope: -0.002 [95% CI: -0.03 to 0.02], p = 0.85). Neither risk of bias, nor the number of references were statistically significantly associated with total error rate, but journal impact factor was: Spearman's ρ = -0.253 (p = 0.043, binomial test, N = 25).

Conclusions: Quotation errors remain a problem in the medical literature, with no improvement over time. Addressing this issue requires concerted efforts to improve scholarly practices and editorial processes.

Background: Case reports are valuable tools that illustrate and analyze practical scenarios, novel problems, and the effectiveness of interventions. In psychiatry they often explore unique and potentially stigmatizing aspects of mental health, underscoring the importance of confidentiality and informed consent. However, journals' guidance on consent and confidentiality for case reports varies. In 2013, an international expert group developed the CAse REports (CARE) Guidelines for best practices in case reports, which include guidelines for informed consent and de-identification. In 2016, the Committee on Publication Ethics (COPE) issued ethical standards for publishing case reports, calling for written informed consent from featured patients.

Methods: Using a cross-sectional approach, we assessed the instructions for authors of 253 indexed psychiatry journals, of which 129 had published English-language case reports in the prior five years. Our research identified and evaluated journals' use of COPE and CARE guidelines on informed consent and de-identification in case reports.

Results: Among these 129 journals, 84 (65%) referred to COPE guidelines, and 59 (46%) referenced CARE guidelines. Furthermore, 46 (36%) required informed consent without de-identification, 7 (5%) required only de-identification, and 21 (16%) required both, specifying consent for identifying information. Notably, 40 (31%) lacked informed consent instructions. Of the 82 journals that required informed consent, 69 (85%) required documentation of consent.

Conclusion: A decade after the publication of expert guidance, psychiatry journals remain inconsistent in their adherence to ethical guidelines for informed consent in case reports. More attention to clear instructions from journals on informed consent-a notable topic across different fields-would provide an important educational message about both publication ethics and fundamental respect for patients' confidentiality.

Background: Continuous cell lines are indispensable in basic and preclinical research. However, cross-contamination, misidentification, and over-passaging affect the validity and reproducibility of biomedical results. Although there have been efforts to highlight this problem for decades, definitive prevention remains a challenge. The International Cell Line Authentication Committee (ICLAC) registry (version 13, 26 April 2024) lists nearly 600 misidentified or contaminated cell lines. The inappropriate use of such cells has led to countless publications containing invalid data, creating a ripple effect of wasted resources, misleading follow-up studies, and compromised evidence-based conclusions.

Methods: The ICLAC registry was consulted to identify commonly misidentified cell lines. A literature search of PubMed was performed to identify recent papers using these lines in liver-related experiments. Four publications with questionable conclusions were highlighted, and the editors of the respective journals were informed with short comments or letters to the editor.

Results: Reactions from journal editors varied widely. In two cases, the editors quickly published the comments, resulting in transparent corrections. In the third example, the editor conducted an internal investigation without immediately publishing a correction. In the fourth example, the journal declined to address concerns publicly.

Conclusions: Misidentified cell lines pose an ongoing threat to scientific rigor. Despite some responsible editorial interventions, the lack of universal standards fosters the dissemination of erroneous data. However, authors, reviewers, and editors have some important tools to prevent publications with misidentified cells by consulting available resources (e.g., ICLAC, Cellosaurus, Research Resource Identification Portal, SciScore™), and adopting consistent procedures to maintain research integrity.

Background: In the U.S. and many other countries, animal use in research, testing, and education is under the purview of Institutional Animal Care and Use Committees or similar bodies. Their responsibility for reviewing proposed experiments, particularly with regard to adherence to legal and ethical mandates, can be a challenging task.

Objective: To understand factors that may limit the effectiveness of Institutional Animal Care and Use Committees and identify possible solutions.

Methods: This editorial review summarizes scientific literature describing the challenges faced by U.S. Institutional Animal Care and Use Committees and those who rely on them and describes actions that may improve their functioning.

Results: Apart from what may be a sizable workload and the need to satisfy applicable regulations, committees have fundamental structural challenges and limitations. Under U.S. law, there is no requirement that committee members have expertise in the research areas under review or in methods that could replace animal use, nor could expertise in such vast technical areas be expected, in contrast with the review process of many scientific journals in which experts in the conditions being studied critique the choice of subjects and methods used. Although investigators are expected to consider alternatives to procedures that may cause more than momentary or slight pain or distress, they are not required to use them. While investigators must assure committee members that studies do not duplicate other research, committee members are not required to verify this. Consideration of alternatives to painful procedures is not required at all for experiments on animals not covered by the Animal Welfare Act. The majority of U.S. research institutions now allow research proposals to be approved by a single committee member, using a system called Designated Member Review, without full committee consideration. In other countries, requirements differ considerably. In the European Union, for example, investigators must complete a harm-benefit analysis and must use alternatives, not simply consider them.

Conclusions: The review process may be improved by requiring searches for nonanimal methods regardless of species, favoring alternatives based on human biology, improving the education of committee members and investigators, using reviewers with subject matter expertise, and minimizing conflicts of interest. Because of the limitations of the review process, funding institutions and scientific journals should not use Institutional Animal Care and Use Committee approval of submissions as evidence of adherence to ethical guidelines beyond those legally required.

Background: Although commonly used to evaluate health interventions, cluster randomized trials raise difficult ethical issues. Recognizing this, the Ottawa Statement on the Ethical Design and Conduct of Cluster Randomized Trials, published in 2012, provides 15 recommendations to address ethical issues across seven domains. But due to several developments in the design and implementation of cluster randomized trials, there are new issues requiring guidance. To inform the forthcoming update of the Ottawa Statement, we aimed to identify any gaps in the Ottawa Statement discussed within the literature.

Methods: We searched Google Scholar, Scopus, and Web of Science using the 'cited by' function on 11 November 2022.We included all types of publications, including articles, book chapters, commentaries, editorials, ethics guidelines, theses and trial-related publications (i.e., primary reports, protocols, and secondary analyses), that cited and engaged with the Ottawa Statement, the Ottawa Statement précis, or one or more of its four background papers. Data were extracted by four reviewers working in rotating pairs. Reviewers captured relevant text verbatim and recorded whether it reflected a gap relating to one or more of the Ottawa Statement domains. Using a thematic analysis approach, semantic coding was used to summarize the content of the data into distinct gaps within the Ottawa Statement domains, which was subsequently expanded in an inductive manner through discussion.

Results: The qualitative analysis of the text from 53 articles resulted in the identification of 24 distinct gaps in the Ottawa Statement: 4 gaps about justifying the cluster randomized design; 2 gaps about research ethics committee review; 3 gaps about identifying research participants; 4 gaps about obtaining informed consent; 3 gaps about gatekepeers; 6 gaps about assessing benefits and harms; 1 gap about protecting vulnerable participants; and 1 gap about equity-related issues in cluster randomized trials.

Conclusion: Identifying 24 gaps reveals a need to update the Ottawa Statement. Alongside additional gaps identified in ongoing empirical work and through engagement with our patient and public partners, the gaps identified through this citation analysis should be considered in the forthcoming Ottawa Statement update.

Background: Retractions undermine the scientific record's reliability and can lead to the continued propagation of flawed research. This study aimed to (1) create a dataset aggregating retraction information with bibliographic metadata, (2) train and evaluate various machine learning approaches to predict article retractions, and (3) assess each feature's contribution to feature-based classifier performance using ablation studies.

Methods: An open-access dataset was developed by combining information from the Retraction Watch database and the OpenAlex API. Using a case-controlled design, retracted research articles were paired with non-retracted articles published in the same period. Traditional feature-based classifiers and models leveraging contextual language representations were then trained and evaluated. Model performance was assessed using accuracy, precision, recall, and the F1-score.

Results: The Llama 3.2 base model achieved the highest overall accuracy. The Random Forest classifier achieved a precision of 0.687 for identifying non-retracted articles, while the Llama 3.2 base model reached a precision of 0.683 for identifying retracted articles. Traditional feature-based classifiers generally outperformed most contextual language models, except for the Llama 3.2 base model, which showed competitive performance across several metrics.

Conclusions: Although no single model excelled across all metrics, our findings indicate that machine learning techniques can effectively support the identification of retracted research. These results provide a foundation for developing automated tools to assist publishers and reviewers in detecting potentially problematic publications. Further research should focus on refining these models and investigating additional features to improve predictive performance.

Trial registration: Not applicable.

Background: The proliferation of generative artificial intelligence (AI) has facilitated the creation and publication of fraudulent scientific articles, often in predatory journals. This study investigates the extent of AI-generated content in the Global International Journal of Innovative Research (GIJIR), where a fabricated article was falsely attributed to me.

Methods: The entire GIJIR website was crawled to collect article PDFs and metadata. Automated scripts were used to extract the number of probable in-text citations, DOIs, affiliations, and contact emails. A heuristic based on the number of in-text citations was employed to identify the probability of AI-generated content. A subset of articles was manually reviewed for AI indicators such as formulaic writing and missing empirical data. Turnitin's AI detection tool was used as an additional indicator. The extracted data were compiled into a structured dataset, which was analyzed to examine human-authored and AI-generated articles.

Results: Of the 53 examined articles with the fewest in-text citations, at least 48 appeared to be AI-generated, while five showed signs of human involvement. Turnitin's AI detection scores confirmed high probabilities of AI-generated content in most cases, with scores reaching 100% for multiple papers. The analysis also revealed fraudulent authorship attribution, with AI-generated articles falsely assigned to researchers from prestigious institutions. The journal appears to use AI-generated content both to inflate its standing through misattributed papers and to attract authors aiming to inflate their publication record.

Conclusions: The findings highlight the risks posed by AI-generated and misattributed research articles, which threaten the credibility of academic publishing. Ways to mitigate these issues include strengthening identity verification mechanisms for DOIs and ORCIDs, enhancing AI detection methods, and reforming research assessment practices. Without effective countermeasures, the unchecked growth of AI-generated content in scientific literature could severely undermine trust in scholarly communication.

Background: Industry funding and author conflicts of interest (COI) have been consistently shown to introduce bias into agenda-setting and results-reporting in biomedical research. Accordingly, maintaining public trust, diminishing patient harm, and securing the integrity of the biomedical research enterprise are critical policy priorities. In this context, a coordinated and methodical research effort is required to effectively identify which policy interventions are most likely to mitigate against the risks of funding bias. Subsequently this scoping review aims to identify and synthesize the available research on policy mechanisms designed to address funding bias and COI in biomedical research.

Methods: We searched PubMed for peer-reviewed, empirical analyses of policy mechanisms designed to address industry sponsorship of research studies, author industry affiliation, and author COI at any stage of the biomedical research process and published between January 2009 and 28 August 2023. The review identified literature conducting five primary analysis types: (1) surveys of COI policies, (2) disclosure compliance analyses, (3) disclosure concordance analyses, (4) COI policy effects analyses, and (5) studies of policy perceptions and contexts. Most available research is devoted to evaluating the prevalence, nature, and effects of author COI disclosure policies.

Results: Six thousand three hundreds eighty five articles were screened, and 81 studies were included. Studies were conducted in 11 geographic regions, with studies of international scope being the most common. Most available research is devoted to evaluating the prevalence, nature, and effects of author COI disclosure policies. This evidence demonstrates that while disclosure policies are pervasive, those policies are not consistently designed, implemented, or enforced. The available evidence also indicates that COI disclosure policies are not particularly effective in mitigating risk of bias or subsequent negative externalities.

Conclusions: The results of this review indicate that the COI policy landscape could benefit from a significant shift in the research agenda. The available literature predominantly focuses on a single policy intervention-author disclosure requirements. As a result, new lines of research are needed to establish a more robust evidence-based policy landscape. There is a particular need for implementation research, greater attention to the structural conditions that create COI, and evaluation of policy mechanisms other than disclosure.

Background: Research on research integrity (RI) has grown exponentially over the past several decades. Although the earliest publications emerged in the 1980 s, more than half of the existing literature has been produced within the last five years. Given that the most recent comprehensive literature review is now eight years old, the present study aims to extend and update previous findings.

Method: We conducted a systematic search of the Web of Science and Constellate databases for articles published between 2015 and 2023. To structure our overview and guide our inquiry, we addressed the following seven broad questions about the field:-What topics does the empirical literature on RI explore? What are the primary objectives of the empirical literature on RI? What methodologies are prevalent in the empirical literature on RI? What populations or organizations are studied in the empirical literature on RI? Where are the empirical studies on RI conducted? Where is the empirical literature on RI published? To what degree is the general literature on RI grounded in empirical research? Additionally, we used the previous scoping review as a benchmark to identify emerging trends and shifts.

Results: Our search yielded a total of 3,282 studies, of which 660 articles met our inclusion criteria. All research questions were comprehensively addressed. Notably, we observed a significant shift in methodologies: the reliance on interviews and surveys decreased from 51 to 30%, whereas the application of meta-scientific methods increased from 17 to 31%. In terms of theoretical orientation, the previously dominant "Bad Apple" hypothesis declined from 54 to 30%, while the "Wicked System" hypothesis increased from 46 to 52%. Furthermore, there has been a pronounced trend toward testing solutions, rising from 31 to 56% at the expense of merely describing the problem, which fell from 69 to 44%.

Conclusion: Three gaps highlighted eight years ago by the previous scoping review remain unresolved. Research on decision makers (e.g., scientists in positions of power, policymakers, accounting for 3%), the private research sector and patents (4.7%), and the peer review system (0.3%) continues to be underexplored. Even more concerning, if current trends persist, these gaps are likely to become increasingly problematic.