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Reproducible science requires transparent reporting. The ARRIVE guidelines (Animal Research: Reporting of In Vivo Experiments) were originally developed in 2010 to improve the reporting of animal research. They consist of a checklist of information to include in publications describing in vivo experiments to enable others to scrutinise the work adequately, evaluate its methodological rigour and reproduce the methods and results. Despite considerable levels of endorsement by funders and journals over the years, adherence to the guidelines has been inconsistent, and the anticipated improvements in the quality of reporting in animal research publications have not been achieved. Here, we introduce ARRIVE 2.0. The guidelines have been updated and information reorganised to facilitate their use in practice. We used a Delphi exercise to prioritise and divide the items of the guidelines into two sets, the ‘ARRIVE Essential 10’, which constitutes the minimum requirement, and the ‘Recommended Set’, which describes the research context. This division facilitates improved reporting of animal research by supporting a stepwise approach to implementation. This helps journal editors and reviewers verify that the most important items are being reported in manuscripts. We have also developed the accompanying Explanation and Elaboration document, which serves (1) to explain the rationale behind each item in the guidelines, (2) to clarify key concepts and (3) to provide illustrative examples. We aim, through these changes, to help ensure that researchers, reviewers and journal editors are better equipped to improve the rigour and transparency of the scientific process and thus reproducibility.

Background Rapid reviews are an accelerated evidence synthesis approach intended to meet the timely needs of decision-makers in healthcare settings. Quality of conduct and reporting has been described in the rapid review literature; however, no formal assessment has been carried out using available instruments. The objective of this study was to explore compliance with conduct and reporting guidelines in rapid reviews published or posted online during 2013 and 2014. Methods We performed a comprehensive literature search for rapid reviews using multiple bibliographic databases (e.g. PubMed, MEDLINE, EMBASE, the Cochrane Library) through December 31, 2014. Grey literature was searched thoroughly, and health technology assessment agencies were surveyed to identify additional rapid review products. Candidate reviews were assessed for inclusion using pre-specified eligibility criteria. Detailed data was collected from the included reviews on study and reporting characteristics and variables significant to rapid reviews (e.g. nomenclature, definition). We evaluated the quality of conduct and reporting of included rapid reviews using the A Measurement Tool to Assess Systematic Reviews (AMSTAR) and Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklists. Compliance with each checklist item was examined, and the sum of adequately reported items was used to describe overall compliance. Rapid reviews were stratified to explore differences in compliance related to publication status. The association between compliance and time to completion or length of publication was explored through univariate regression. Results Sixty-six rapid reviews were included. There were heterogeneous nomenclature, research questions and approaches to rapid reviews. Compliance with AMSTAR and PRISMA checklists was poor. Published rapid reviews were compliant with individual PRISMA items more often than unpublished reviews, but no difference was seen in AMSTAR item compliance overall. There was evidence of an association between length of publication and time to completion and the number of adequately reported PRISMA or AMSTAR items. Conclusions Transparency and inadequate reporting are significant limitations of rapid reviews. Scientific editors, authors and producing agencies should ensure that the reporting of conduct and findings is accurate and complete. Further research may be warranted to explore reporting and conduct guidelines specific to rapid reviews and how these guidelines may be applied across the spectrum of rapid review approaches.

Generative Artificial Intelligence (AI) tools, particularly large language models (LLMs), are rapidly transforming qualitative data analysis by offering unprecedented speed and scale. However, this integration introduces significant challenges to methodological transparency due to the algorithmic opacity of these “black-box” systems and their hidden decision points. Traditional qualitative reporting guidelines predate generative AI and lack specific guidance for disclosing AI usage. This paper addresses this critical gap by introducing a novel heuristic framework that poses 20 questions across five key themes: The Research Team, Participant Interaction, Study Design, Data Practices, and Data Analysis, providing disclosure actions for each. This framework blends and augments existing frameworks, aligning with principles to guide researchers in meticulously documenting their AI-mediated analytic choices. Methodologically, the framework advances the field by requiring explicit reporting on: the roles of AI tools and the AI literacy of the human research team; AI’s involvement in participant communication, informed consent processes, and safeguards for sensitive demographic data; the alignment of AI tools with theoretical frameworks, their influence on sampling strategies, and discussions during IRB review; data storage, AI’s role in data creation (e.g., synthetic data, transcription, interview protocols), and its assistance in determining data saturation and participant checking; and the precise contributions of AI to coding and thematic categorization, alongside detailed documentation of iterative human-AI interactions and prompts used. By fostering rigorous audit trails and comprehensive documentation, the framework aims to maximize transparency, ensure methodological rigor, and uphold ethical standards in AI-augmented qualitative inquiry, thereby enhancing the credibility of findings.

Background Machine learning (ML) and artificial intelligence (AI) applications have increased across different stages of clinical research. Their use in clinical trials (CTs) has been discussed but not quantified. Methods A scoping review was conducted by searching PubMed, Embase (Ovid), and Scopus for CTs or protocols. The goal was to understand the extent of ML and AI applications in the design, conduct, and analysis of CTs. Screening was performed on Covidence, with GPT model support. Findings After title/abstract and full-text screening, 108 records were included; in some studies, AI/ML was applied across multiple stages. For the design, 20 studies involved advanced methods, six applied them to stratification, four to treatment selection during randomization, six to participant selection, two for outcome assessment, and two for site selection. Seven studies involved them in the collection and analysis of data from wearable devices, and one for monitoring. More commonly, AI/ML has been used at the analysis stage of 93 CTs; however, limitations in reporting trial objectives make it difficult to distinguish the purpose between primary and exploratory analyses. Interpretation This research identifies a serious mismatch between the potential and actual applications of ML in CTs. Considering the potential benefits of ML in CTs, such underuse could hinder the evolution of CTs toward faster and more efficient approaches.

Outcome Measures in Rheumatology promotes standardized outcome measures. No such organization exists for nephrology. We compared the reporting and homogeneity of outcome measures in registered protocols of randomized trials in rheumatology and nephrology. Data were extracted from protocols for rheumatoid arthritis or nephroprotection registered in ClinicalTrials.gov. We rated five outcome items (domain, specific measurement, specific metric, method of aggregating data, and time frame) to obtain a 5-point score. We split outcomes into clusters that could be pooled for meta-analysis, and assessed the proportion of trials and patients by cluster. We selected 75 protocols for rheumatology and 66 for nephrology. A high adjusted score for outcomes was associated with rheumatology protocols (odds ratio, 4.2; 95% confidence interval, 2.39, 7.39). We retained 13 clusters of outcomes for rheumatology, and one of one outcome (American College Rheumatology Criteria) could pool 87.1% of trials and 92.8% of patients. We retained eight clusters for nephrology, and one of four outcomes (assessing proteinuria) could pool 83.1% of trials and 44.7% of patients. The reporting and homogeneity of outcomes is better in registered protocols of rheumatology than nephrology. The presence of international guidelines on outcome measurement may explain the differences.

Background:The Declaration of Helsinki prohibits the publication of articles that do not meet defined ethical standards for reporting of research ethics board (REB) approval and informed consent. Despite this prohibition and a call to highlight the deficiency for the reader, articles with potential ethical shortcomings continue to be published.Objective:To determine what proportion of articles in major medical journals lack statements confirming REB approval and informed consent, and whether accompanying commentary alerts readers to this deficiency.Design:Retrospective, observational study.Setting:Online review of five major medical journals.Population:All clinical research articles published online between 1 January 2005 and 31 December 2006 in the BMJ, Lancet, Annals of Internal Medicine, JAMA and the New England Journal of Medicine.Measurements:Statement of REB approval and informed consent.Results:Of 1780 articles reviewed, 1133 (63.7%) met inclusion criteria (manuscripts reporting human subjects, human tissue or identifiable personal data research), 36 (3.2%) articles lacked a statement of REB approval, 62 (5.5%) lacked disclosure of informed consent and 15 (1.3%) articles lacked both. Articles that did not state REB approval were associated with not stating informed consent (p<0.001). There were no editorial comments to alert readers to the lack of either REB approval or informed consent statements associated with any of the deficient articles.Conclusions:Articles that lack explicit statements of REB approval and informed consent are infrequent but continue to be published in major medical journals without editorial statements to alert the reader to this deficiency.

Theoretically, the reporting and conduct of research should be in harmony. In practice, however, while good reporting promotes enlightenment and clarity, poor reporting creates ambiguities and confusions. Most developers of reporting guidelines embrace an intense interest in improving the design and conduct of health research. A further confusion between reporting and conduct emanates from the misuse of reporting guidelines. This misuse often takes the form of researchers using a guideline to develop a quality score for conduct of studies. If the description of allocation concealment reported in an article meets that quality criterion, a reader would likely judge the trial to be of good quality on the allocation concealment item in CONsolidated Standards Of Reporting Trials (CONSORT) 2010.

Many industry professionals will likely find that some of their clients are not yet conducting background checks or are using inadequate background checks that can leave worrying gaps in a candidate's history. In these cases, clients could naturally expect their dealer or integrator to provide high-quality background checks.

The historical background of international business codes of conduct are reviewed, with a discussion of some of the provisions of the current codes and a consideration of some of the issues which the existence of the codes may create. Current problems include restrictive business practices and corrupt practices. In the coming years, there will be additional codes of conduct adopted by various multilateral groups. A significant effect of the Organization for Economic Cooperation and Development (OECD) will probably concern financial disclosure provisions since recommendations of disclosure of financial information in the OECD's Guidelines is more comprehensive than SEC financial reporting requirements. Codes of conduct will become more prevalent as a multilateral response to the activities of multinational corporations.