bioRxiv ScienceSearch

bioRxiv · 10.1101/773945

Evaluation of Reproducibility in Urology Publications

Abstract

Take Home MessageMany components of transparency and reproducibility are lacking in urology publications, making study replication, at best, difficult.\n\nIntroductionReproducibility is essential for the integrity of scientific research. Reproducibility is measured by the ability of investigators to replicate the outcomes of an original publication by using the same materials and procedures.\n\nMethodsWe sampled 300 publications in the field of urology for assessment of multiple indicators of reproducibility, including material availability, raw data availability, analysis script availability, pre-registration information, links to protocols, and whether the publication was freely available to the public. Publications were also assessed for statements about conflicts of interest and funding sources.\n\nResultsOf the 300 sample publications, 171 contained empirical data and could be analyzed for reproducibility. Of the analyzed articles, 0.58% (1/171) provided links to protocols, and none of the studies provided analysis scripts. Additionally, 95.91% (164/171) did not provide accessible raw data, 97.53% (158/162) did not provide accessible materials, and 95.32% (163/171) did not state they were pre-registered.\n\nConclusionCurrent urology research does not consistently provide the components needed to reproduce original studies. Collaborative efforts from investigators and journal editors are needed to improve research quality, while minimizing waste and patient risk.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Rauh, S. L., Johnson, B. S., Bowers, A., Tritz, D., Vassar, M.. 2019-09-25. Evaluation of Reproducibility in Urology Publications. https://doi.org/10.1101/773945

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Evaluating Large Language Models as Tools to Navigate Researchers in Rapidly Evolving Research Landscapes: A Case Study in Cancer Drug Response Prediction

Large Language Models (LLMs) have emerged as promising tools for assisting researchers in automating and accelerating the synthesis of literature reviews. However, their reliability is a significant concern due to issues like factual inaccuracies and hallucinations. The key question is whether LLMs can reliably provide comprehensive, up-to-date overviews and analyses. This study evaluates the performance of three leading LLMs (OpenAI's ChatGPT, Google's Gemini, and DeepSeek) on the complex task of generating a comprehensive survey paper on deep learning for cancer Drug Response Prediction (DRP). By testing both standard and Deep Research (DR) / Deep Think (DT) modes of LLMs with prompts of varying detail, this paper assesses key academic dimensions, including reference management, content quality, and analytical depth. Key findings reveal that while DR modes of LLMs significantly improve reliability by eliminating hallucinations, performance variations exist across models and prompts. A trade-off between reference quantity and integration quality was observed, and even the best-performing models lacked the analytical depth of human experts, often requiring extensive human supervision. The study concludes that LLMs currently serve as powerful assistive tools but still cannot replace the critical validation and synthesis provided by human researchers. Choosing the best LLM to use depends on the task in hand, while several strategies can be implemented to improve the produced output.

scientific communication and education

Plagiarism in Brazil: A perspective of 25,000 PhD holders across the sciences

When it comes to ownership of ideas in science, Robert K. Merton (1957) observed in Priorities in Scientific Discovery: A Chapter in the Sociology of Science that "what is true of physics, chemistry, astronomy, medicine and mathematics is true also of all the other scientific disciplines, not excluding the social and psychological sciences". However, consensus over related issues, such as what constitutes plagiarism in these fields cannot be taken for granted. We conducted a comprehensive study on plagiarism views among PhD holders registered in the database of the Brazilian National Council for Scientific and Technological Development (CNPq). We collected 25,157 valid responses encompassing views and attitudes toward plagiarism from a probability sample of PhD holders across the fields, including biologists, physicists, mathematicians, and engineers as well as linguists, philosophers and anthropologists. The results suggest that core principles about plagiarism are shared among this multidisciplinary community and that they corroborate Mertons observations. Before this study, we could only speculate that this is the case. With these data from a probability sample of Brazilian academia (PhD holders), this study offers insight into the way plagiarism is perceived across the sciences, including the literature and arts, and sheds light on the problem in the context of international collaborative research networks. The data focus on a young research system in Latin America, but, given the cultural similarities that bind most Latin-American nations, these results may be relevant to other PhD populations in the region and should provide a comparison with studies from other emerging, non-Anglophone regions.

scientific communication and education

Turn of Events: Academic events as a platform for preregistration

Prereg posters are conference posters that present planned scientific projects. We provide preliminary evidence for their value in receiving constructive feedback, promoting open science, and supporting early career researchers.View Full Text

scientific communication and education