Transparency In Research Research Articles

Transparency, openness, and reproducible research practices are frequently underused in health economic evaluations

ObjectivesTo investigate the extent to which articles of economic evaluations of healthcare interventions indexed in MEDLINE incorporate research practices that promote transparency, openness, and reproducibility. Study Design and SettingWe evaluated a random sample of health economic evaluations indexed in MEDLINE during 2019. We included articles written in English reporting an incremental cost-effectiveness ratio in terms of costs per life years gained, quality-adjusted life years, and/or disability-adjusted life years. Reproducible research practices, openness, and transparency in each article were extracted in duplicate. We explored whether reproducible research practices were associated with self-report use of a guideline. ResultsWe included 200 studies published in 147 journals. Almost half were published as open access articles (n = 93; 47%). Most studies (n = 150; 75%) were model-based economic evaluations. In 109 (55%) studies, authors self-reported use a guideline (e.g., for study conduct or reporting). Few studies (n = 31; 16%) reported working from a protocol. In 112 (56%) studies, authors reported the data needed to recreate the incremental cost-effectiveness ratio for the base case analysis. This percentage was higher in studies using a guideline than studies not using a guideline (72/109 [66%] with guideline vs. 40/91 [44%] without guideline; risk ratio 1.50, 95% confidence interval 1.15–1.97). Only 10 (5%) studies mentioned access to raw data and analytic code for reanalyses. ConclusionTransparency, openness, and reproducible research practices are frequently underused in health economic evaluations. This study provides baseline data to compare future progress in the field.

Improving Agricultural Policy Decisions through Replications

SummaryCurrently, policy decisions are often made based on untested scientific results. Replication studies repeat previously published research and, thus, are an effective way to test the validity and reliability of research studies, as well as to test the potential for generalisations of such studies. Replications can contribute to improved policy decisions and thus more efficient use of resources. To date, very few replications of research in agricultural economics are available and the incentives to engage in replications are low. Moreover, the conditions for replicating studies are poor. For example, published articles often lack full transparency in terms of documentation, data and computer code. This Point de Vue highlights the advantages of striving for conditions that facilitate replication studies and foster such a culture in agricultural economics. Policymakers could explicitly invite and support replications of studies that are key for good policymaking. To this end, they can address both demand‐side and supply‐side problems of replications, for example, by inviting, valuing and supporting replications of policy‐relevant analyses and by providing institutional and legal infrastructure facilitating open science and replications. With this, policy can support the agricultural economics profession, while agricultural economists can support sound policymaking, both reaping the benefits of a more transparent research culture.

Analysing the informal economy: Data challenges, research design, and research transparency

AbstractAnalyses of the informal economy are vital to understanding economic activity in developing countries, but challenges abound when analysing something that is so difficult to measure. In this article, we explore these challenges and what they mean for research and research design in studies of the informal economy. We review key economic theories developed to study the informal economy, before critically discussing the range of methods of data collection available for researchers. All approaches to data collection have limitations, yet many studies fail to reflect adequately on these in their design and presentation. In reviewing data sources for economic analyses of informality, we give particular attention to surveys designed and led by academic researchers, the consideration of which is omitted from leading official organisations' own reports on data collection in the informal economy. In the absence of a unifying theory and data sources that deliver the ‘comprehensive and accurate’ data called for by some authors we argue, first, that no one source of data is intrinsically superior; and second, that research on the informal economy must embrace transparency—around the data used, their alignment with the underlying theory adopted, and the detailed arrangements for data collection and analysis.

Navigating the polycrisis—governing for transformation: The 2024 agenda for the systems community

AbstractThe challenges of the Anthropocene were pre‐empted by systems scholars in the exposition of the ‘global problematique’ and are now made manifest in what systems scholars called the polycrisis. These framings alert us to our human circumstances but to date, have done little to transform our manners of being and doing, as the polycrisis is an outcome of a profound governance crisis. Ongoing reflections, building on the framing offered by the global problematique, in the IFSR Conversations in 2023 addressed these issues. Advocating for more epistemological transparency in systems research was a major theme to emerge. Widening the gaze and embracing the full capacity of the cybersystemic perspective of systems research seeks to allow IFSR members, and cybersystemic scholars more generally, to harness their understandings and praxes to bring fresh momentum to navigating the polycrisis and governing for transformation.

AMS Publications Support for Open, Transparent, and Equitable Research

AMS Publications Support for Open, Transparent, and Equitable Research

AMS Publications Support for Open, Transparent, and Equitable Research

AMS Publications Support for Open, Transparent, and Equitable Research

AMS Publications Support for Open, Transparent, and Equitable Research

AMS Publications Support for Open, Transparent, and Equitable Research

AMS Publications Support for Open, Transparent, and Equitable Research

AMS Publications Support for Open, Transparent, and Equitable Research

AMS Publications Support for Open, Transparent, and Equitable Research

AMS Publications Support for Open, Transparent, and Equitable Research

AMS Publications Support for Open, Transparent, and Equitable Research

AMS Publications Support for Open, Transparent, and Equitable Research

AMS Publications Support for Open, Transparent, and Equitable Research

AMS Publications Support for Open, Transparent, and Equitable Research

AMS Publications Support for Open, Transparent, and Equitable Research

AMS Publications Support for Open, Transparent, and Equitable Research

Increased endorsement of TRIPOD and other reporting guidelines by high impact factor journals: survey of instructions to authors

ObjectivesTo assess the endorsement of reporting guidelines by high impact factor journals over the period 2017–2022, with a specific focus on the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis (TRIPOD) statement. Study Design and SettingWe searched the online ‘instructions to authors’ of high impact factor medical journals in February 2017 and in January 2022 for any reference to reporting guidelines and TRIPOD in particular. ResultsIn 2017, 205 out of 337 (61%) journals mentioned any reporting guideline in their instructions to authors and in 2022 this increased to 245 (73%) journals. A reference to TRIPOD was provided by 27 (8%) journals in 2017 and 67 (20%) in 2022. Of those journals mentioning TRIPOD in 2022, 22% provided a link to the TRIPOD website and 60% linked to TRIPOD information on the Enhancing the QUAlity and Transparency Of health Research (EQUATOR) Network website. Twenty-five percent of the journals required adherence to TRIPOD. ConclusionAbout three-quarters of high-impact medical journals endorse the use of reporting guidelines and 20% endorse TRIPOD. Transparent reporting is important in enhancing the usefulness of health research and endorsement by journals plays a critical role in this.

The Impact of Artificial Intelligence on Optimizing Diagnosis and Treatment Plans for Rare Genetic Disorders.

Rare genetic disorders (RDs), characterized by their low prevalence and diagnostic complexities, present significant challenges to healthcare systems. This article explores the transformative impact of artificial intelligence (AI) and machine learning (ML) in addressing these challenges. It emphasizes the need for accurate and early diagnosis of RDs, often hindered by genetic and clinical heterogeneity. This article discusses how AI and ML are reshaping healthcare, providing examples of their effectiveness in disease diagnosis, prognosis, image analysis, and drug repurposing. It highlights AI's ability to efficiently analyze extensive datasets and expedite diagnosis, showcasing case studies like Face2Gene. Furthermore, the article explores how AI tailors treatment plans for RDs, leveraging ML and deep learning (DL) to create personalized therapeutic regimens. It emphasizes AI's role in drug discovery, including the identification of potential candidates for rare disease treatments. Challenges and limitations related to AI in healthcare, including ethical, legal, technical, and human aspects, are addressed. This article underscores the importance of data ethics, privacy, and algorithmic fairness, as well as the need for standardized evaluation techniques and transparency in AI research. It highlights second-generation AI systems that prioritize patient-centric care, efficient patient recruitment for clinical trials, and the significance of high-quality data. The integration of AI with telemedicine, the growth of health databases, and the potential for personalized therapeutic recommendations are identified as promising directions for the field. In summary, this article provides a comprehensive exploration of how AI and ML are revolutionizing the diagnosis and treatment of RDs, addressing challenges while considering ethical implications in this rapidly evolving healthcare landscape.

Evaluation of Transparency and Openness Guidelines in Physical Therapist Journals.

The goals of this study were to evaluate the extent that physical therapist journals support open science research practices by adhering to the Transparency and Openness Promotion (TOP) guidelines and to assess the relationship between journal scores and their respective journal impact factor (JIF). Scimago, mapping studies, the National Library of Medicine, and journal author guidelines were searched to identify physical therapist journals for inclusion. Journals were graded on 10 standards (29 available total points) related to transparency with data, code, research materials, study design and analysis, preregistration of studies and statistical analyses, replication, and open science badges. The relationship between journal transparency and openness scores and their JIF was determined. Thirty-five journals' author guidelines were assigned transparency and openness factor scores. The median score (interquartile range) across journals was 3.00 out of 29 (3.00) points (for all journals the scores ranged from 0 to 8). The 2 standards with the highest degree of implementation were design and analysis transparency (reporting guidelines) and study preregistration. No journals reported on code transparency, materials transparency, replication, and open science badges. TOP factor scores were a significant predictor of JIF scores. There is low implementation of the TOP standards by physical therapist journals. TOP factor scores demonstrated predictive abilities for JIF scores. Policies from journals must improve to make open science practices the standard in research. Journals are in an influential position to guide practices that can improve the rigor of publication which, ultimately, enhances the evidence-based information used by physical therapists. Transparent, open, and reproducible research will move the profession forward by improving the quality of research and increasing the confidence in results for implementation in clinical care.

Autonomous, bidding, credible, decentralized, ethical, and funded (ABCDEF) publishing.

Scientists write research articles, process ethics reviews, evaluate proposals and research, and seek funding. Several strategies have been proposed to optimize these operations and to decentralize access to research resources and opportunities. For instance, we previously proposed the trinity review method, combining registered reports with financing and research ethics assessments. However, previously proposed systems have a number of shortcomings, including how to implement them, e.g., who manages them, how incentives for reviewers are paid, etc. Various solutions have been proposed to address these issues, employing methods based on blockchain technologies, called "decentralized science (DeSci)". Decentralized approaches that exploit these developments offer potentially profound improvements to the troubled scientific ecosystem. Here, we propose a system that integrates ethics reviews, peer reviews, and funding in a decentralized manner, based on Web3 technology. This new method, named ABCDEF publishing, would enhance the speed, fairness, and transparency of scientific research and publishing.

A call to implement preclinical study registration in animal ethics review.

Protocol registration is required in clinical trials. Registration of animal studies could improve research transparency and reduce redundancy, yet uptake has been minimal. Integrating study registration into institutional approval of animal use protocols is a promising approach to increase uptake.

Toward the Conceptualization of Data Quality Assurance in Research Data Repositories

ABSTRACTData quality assurance (DQA) is critical to research data sharing and reuse. There has been a growing recognition of data transparency, reproducibility, credibility, and validity in research. Although the research data curation literature is large, it lacks data quality theory‐guided examinations of DQA practices in research data repositories. This poster paper reports on the preliminary findings of a larger study that examines DQA practices in research data repositories, including their use of DQA ontologies, standards, and metadata vocabularies. In particular, the paper examines two quality standards and an ontology for their conceptualization of DQA activities and their structure. The authors used the findings of the analysis and the data quality literature to synthesize an initial model of a DQA process in research data repositories that conceptualizes three DQA activities: evaluation, intervention, and communication. This paper can inform the development of ontologies and best practice guides for designing and evaluating DQA workflows in research data repositories.

AMS Publications Support for Open, Transparent, and Equitable Research

AMS Publications Support for Open, Transparent, and Equitable Research

AMS Publications Support for Open, Transparent, and Equitable Research

AMS Publications Support for Open, Transparent, and Equitable Research