28 research outputs found
A re-randomisation design for clinical trials
Background: Recruitment to clinical trials is often problematic, with many trials failing to recruit to their target sample size. As a result, patient care may be based on suboptimal evidence from underpowered trials or non-randomised studies. Methods: For many conditions patients will require treatment on several occasions, for example, to treat symptoms of an underlying chronic condition (such as migraines, where treatment is required each time a new episode occurs), or until they achieve treatment success (such as fertility, where patients undergo treatment on multiple occasions until they become pregnant). We describe a re-randomisation design for these scenarios, which allows each patient to be independently randomised on multiple occasions. We discuss the circumstances in which this design can be used. Results: The re-randomisation design will give asymptotically unbiased estimates of treatment effect and correct type I error rates under the following conditions: (a) patients are only re-randomised after the follow-up period from their previous randomisation is complete; (b) randomisations for the same patient are performed independently; and (c) the treatment effect is constant across all randomisations. Provided the analysis accounts for correlation between observations from the same patient, this design will typically have higher power than a parallel group trial with an equivalent number of observations. Conclusions: If used appropriately, the re-randomisation design can increase the recruitment rate for clinical trials while still providing an unbiased estimate of treatment effect and correct type I error rates. In many situations, it can increase the power compared to a parallel group design with an equivalent number of observations
What we talk about when we talk about "global mindset": managerial cognition in multinational corporations
Recent developments in the global economy and in multinational corporations have placed significant emphasis on the cognitive orientations of managers, giving rise to a number of concepts such as āglobal mindsetā that are presumed to be associated with the effective management of multinational corporations (MNCs). This paper reviews the literature on global mindset and clarifies some of the conceptual confusion surrounding the construct. We identify common themes across writers, suggesting that the majority of studies fall into one of three research perspectives: cultural, strategic, and multidimensional. We also identify two constructs from the social sciences that underlie the perspectives found in the literature: cosmopolitanism and cognitive complexity and use these two constructs to develop an integrative theoretical framework of global mindset. We then provide a critical assessment of the field of global mindset and suggest directions for future theoretical and empirical research
Using re-randomization to increase the recruitment rate in clinical trials - an assessment of three clinical areas
Recruiting faith- and non-faith-based schools, adolescents and parents to a cluster randomised sexual-health trial: experiences, challenges and lessons from the mixed-methods Jack Feasibility Trial
A study of target effect sizes in randomised controlled trials published in the Health Technology Assessment journal
BACKGROUND: When designing a randomised controlled trial (RCT), an important consideration is the sample size required. This is calculated from several components; one of which is the target difference. This study aims to review the currently reported methods of elicitation of the target difference as well as to quantify the target differences used in Health Technology Assessment (HTA)-funded trials. METHODS: Trials were identified from the National Institute of Health Research Health Technology Assessment journal. A total of 177 RCTs published between 2006 and 2016 were assessed for eligibility. Eligibility was established by the design of the trial and the quality of data available. The trial designs were parallel-group, superiority RCTs with a continuous primary endpoint. Data were extracted and the standardised anticipated and observed effect size estimates were calculated. Exclusion criteria was based on trials not providing enough detail in the sample size calculation and results, and trials not being of parallel-group, superiority design. RESULTS: A total of 107 RCTs were included in the study from 102 reports. The most commonly reported method for effect size derivation was a review of evidence and use of previous research (52.3%). This was common across all clinical areas. The median standardised target effect size was 0.30 (interquartile range: 0.20-0.38), with the median standardised observed effect size 0.11 (IQR 0.05-0.29). The maximum anticipated and observed effect sizes were 0.76 and 1.18, respectively. Only two trials had anticipated target values above 0.60. CONCLUSION: The most commonly reported method of elicitation of the target effect size is previous published research. The average target effect size was 0.3. A clear distinction between the target difference and the minimum clinically important difference is recommended when designing a trial. Transparent explanation of target difference elicitation is advised, with multiple methods including a review of evidence and opinion-seeking advised as the more optimal methods for effect size quantification
Benefits and challenges of using the cohort multiple randomised controlled trial design for testing an intervention for depression
This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise statedThe DEPSY trial was funded as part of PVās doctoral research project. This project received funding from multiple sources, including private donors in Germany, Norway, Sweden and the United Kingdom as well as from a National Institute for Health Research senior investigator award
Protocol for the development of a CONSORT extension for RCTs using cohorts and routinely collected health data.
Background: Randomized controlled trials (RCTs) are often complex and expensive to perform. Less than one third achieve planned recruitment targets, follow-up can be labor-intensive, and many have limited real-world generalizability. Designs for RCTs conducted using cohorts and routinely collected health data, including registries, electronic health records, and administrative databases, have been proposed to address these challenges and are being rapidly adopted. These designs, however, are relatively recent innovations, and published RCT reports often do not describe important aspects of their methodology in a standardized way. Our objective is to extend the Consolidated Standards of Reporting Trials (CONSORT) statement with a consensus-driven reporting guideline for RCTs using cohorts and routinely collected health data. Methods: The development of this CONSORT extension will consist of five phases. Phase 1 (completed) consisted of the project launch, including fundraising, the establishment of a research team, and development of a conceptual framework. In phase 2, a systematic review will be performed to identify publications (1) that describe methods or reporting considerations for RCTs conducted using cohorts and routinely collected health data or (2) that are protocols or report results from such RCTs. An initial "long list" of possible modifications to CONSORT checklist items and possible new items for the reporting guideline will be generated based on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) and The REporting of studies Conducted using Observational Routinely-collected health Data (RECORD) statements. Additional possible modifications and new items will be identified based on the results of the systematic review. Phase 3 will consist of a three-round Delphi exercise with methods and content experts to evaluate the "long list" and generate a "short list" of key items. In phase 4, these items will serve as the basis for an in-person consensus meeting to finalize a core set of items to be included in the reporting guideline and checklist. Phase 5 will involve drafting the checklist and elaboration-explanation documents, and dissemination and implementation of the guideline. Discussion: Development of this CONSORT extension will contribute to more transparent reporting of RCTs conducted using cohorts and routinely collected health data
Reasons for non-recruitment of eligible patients to a randomised controlled trial of secondary prevention after intracerebral haemorrhage: observational study.
Recruitment to randomised prevention trials is challenging, not least for intracerebral haemorrhage (ICH) associated with antithrombotic drug use. We investigated reasons for not recruiting apparently eligible patients at hospital sites that keep screening logs in the ongoing REstart or STop Antithrombotics Randomised Trial (RESTART), which seeks to determine whether to start antiplatelet drugs after ICH.EDGE project number 14013British Heart Foundation Special Project (SP/12/2/29422) & Project (PG/14/50/30891) fundin
Can testing clinical significance reduce false positive rates in randomized controlled trials? A snap review
Dynamic consent: a patient interface for twenty-first century research networks
Biomedical research is being transformed through the application of information technologies that allow ever greater amounts of data to be shared on an unprecedented scale. However, the methods for involving participants have not kept pace with changes in research capability. In an era when information is shared digitally at the global level, mechanisms of informed consent remain static, paper-based and organised around national boundaries and legal frameworks. Dynamic consent (DC) is both a specific project and a wider concept that offers a new approach to consent; one designed to meet the needs of the twenty-first century research landscape. At the heart of DC is a personalised, digital communication interface that connects researchers and participants, placing participants at the heart of decision making. The interface facilitates two-way communication to stimulate a more engaged, informed and scientifically literate participant population where individuals can tailor and manage their own consent preferences. The technical architecture of DC includes components that can securely encrypt sensitive data and allow participant consent preferences to travel with their data and samples when they are shared with third parties. In addition to improving transparency and public trust, this system benefits researchers by streamlining recruitment and enabling more efficient participant recontact. DC has mainly been developed in biobanking contexts, but it also has potential application in other domains for a variety of purposes