Creating a database of internet-based clinical trials to support a public-led research programme: A descriptive analysis

Background: Online trials are rapidly growing in number, offering potential benefits but also methodological, ethical and social challenges. The International Network for Knowledge on Well-being (ThinkWell™) aims to increase public and patient participation in the prioritisation, design and conduct of research through the use of technologies. Objective: We aim to provide a baseline understanding of the online trial environment, determining how many trials have used internet-based technologies; how they have been used; and how use has developed over time. Methods: We searched a range of bibliographic databases to March 2015, with no date limits, supplemented by citation searching and references provided by experts in the field. Results were screened against inclusion and exclusion criteria, and included studies mapped against a number of key dimensions, with key themes developed iteratively throughout the process. Results: We identified 1992 internet-based trials to March 2015. The number of reported studies increased substantially over the study timeframe. The largest number of trials were conducted in the USA (49.7%), followed by The Netherlands (10.2%); Australia (8.5%); the United Kingdom (5.8%); Sweden (4.6%); Canada (4%); and Germany (2.6%). South Korea (1.5%) has the highest number of reported trials for other continents. There is a predominance of interventions addressing core public health challenges including obesity (8.6%), smoking cessation (5.9%), alcohol abuse (7.7%) and physical activity (10.2%); in mental health issues such as depression (10.9%) and anxiety (5.6%); and conditions where self-management (16.6%) or monitoring (8.1%) is a major feature of care. Conclusions: The results confirm an increase in the use of the internet in trials. Key themes have emerged from the analysis and further research will be undertaken in order to investigate how the data can be used to improve trial design and recruitment, and to build an open access resource to support the public-led research agenda

Why are feasibility studies accessing routinely collected health data? A systematic review

BACKGROUND: Feasibility trials are often undertaken to determine whether a larger randomised controlled trial (RCT) is achievable. In a recent review, 15 feasibility trials accessed routinely collected health data (RCHD) from UK national databases and registries. This paper looks at attributes of these trials and the reasons why they accessed RCHD. METHODS: We extracted data from all publicly available sources for the 15 feasibility studies found in a previous review of trials successfully accessing RCHD in the UK between 2013–2018 for the purpose of informing or supplementing participant data. We extracted trial characteristics, the registry accessed, and the way the RCHD was used. RESULTS: The 15 feasibility RCTs were conducted in a variety of disease areas, and were generally small (median sample size 100, range 41–4061) and individually randomised (60%, 9/15). The primary trial outcome was predominantly administrative (non-clinical) (80%, 12/15) such as feasibility of patient recruitment. They were more likely to recruit from secondary care (67%, 10/15) settings than primary (33%, 5/15). NHS Digital was the most commonly accessed registry (33% (5/15)) with SAIL databank (20% (3/15)), electronic Data Research and Innovation Service (eDRIS) and Paediatric Intensive Care Audit Network (PICANET) (each 13% 2/15) also being accessed. Where the information was clear, the trials used RCHD for data collection during the trial (47%, 7/15), follow-up after the trial (27%, 4/15) and recruitment (13%, 2/15). CONCLUSIONS: Between 2013 and 2018, 15 feasibility trials successfully accessed UK RCHD. Feasibility trials would benefit, as with other trials, from guidance on reporting the use of RCHD in protocols and publications

Sample size calculations for cluster randomised controlled trials with a fixed number of clusters

Background\ud Cluster randomised controlled trials (CRCTs) are frequently used in health service evaluation. Assuming an average cluster size, required sample sizes are readily computed for both binary and continuous outcomes, by estimating a design effect or inflation factor. However, where the number of clusters are fixed in advance, but where it is possible to increase the number of individuals within each cluster, as is frequently the case in health service evaluation, sample size formulae have been less well studied. \ud \ud Methods\ud We systematically outline sample size formulae (including required number of randomisation units, detectable difference and power) for CRCTs with a fixed number of clusters, to provide a concise summary for both binary and continuous outcomes. Extensions to the case of unequal cluster sizes are provided. \ud \ud Results\ud For trials with a fixed number of equal sized clusters (k), the trial will be feasible provided the number of clusters is greater than the product of the number of individuals required under individual randomisation ($n_i$) and the estimated intra-cluster correlation ($\rho$). So, a simple rule is that the number of clusters ($\kappa$) will be sufficient provided: \ud \ud $\kappa$ > $n_i$ x $\rho$\ud \ud Where this is not the case, investigators can determine the maximum available power to detect the pre-specified difference, or the minimum detectable difference under the pre-specified value for power. \ud \ud Conclusions\ud Designing a CRCT with a fixed number of clusters might mean that the study will not be feasible, leading to the notion of a minimum detectable difference (or a maximum achievable power), irrespective of how many individuals are included within each cluster. \ud \u

Forage selection preferences of experienced cows and naïve heifers grazing native tallgrass range during winter

Beef Cattle Research, 2011 is known as Cattlemen’s Day, 2011Estimating the nutritive value of a grazing animal’s diet is a significant challenge. Description of the botanical composition of a grazed diet is vital in that regard. Microhistological analysis of fecal material has been used for estimating the botanical composition of wild and domestic ungulate diets since first described by Baumgartner and Martin in 1939. Little research has been conducted on the diet selection preferences of multiparous beef cows compared to primiparous beef cows. We hypothesized that foraging strategies change as cows age. To that end, our objective was to characterize differences in diet selection between experienced multiparous and naïve primiparous beef cows grazing dormant, native tallgrass pastures during winter

Improving the normalization of complex interventions: measure development based on normalization process theory (NoMAD): study protocol

<b>Background</b> Understanding implementation processes is key to ensuring that complex interventions in healthcare are taken up in practice and thus maximize intended benefits for service provision and (ultimately) care to patients. Normalization Process Theory (NPT) provides a framework for understanding how a new intervention becomes part of normal practice. This study aims to develop and validate simple generic tools derived from NPT, to be used to improve the implementation of complex healthcare interventions.<p></p> <b>Objectives</b> The objectives of this study are to: develop a set of NPT-based measures and formatively evaluate their use for identifying implementation problems and monitoring progress; conduct preliminary evaluation of these measures across a range of interventions and contexts, and identify factors that affect this process; explore the utility of these measures for predicting outcomes; and develop an online users’ manual for the measures.<p></p> <b>Methods</b> A combination of qualitative (workshops, item development, user feedback, cognitive interviews) and quantitative (survey) methods will be used to develop NPT measures, and test the utility of the measures in six healthcare intervention settings.<p></p> <b>Discussion</b> The measures developed in the study will be available for use by those involved in planning, implementing, and evaluating complex interventions in healthcare and have the potential to enhance the chances of their implementation, leading to sustained changes in working practices

The depression in visual impairment trial (DEPVIT): trial design and protocol

<b>Background</b> The prevalence of depression in people with a visual disability is high but screening for depression and referral for treatment is not yet an integral part of visual rehabilitation service provision. One reason for this may be that there is no good evidence about the effectiveness of treatments in this patient group. This study is the first to evaluate the effect of depression treatments on people with a visual impairment and co morbid depression.<p></p> <b>Methods/design</b> The study is an exploratory, multicentre, individually randomised waiting list controlled trial. Participants will be randomised to receive Problem Solving Therapy (PST), a ‘referral to the GP’ requesting treatment according to the NICE’s ‘stepped care’ recommendations or the waiting list arm of the trial. The primary outcome measure is change (from randomisation) in depressive symptoms as measured by the Beck’s Depression Inventory (BDI-II) at 6 months. Secondary outcomes include change in depressive symptoms at 3 months, change in visual function as measured with the near vision subscale of the VFQ-48 and 7 item NEI-VFQ at 3 and 6 months, change in generic health related quality of life (EQ5D), the costs associated with PST, estimates of incremental cost effectiveness, and recruitment rate estimation.<p></p> <b>Discussion</b> Depression is prevalent in people with disabling visual impairment. This exploratory study will establish depression screening and referral for treatment in visual rehabilitation clinics in the UK. It will be the first to explore the efficacy of PST and the effectiveness of NICE’s ‘stepped care’ approach to the treatment of depression in people with a visual impairment.<p></p&gt

Transnational social capital: the socio‐spatialities of civil society

Civil society remains a contested concept, but one that is widely embedded in global development processes. Transnationalism within civil society scholarship is often described dichotomously, either through hierarchical dependency relations or as a more amorphous networked global civil society. These two contrasting spatial imaginaries produce very particular ideas about how transnational relations contribute to civil society. Drawing on empirical material from research with civil society organizations in Barbados and Grenada, in this article I contend that civil society groups use forms of transnational social capital in their work. This does not, however, resonate with the horizontal relations associated with grassroots globalization or vertical chains of dependence. These social relations are imbued with power and agency and are entangled in situated historical, geographical and personal contexts. I conclude that the diverse transnational social relations that are part of civil society activity offer hope and possibilities for continued civil society action in these unexpected spatial arrangements

Planning a cluster randomized trial with unequal cluster sizes: practical issues involving continuous outcomes

BACKGROUND: Cluster randomization design is increasingly used for the evaluation of health-care, screeening or educational interventions. At the planning stage, sample size calculations usually consider an average cluster size without taking into account any potential imbalance in cluster size. However, there may exist high discrepancies in cluster sizes. METHODS: We performed simulations to study the impact of an imbalance in cluster size on power. We determined by simulations to which extent four methods proposed to adapt the sample size calculations to a pre-specified imbalance in cluster size could lead to adequately powered trials. RESULTS: We showed that an imbalance in cluster size can be of high influence on the power in the case of severe imbalance, particularly if the number of clusters is low and/or the intraclass correlation coefficient is high. In the case of a severe imbalance, our simulations confirmed that the minimum variance weights correction of the variation inflaction factor (VIF) used in the sample size calculations has the best properties. CONCLUSION: Publication of cluster sizes is important to assess the real power of the trial which was conducted and to help designing future trials. We derived an adaptation of the VIF from the minimum variance weights correction to be used in case the imbalance can be a priori formulated such as "a proportion (γ) of clusters actually recruit a proportion (τ) of subjects to be included (γ ≤ τ)"