398 research outputs found
Extended brief intervention to address alcohol misuse in people with mild to moderate intellectual disabilities living in the community (EBI-ID): study protocol for a randomised controlled trial.
There is some evidence that people with intellectual disabilities who live in the community are exposed to the same risks of alcohol use as the rest of the population. Various interventions have been evaluated in the general population to tackle hazardous or harmful drinking and alcohol dependence, but the literature evaluating interventions is very limited regarding intellectual disabilities. The National Institute for Health and Clinical Excellence recommends that brief and extended brief interventions be used to help young persons and adults who have screened as positive for hazardous and harmful drinking. The objective of this trial is to investigate the feasibility of adapting and delivering an extended brief intervention (EBI) to persons with mild/moderate intellectual disability who live in the community and whose level of drinking is harmful or hazardous
Bayesian hierarchical model for the prediction of football results
The problem of modelling football data has become increasingly popular in the last few years and many different models have been proposed with the aim of estimating the characteristics that bring a team to lose or win a game, or to predict the score of a particular match. We propose a Bayesian hierarchical model to fulfil both these aims and test its predictive strength based on data about the Italian Serie A 1991-1992 championship. To overcome the issue of overshrinkage produced by the Bayesian hierarchical model, we specify a more complex mixture model that results in a better fit to the observed data. We test its performance using an example of the Italian Serie A 2007-2008 championship
Joint Longitudinal Models for Dealing With Missing at Random Data in Trial-Based Economic Evaluations
OBJECTIVES: In trial-based economic evaluation, some individuals are typically associated with missing data at some time point, so that their corresponding aggregated outcomes (eg, quality-adjusted life-years) cannot be evaluated. Restricting the analysis to the complete cases is inefficient and can result in biased estimates, while imputation methods are often implemented under a missing at random (MAR) assumption. We propose the use of joint longitudinal models to extend standard approaches by taking into account the longitudinal structure to improve the estimation of the targeted quantities under MAR. METHODS: We compare the results from methods that handle missingness at an aggregated (case deletion, baseline imputation, and joint aggregated models) and disaggregated (joint longitudinal models) level under MAR. The methods are compared using a simulation study and applied to data from 2 real case studies. RESULTS: Simulations show that, according to which data affect the missingness process, aggregated methods may lead to biased results, while joint longitudinal models lead to valid inferences under MAR. The analysis of the 2 case studies support these results as both parameter estimates and cost-effectiveness results vary based on the amount of data incorporated into the model. CONCLUSIONS: Our analyses suggest that methods implemented at the aggregated level are potentially biased under MAR as they ignore the information from the partially observed follow-up data. This limitation can be overcome by extending the analysis to a longitudinal framework using joint models, which can incorporate all the available evidence
Estimating the Expected Value of Partial Perfect Information in Health Economic Evaluations using Integrated Nested Laplace Approximation
The Expected Value of Perfect Partial Information (EVPPI) is a
decision-theoretic measure of the "cost" of parametric uncertainty in decision
making used principally in health economic decision making. Despite this
decision-theoretic grounding, the uptake of EVPPI calculations in practice has
been slow. This is in part due to the prohibitive computational time required
to estimate the EVPPI via Monte Carlo simulations. However, recent developments
have demonstrated that the EVPPI can be estimated by non-parametric regression
methods, which have significantly decreased the computation time required to
approximate the EVPPI. Under certain circumstances, high-dimensional Gaussian
Process regression is suggested, but this can still be prohibitively expensive.
Applying fast computation methods developed in spatial statistics using
Integrated Nested Laplace Approximations (INLA) and projecting from a
high-dimensional into a low-dimensional input space allows us to decrease the
computation time for fitting these high-dimensional Gaussian Processes, often
substantially. We demonstrate that the EVPPI calculated using our method for
Gaussian Process regression is in line with the standard Gaussian Process
regression method and that despite the apparent methodological complexity of
this new method, R functions are available in the package BCEA to implement it
simply and efficiently
A Virtual Conversational Agent for Teens with Autism: Experimental Results and Design Lessons
We present the design of an online social skills development interface for
teenagers with autism spectrum disorder (ASD). The interface is intended to
enable private conversation practice anywhere, anytime using a web-browser.
Users converse informally with a virtual agent, receiving feedback on nonverbal
cues in real-time, and summary feedback. The prototype was developed in
consultation with an expert UX designer, two psychologists, and a pediatrician.
Using the data from 47 individuals, feedback and dialogue generation were
automated using a hidden Markov model and a schema-driven dialogue manager
capable of handling multi-topic conversations. We conducted a study with nine
high-functioning ASD teenagers. Through a thematic analysis of post-experiment
interviews, identified several key design considerations, notably: 1) Users
should be fully briefed at the outset about the purpose and limitations of the
system, to avoid unrealistic expectations. 2) An interface should incorporate
positive acknowledgment of behavior change. 3) Realistic appearance of a
virtual agent and responsiveness are important in engaging users. 4)
Conversation personalization, for instance in prompting laconic users for more
input and reciprocal questions, would help the teenagers engage for longer
terms and increase the system's utility
A predictable outcome
Gianluca Baio and Roberto Cerina used a modified version of a dynamic Bayesian forecasting model to "predict" the 2014 US Senate elections. The results bode well for the 2016 vote
Calculating the Expected Value of Sample Information in Practice: Considerations from Three Case Studies
Investing efficiently in future research to improve policy decisions is an
important goal. Expected Value of Sample Information (EVSI) can be used to
select the specific design and sample size of a proposed study by assessing the
benefit of a range of different studies. Estimating EVSI with the standard
nested Monte Carlo algorithm has a notoriously high computational burden,
especially when using a complex decision model or when optimizing over study
sample sizes and designs. Therefore, a number of more efficient EVSI
approximation methods have been developed. However, these approximation methods
have not been compared and therefore their relative advantages and
disadvantages are not clear. A consortium of EVSI researchers, including the
developers of several approximation methods, compared four EVSI methods using
three previously published health economic models. The examples were chosen to
represent a range of real-world contexts, including situations with multiple
study outcomes, missing data, and data from an observational rather than a
randomized study. The computational speed and accuracy of each method were
compared, and the relative advantages and implementation challenges of the
methods were highlighted. In each example, the approximation methods took
minutes or hours to achieve reasonably accurate EVSI estimates, whereas the
traditional Monte Carlo method took weeks. Specific methods are particularly
suited to problems where we wish to compare multiple proposed sample sizes,
when the proposed sample size is large, or when the health economic model is
computationally expensive. All the evaluated methods gave estimates similar to
those given by traditional Monte Carlo, suggesting that EVSI can now be
efficiently computed with confidence in realistic examples.Comment: 11 pages, 3 figure
"Fishing na everybody business": women's work and gender relations in Sierra Leone's fisheries
While small-scale marine fisheries in many developing countries is "everybody’s business", a strong gendered division of labour sees production concentrated in the hands of male fishermen - while women - ‘fish mammies’ - invariably dominate the post-harvest processing and retailing sector. Consequently, the production bias of many fisheries management programmes has not only largely overlooked the critical role that fisherwomen play in the sector, but has also seen ‘fish mammies’ marginalised in terms of resource and training support. This paper employs a gender aware livelihoods framework to make the economic space occupied by women in the small-scale fisheries sector in Sierra Leone more ‘visible’, and highlights how their variegated access to different livelihood capitals and resources interact with gendered social norms and women’s reproductive work. We argue for more social and economic investments in women’s fish processing and reproductive work, so as to enable them to reconcile both roles more effectively
Optomechanical transport of cold atoms induced by structured light
Optomechanical pattern forming instabilities in a cloud of cold atoms lead to self-organized spatial structures of light and atoms. Here, we consider the optomechanical self-structuring of a cold atomic cloud in the presence of a phase structured input field, carrying orbital angular momentum. For a planar ring cavity setup, a model of coupled cavity field and atomic density equations describes a wide range of drifting modulation instabilities in the transverse plane. This leads to the formation of rotating self-organized rings of light-atom lattices. Using linear stability analysis and numerical simulations of the coupled atomic and optical dynamics, we demonstrate the presence of macroscopic atomic transport corresponding to the pattern rotation, induced by the structured pump phase profile
Designing a stepped wedge trial: three main designs, carry-over effects and randomisation approaches.
BACKGROUND: There is limited guidance on the design of stepped wedge cluster randomised trials. Current methodological literature focuses mainly on trials with cross-sectional data collection at discrete times, yet many recent stepped wedge trials do not follow this design. In this article, we present a typology to characterise the full range of stepped wedge designs, and offer guidance on several other design aspects. METHODS: We developed a framework to define and report the key characteristics of a stepped wedge trial, including cluster allocation and individual participation. We also considered the relative strengths and weaknesses of trials according to this framework. We classified recently published stepped wedge trials using this framework and identified illustrative case studies. We identified key design choices and developed guidance for each. RESULTS: We identified three main stepped wedge designs: those with a closed cohort, an open cohort, and a continuous recruitment short exposure design. In the first two designs, many individuals experience both control and intervention conditions. In the final design, individuals are recruited in continuous time as they become eligible and experience either the control or intervention condition, but not both, and then provide an outcome measurement at follow-up. While most stepped wedge trials use simple randomisation, stratification and restricted randomisation are often feasible and may be useful. Some recent studies collect outcome information from individuals exposed a long time before or after the rollout period, but this contributes little to the primary analysis. Incomplete designs should be considered when the intervention cannot be implemented quickly. Carry-over effects can arise in stepped wedge trials with closed and open cohorts. CONCLUSIONS: Stepped wedge trial designs should be reported more clearly. Researchers should consider the use of stratified and/or restricted randomisation. Trials should generally not commit resources to collect outcome data from individuals exposed a long time before or after the rollout period. Though substantial carry-over effects are uncommon in stepped wedge trials, researchers should consider their possibility before conducting a trial with closed or open cohorts
- …