Leeds University

Current Research


Decisions is a large five year research programme funded by the European Research Council which involves only members of CMC. The project looks at modelling long and short term decisions in a changing world. It aims to develop a new framework which realigns modelled behaviour with real world behaviour, jointly representing the choice of multiple options or products and the quantity of consumption for each of these. In contrast with existing work, these choices will be placed within a wider framework, incorporating links between long term decisions and day to day choices, accounting for the growing importance of virtual social networks and the role of joint decisions. The work will ensure consistency with economic theory and in particular deal with the formation and role of budgets and constraints. The research promises a step change in model flexibility and realism with impacts across a number of academic disciplines as well as real world benefits to society as a whole.

CMC members involved: Stephane Hess, Charisma Choudhury, Richard Batley

NG-DBM (Next Generation Driving Behaviour Models)

NG-DBM (Next Generation Driving Behaviour Models) is a four year research project funded by the European Union involving only members of CMC. The goal of this project is to develop dynamic driving behaviour models that explicitly account for the effects of driver characteristics in his/her decisions alongside the effects of path-plan, network topography and traffic conditions. In a novel approach, the project proposes to calibrate the driving behaviour models combining experimental data collected from the University of Leeds Driving Simulator (UoLDS) and actual traffic data collected using video recordings

CMC members involved: Charisma Choudhury & Stephane Hess

IMPACCT - Improving the Management of Pain from Advanced Cancer in the CommuniTy

IMPACCT - Improving the Management of Pain from Advanced Cancer in the CommuniTy. For community based cancer patients, research shows that pain remains common, severe and under-treated. Barriers to good pain control include inadequate support and patient education, poor assessment and communication, and lack of access to an adequate prescription and timely analgesia. IMPACCT will design and test a new model of pain management in the community. A stated preference survey is being conducted with cancer patients to identify which aspects of community pain management are most important to them. Attributes under consideration include: waiting time for advice and treatment, level of pain relief, level of side effect control, communication and out-of-pocket expenses. Information from the survey will inform the design of the new care pathway.

CMC members involved: David Meads

CRIMSON: Considering Risk and Benefits in Multiple Sclerosis Treatment Selection

CRIMSON: Considering Risk and Benefits in Multiple Sclerosis Treatment Selection

Multiple Sclerosis (MS) is an incurable disease, but there are a range of disease modifying treatments (DMTs) which can reduce the number and severity of relapses, accumulation of brain lesions and may slow disability progression. However the DMTs have side effects ranging from minor (e.g. a rash) to major e.g. rare viral infections, so decisions about taking DMTs are best made by carefully considering and weighing factors including individual lifestyle, disease course, known side effects, and the potential risks and benefits of the different treatments.

The aim of CRIMSON is to improve the understanding of whether (and how) people with relapsing remitting multiple sclerosis trade-off likely risk/harms against benefits in making treatment choices, in order to develop ways of supporting this decision-making process.

We will conduct a large scale discrete choice experiment using access to patients in the UKMS register. The register will allow us to readily identify those patients relatively recently diagnosed as well as those with longer duration and severity to target specific groups of interest. By examining the choices people with MS are prepared to make using a survey method with many hundreds of participants we can start to quantify and rank patient preferences across a range of characteristics associated with treatments.

Of particular interest is heterogeneity across patient groups, and the statistical analysis will use methods such as mixed-logit regressions that allow for investigation of such heterogeneity.

CMC members involved: David Meads

I-ASC- Identifying Appropriate Symbol Communication aids for children who are non-speaking: enhancing clinical decision making

I-ASC - Identifying appropriate symbol communication aids for children who are non-speaking: enhancing clinical decision making

Some children with conditions such as cerebral palsy, dyspraxia or severe autism, struggle to develop intelligible speech. High-tech augmentative and alternative communication (AAC) can enable such children to supplement their communication by accessing pictures, symbols and/or text, often accompanied by voice output. The choice of which AAC device to prescribe can have long lasting consequences for children and their development but little is known about the decision making of clinicians in this context.

We aim to study the priorities of clinicians and the trade-offs they make by conducting two stated preference surveys. The first is a best-worst scaling study which will identify the most important factors relating both to children and to AAC devices. The results of this study will then feed into a discrete choice experiment which will examine in more detail the trade-offs clinicians make and the interactions between child and device related factors.

These experiments and other qualitative findings will inform the development of a clinical decision making heuristic.

CMC members involved: David Meads