Comparison of a full and partial choice set design in a labeled discrete choice experiment.

Labeled discrete choice experiments (DCEs) commonly present all alternatives using a full choice set design (FCSD), which could impose a high cognitive burden on respondents. In the setting of employment preferences, this study explored if a partial choice set design (PCSD) reduced cognitive burden whilst maintaining convergent validity compared with a FCSD. Respondents' preferences between the two designs were investigated.

Applications of discrete choice experiments in COVID-19 research: Disparity in survey qualities between health and transport fields.

Published choice experiments linked to various aspects of the COVID-19 pandemic are analysed in a rapid review. The aim is to (i) document the diversity of topics as well as their temporal and geographical patterns of emergence, (ii) compare various elements of design quality across different sectors of applied economics, and (iii) identify potential signs of convergent validity across findings of comparable experiments. Of the N = 43 published choice experiments during the first two years of the pandemic, the majority identifies with health applications (n = 30), followed by transport-related applications (n = 10).

Eliciting preferences for continuing medication among adult patients and parents of children with attention-deficit hyperactivity disorder.

Background: Adherence to medication for attention-deficit hyperactivity disorder (ADHD) is less than optimal. Previous studies have primarily focused on qualitative assessment of factors that influence medication adherence.

Objective: This study aimed to quantify the factors that influence patient and parent preferences for continuing ADHD medication.

Structural anatomy and temporal trends of road accident research: Full-scope analyses of the field.

Introduction: Scholarly research on road accidents over the past 50 years has generated substantial literature. We propose a robust search strategy to retrieve and analyze this literature.

Method: Analyses was focused on estimating the size of this literature and examining its intellectual anatomy and temporal trends using bibliometric indicators of its articles.

Using discrete choice experiment to investigate patients' and parents' preferences for initiating ADHD medication.

Background: The decision to initiate medication is complex and is influenced by a variety of factors. There is limited information on the relative importance of factors that influence the initiation of ADHD medication.

Aims: To investigate the factors, and their relative importance, that influence the decision to initiate medication in adults, and parents of children, with ADHD.

Applications of brain imaging methods in driving behaviour research.

Applications of neuroimaging methods have substantially contributed to the scientific understanding of human factors during driving by providing a deeper insight into the neuro-cognitive aspects of driver brain. This has been achieved by conducting simulated (and occasionally, field) driving experiments while collecting driver brain signals of various types. Here, this sector of studies is comprehensively reviewed at both macro and micro scales.

Covid-19 pandemic and the unprecedented mobilisation of scholarly efforts prompted by a health crisis: Scientometric comparisons across SARS, MERS and 2019-nCoV literature.

During the current century, each major coronavirus outbreak has triggered a quick and immediate surge of academic publications on its respective topic. The spike in research publications following the 2019 Novel Coronavirus (Covid-19) outbreak, however, has been like no other. The global crisis caused by the Covid-19 pandemic has mobilised scientific efforts at an unprecedented scale.

The scientific literature on Coronaviruses, COVID-19 and its associated safety-related research dimensions: A scientometric analysis and scoping review.

The COVID-19 global pandemic has generated an abundance of research quickly following the outbreak. Within only a few months, more than a thousand studies on this topic have already appeared in the scientific literature. In this short review, we analyse the bibliometric aspects of these studies on a macro level, as well as those addressing Coronaviruses in general.

On the Optimization of Bayesian D-Efficient Discrete Choice Experiment Designs for the Estimation of QALY Tariffs That Are Corrected for Nonlinear Time Preferences.

Objectives: This article explains how to optimize Bayesian D-efficient discrete choice experiment (DCE) designs for the estimation of quality-adjusted life year (QALY) tariffs that are unconfounded by respondents' time preferences.

Methods: The calculation of Bayesian D-errors is explained for DCE designs that allow for the disentanglement of respondents' time and health-state preferences. Time preferences are modelled via an exponential, hyperbolic, or power discount function and the performance of the proposed DCE designs is compared with that of several conventional DCE designs that do not take nonlinear time preferences into account.

Are Healthcare Choices Predictable? The Impact of Discrete Choice Experiment Designs and Models.

Background: Lack of evidence about the external validity of discrete choice experiments (DCEs) is one of the barriers that inhibit greater use of DCEs in healthcare decision making.

Objectives: To determine whether the number of alternatives in a DCE choice task should reflect the actual decision context, and how complex the choice model needs to be to be able to predict real-world healthcare choices.

Methods: Six DCEs were used, which varied in (1) medical condition (involving choices for influenza vaccination or colorectal cancer screening) and (2) the number of alternatives per choice task.

Individual preferences on the balancing of good and harm of cardiovascular disease screening.

Objective: Transition towards value-based healthcare requires insight into what makes value to the individual. The aim was to elicit individual preferences for cardiovascular disease screening with respect to the difficult balancing of good and harm as well as mode of delivery.

Methods: A discrete choice experiment was conducted as a cross-sectional survey among 1231 male screening participants at three Danish hospitals between June and December 2017.

Network growth models: A behavioural basis for attachment proportional to fitness.

Several growth models have been proposed in the literature for scale-free complex networks, with a range of fitness-based attachment models gaining prominence recently. However, the processes by which such fitness-based attachment behaviour can arise are less well understood, making it difficult to compare the relative merits of such models. This paper analyses an evolutionary mechanism that would give rise to a fitness-based attachment process.

Network science approach to modelling the topology and robustness of supply chain networks: a review and perspective.

Due to the increasingly complex and interconnected nature of global supply chain networks (SCNs), a recent strand of research has applied network science methods to model SCN growth and subsequently analyse various topological features, such as robustness. This paper provides: (1) a comprehensive review of the methodologies adopted in literature for modelling the topology and robustness of SCNs; (2) a summary of topological features of the real world SCNs, as reported in various data driven studies; and (3) a discussion on the limitations of existing network growth models to realistically represent the observed topological characteristics of SCNs. Finally, a novel perspective is proposed to mimic the SCN topologies reported in empirical studies, through fitness based generative network models.

Public preferences for vaccination programmes during pandemics caused by pathogens transmitted through respiratory droplets - a discrete choice experiment in four European countries, 2013.

This study aims to quantify and compare preferences of citizens from different European countries for vaccination programme characteristics during pandemics, caused by pathogens which are transmitted through respiratory droplets. Internet panel members, nationally representative based on age, sex, educational level and region, of four European Union Member States (Netherlands, Poland, Spain, and Sweden, n = 2,068) completed an online discrete choice experiment. These countries, from different geographical areas of Europe, were chosen because of the availability of high-quality Internet panels and because of the cooperation between members of the project entitled Effective Communication in Outbreak Management: development of an evidence-based tool for Europe (ECOM).

Protective Behaviour of Citizens to Transport Accidents Involving Hazardous Materials: A Discrete Choice Experiment Applied to Populated Areas nearby Waterways.

Background: To improve the information for and preparation of citizens at risk to hazardous material transport accidents, a first important step is to determine how different characteristics of hazardous material transport accidents will influence citizens' protective behaviour. However, quantitative studies investigating citizens' protective behaviour in case of hazardous material transport accidents are scarce.

Methods: A discrete choice experiment was conducted among subjects (19-64 years) living in the direct vicinity of a large waterway.

Driver behaviour profiles for road safety analysis.

Driver behaviour is a contributing factor in over 90 percent of road crashes. As a consequence, there is significant benefit in identifying drivers who engage in unsafe driving practices. Driver behaviour profiles (DBPs) are introduced here as an approach for evaluating driver behaviour as a function of the risk of a casualty crash.

Evaluating changes in driver behaviour: a risk profiling approach.

New road safety strategies continue to be devised by researchers and policy makers with pay-as-you-drive (PAYD) schemes gaining increasing attention. However, empirically measuring the effectiveness of these strategies is challenging due to the influence of the road environment and other factors external to the driver. The analysis presented here applies Temporal and Spatial Identifiers to control for the road environment and Driver Behaviour Profiles to provide a common measure of driving behaviour based on the risk of a casualty crash for assessing the effectiveness of a PAYD scheme on reducing driving risks.

Acceptance of vaccinations in pandemic outbreaks: a discrete choice experiment.

Background: Preventive measures are essential to limit the spread of new viruses; their uptake is key to their success. However, the vaccination uptake in pandemic outbreaks is often low. We aim to elicit how disease and vaccination characteristics determine preferences of the general public for new pandemic vaccinations.

A closer look at decision and analyst error by including nonlinearities in discrete choice models: implications on willingness-to-pay estimates derived from discrete choice data in healthcare.

Background: Most researchers in health economics cite random utility theory (RUT) when analysing discrete choice experiments (DCEs). Under RUT, the error term is associated with the analyst's inability to properly capture the true choice processes of the respondent as well as the inconsistency or mistakes arising from the respondent themselves. Under such assumptions, it stands to reason that analysts should explore more complex nonlinear indirect utility functions, than currently used in healthcare, to strive for better estimates of preferences in healthcare.