Rethinking Suriname-Dutch ties in uncertain times

The current debate around Suriname-Dutch ties predominantly focuses on the harmonious and horizontal verbalized intentions to intensify cooperation in- and outside the bilateral sphere. In this reflective note, we plea for a more critical perspective that questions the underlying reasons for and differences in the level of urgency with which both governments try to cooperate more intensively. It argues that a critical approach is necessary to ensure that both Surinamese and Dutch society do not overlook (un)intended consequences of their unbalanced relation, and neglect existing social (negative) sentiments amongst (Dutch) Surinamese communities about unresolved issues between both countries. Our hope is that the raised questions will deepen debates amongst Dutch and Surinamese citizens, politicians and policymakers, how to further build on the special connection between an old colonizer and its former colony since

What works better for preference elicitation among older people? Cognitive burden of discrete choice experiment and case 2 best-worst scaling in an online setting

To appropriately weight dimensions of quality of life instruments for health economic evaluations, population and patient preferences need to be elicited. Two commonly used elicitation methods for this purpose are discrete choice experiments (DCE) and case 2 best-worst scaling (BWS). These methods differ in terms of their cognitive burden, which is especially relevant when eliciting preferences among older people. Using a randomised experiment with respondents from an online panel, this paper examines the cognitive burden associated with colour-coded and level overlapped DCE, colour-coded BWS, and ‘standard’ BWS choice tasks in a complex health state valuation setting. Our sample included 469 individuals aged 65 and above. Based on both revealed and stated cognitive burden, we found that the DCE tasks were less cognitively burdensome than case 2 BWS. Colour coding case 2 BWS cannot be recommended as its effect on cognitive burden was less clear and the colour coding lead to undesired choice heuristics. Our results have implications for future health state valuations of complex quality of life instruments and at least serve as an example of assessing cognitive burden associated with different types of choice experiments

Preferences of patients, clinicians, and healthy controls for the management of a Bethesda III thyroid nodule

Background: Active surveillance is propagated as an alternative for hemithyroidectomy in the management of Bethesda III thyroid nodules. Methods: A cross-sectional survey questioned respondents on their willingness to accept risks related to active surveillance and hemithyroidectomy. Results: In case of active surveillance, respondents (129 patients, 46 clinicians, and 66 healthy controls) were willing to accept a risk of 10%–15% for thyroid cancer and 15% for needing more extensive surgery in the future. Respondents were willing to accept a risk of 22.5%–30% for hypothyroidism after hemithyroidectomy. Patients and controls were willing to accept a higher risk on permanent voice changes compared with clinicians (10% vs. 3%, p < 0.001). Conclusion: Real-life risks associated which active surveillance and hemithyroidectomy for Bethesda III nodules are equivalent or less than the risks people are willing to accept. Clinicians accepted less risk for permanent voice changes

Choice Modelling in Health: Challenges and Opportunities

This thesis studies several challenges and opportunities of choice modelling in healt

Discrete Choice Experiments in Health Economics: Past, Present and Future

Objectives: Discrete choice experiments (DCEs) are increasingly advocated as a way to quantify preferences for health. However, increasing support does not necessarily result in increasing quality. Although specific reviews have been conducted in certain contexts, there exists no recent description of the general state of the science of health-related DCEs. The aim of this paper was to update prior reviews (1990–2012), to identify all health-related DCEs and to provide a description of trends, current practice and future challenges. Methods: A systematic literature review was conducted to identify health-related empirical DCEs published between 2013 and 2017. The search strategy and data extraction replicated prior reviews to allow the reporting of trends, although additional extraction fields were incorporated. Results: Of the 7877 abstracts generated, 301 studies met the inclusion criteria and underwent data extraction. In general, the total number of DCEs per year continued to increase, with broader areas of application and increased geographic scope. Studies reported using more sophisticated designs (e.g. D-efficient) with associated software (e.g. Ngene). The trend towards using more sophisticated econometric models also continued. However, many studies presented sophisticated methods with insufficient detail. Qualitative research methods continued to be a popular approach for identifying attributes and levels. Conclusions: The use of empirical DCEs in health economics continues to grow. However, inadequate reporting of methodological details inhibits quality assessment. This may reduce decision-makers’ confidence in results and their ability to act on the findings. How and when to integrate health-related DCE outcomes into decision-making remains an important area for future research

A Systematic Review of Discrete Choice Experiments in Oncology Treatments

As the number and type of cancer treatments available rises and patients live with the consequences of their disease and treatments for longer, understanding preferences for cancer care can help inform decisions about optimal treatment development, access, and care provision. Discrete choice experiments (DCEs) are commonly used as a tool to elicit stakeholder preferences; however, their implementation in oncology may be challenging if burdensome trade-offs (e.g. length of life versus quality of life) are involved and/or target populations are small

Comparing Outcomes of a Discrete Choice Experiment and Case 2 Best-Worst Scaling: An Application to Neuromuscular Disease Treatment

BACKGROUND AND OBJECTIVES: Case 2 best-worst scaling (BWS-2) is an increasingly popular method to elicit patient preferences. Because BWS-2 potentially has a lower cognitive burden compared with discrete choice experiments, the aim of this study was to compare treatment preference weights and relative importance scores. METHODS: Patients with neuromuscular diseases completed an online survey at two different moments in time, completing one method per occasion. Patients were randomly assigned to either first a discrete choice experiment or BWS-2. Attributes included: muscle strength, energy endurance, balance, cognition, chance of blurry vision, and chance of liver damage. Multinomial logit was used to calculate overall relative importance scores and latent class logit was used to estimate heterogeneous preference weights and to calculate the relative importance scores of the attributes for each latent class. RESULTS: A total of 140 patients were included for analyses. Overall relative importance scores showed differences in attribute importance rankings between a discrete choice experiment and BWS-2. Latent class analyses indicated three latent classes for both methods, with a specific class in both the discrete choice experiment and BWS-2 in which (avoiding) liver damage was the most important attribute. Ex-post analyses showed that classes differed in sex, age, level of education, and disease status. The discrete choice experiment was easier to understand compared with BWS-2. CONCLUSIONS: This study showed that using a discrete choice experiment and BWS-2 leads to different outcomes, both in preference weights as well as in relative importance scores, which might have been caused by the different framing of risks in BWS-2. However, a latent class analysis revealed similar latent classes between methods. Careful consideration about method selection is required, while keeping the specific decision context in mind and pilot testing the methods