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). Nearly 100,000 people across the world responded to pandemic-related discrete choice surveys. Within health applications, while the dominant theme, up until June 2020, was lockdown relaxation and tracing measures, the focus shifted abruptly to vaccine preference since then. Geographical origins of the health surveys were not diverse. Nearly 50% of all health surveys were conducted in only three countries, namely US, China and The Netherlands. Health applications exhibited stronger pre-testing and larger sample sizes compared to transport applications. Limited signs of convergent validity were identifiable. Within some applications, issues of temporal instability as well as hypothetical bias attributable to social desirability, protest response or policy consequentiality seemed likely to have affected the findings. Nevertheless, very few of the experiments implemented measures of hypothetical bias mitigation and those were limited to health studies. Our main conclusion is that swift administration of pandemic-related choice experiments has overall resulted in certain degrees of compromise in study quality, but this has been more so the case in relation to transport topics than health topics

Discrete Choice Experiments in Health Care: theory and applications

Health economics is concerned with issues related to scarcity in the allocation of health care. The basic tasks of any economic evaluation are to identify, measure, value, and compare the costs and benefits of alternatives being considered. Traditional means of measuring benefits in the delivery of health care have concentrated on improvements in health outcomes using clinical outcomes and Quality Adjusted Life Years (QALY). The QALY is a measure of the quantity of life gained weighted by the quality of that life. QALYs are extensively used in economic analyses in health care. They claim to capture the health outcome benefits caused by an intervention . However, benefits of a health care intervention or service can be many-sided, e.g. containing non-health outcomes (e.g. amount of information) and process characteristics (e.g. treatment location, route of drug administration, patient experienced burden of testing). For instance, is ‘reduction of dying from cervical cancer’ the only screening characteristic that is considered by women attending a cervical cancer screening programme? Evidence shows that, within the context of cervical cancer screening, women’s preferences for various programmes are also determined by other characteristics than the reduced chance of dying from cervical cancer. Individuals are willing to trade changes in health outcome (change in chance of dying from cervical cance

An attempt to decrease social desirability bias:The effect of cheap talk mitigation on internal and external validity of discrete choice experiments

Discrete choice experiments (DCEs) have been used extensively to elicit preferences. However, the hypothetical nature of choices induces socially desirable behaviour and endangers internal and external validity of DCEs. This study experimentally investigated social desirability bias in DCEs and whether it can be mitigated using the cheap talk mitigation method in the context of food choices. Respondents (N = 1027) were randomly allocated to one of four questionnaire versions: default without manipulation, priming socially desirable behaviour, cheap talk mitigation, or both. The effect on internal validity was assessed by comparing respondent-reported characteristics, DCE results, and prediction accuracy for a holdout task between questionnaire versions. The effect on external validity was assessed by comparing stated and revealed preferences. Social desirability bias, if present, was hardly affected by cheap talk mitigation. Respondent-reported characteristics, DCE results and prediction accuracy for the holdout task and actual food choice did not strongly differ between questionnaire versions. Prediction accuracy for the holdout task was lowest in the default version. Prediction accuracy for actual food choice was slightly better among respondents in the versions that were exposed to cheap talk mitigation. Social desirability bias was hard to detect and mitigate in this study, potentially due to limited social desirability, the effectiveness of the cheap talk mitigation method, and other sources of hypothetical bias. The differences in prediction accuracy indicates that cheap talk mitigation slightly improved external validity at minimum cost to internal validity. Recommendations for future research are provided.</p

Sample Size Requirements for Discrete-Choice Experiments in Healthcare: a Practical Guide

Discrete-choice experiments (DCEs) have become a commonly used instrument in health economics and patient-preference analysis, addressing a wide range of policy questions. An important question when setting up a DCE is the size of the sample needed to answer the research question of interest. Although theory exists as to the calculation of sample size requirements for stated choice dat

Mimicking Real-Life Decision Making in Health: Allowing Respondents Time to Think in a Discrete Choice Experiment

Objective: To empirically test the impact of allowing respondents time to think (TTT) about their choice options on the outcomes of a discrete choice experiments (DCE). Methods: In total, 613 participants of the Swedish CArdioPulmonary bioImage Study (SCAPIS) completed a DCE questionnaire that measured their preferences for receiving secondary findings of a genetic test. A Bayesian D-efficient design with 60 choice tasks divided over 4 questionnaires was used. Each choice task contained 2 scenarios with 4 attributes: type of disease, disease penetrance probability, preventive opportunities, and effectiveness of prevention. Respondents were randomly allocated to the TTT or no TTT (NTTT) sample. Latent class models (LCMs) were estimated to determine attribute-level values and their relative importance. In addition, choice certainty, attribute-level interpretation, choice consistency, and potential uptake rates were compared between samples. Results: In the TTT sample, 92% of the respondents (245 of 267) indicated they used the TTT period to (1) read the information they received (72%) and (2) discuss with their family (24%). In both samples, respondents were very certain about their choices. A 3-class LCM was fitted for both samples. Preference reversals were found for 3 of the 4 attributes in one class in the NTTT sample (34% class-membership probability). Relative importance scores of the attributes differed between the 2 samples, and significant scale effects indicating higher choice consistency in TTT sample were found. Conclusions: Offering respondents TTT influences decision making and preferences. Developers of future DCEs regarding complex health-related decisions are advised to consider this approach to enhance the validity of the elicited preferences

Construct Validity, Reliability, and Responsiveness of the 10-Item Well-being Instrument for Use in Economic Evaluation Studies

Objectives: Economic evaluations of interventions in health and social care require outcome measures that capture their full benefits, including those beyond health. This study aimed to assess construct validity, test-retest reliability, and responsiveness of the newly developed 10-item Well-being instrument (WiX). Methods: Data were gathered via an online survey in a representative sample of the adult general population in The Netherlands (N = 1045). Construct validity was assessed by inspecting convergent, structural, and discriminant validity, following the COnsensus-based Standards for the selection of health status Measurement INstruments methodology. Regression analyses of the WiX and its items on other validated measures of well-being were performed to assess the convergent validity of the instrument and the relevance of its items. Dimensionality of the WiX was assessed using exploratory factor analysis. To assess discriminant validity, several hypotheses in terms of well-being differences were assessed. Finally, a second survey was sent out 2 weeks after the initial survey (n = 563; 53.9% response rate) to assess the test-retest reliability and responsiveness of the WiX. Results: The WiX showed to be correlated with alternative well-being measures as expected and able to sufficiently differentiate between relevant subgroups in the population. Moreover, the dimensionality analysis indicated that the WiX captures a broad array of elements relevant to well-being, including physical and mental health. The test-retest reliability was good, with an intraclass correlation coefficient of 0.82. Conclusions: The results regarding the WiX are favorable and indicate that this new instrument may be a promising alternative for existing measures of well-being for evaluating interventions in health and social care.</p

Can healthcare choice be predicted using stated preference data?

Lack of evidence about the external validity of Discrete Choice Experiments (DCEs)-sourced preferences inhibits greater use of DCEs in healthcare decision-making. This study examines the external validity of such preferences, unravels its determinants, and provides evidence of whether healthcare choice is predictable. We focused on influenza vaccination and used a six-step approach: i) literature study, ii) expert interviews, iii) focus groups, iv) survey including a DCE, v) field data, and vi) in-depth interviews with respondents who showed discordance between stated choices and actual healthcare utilization. Respondents without missing values in the survey and the actual healthcare utilization (377/499 = 76%) were included in the analyses. Random-utility-maximization and random-regret-minimization models were used to analyze the DCE data, whereas the in-depth interviews combined five scientific theories to explain discordance.

Patients' Preferences for Surgical Management of Esophageal Cancer: A Discrete Choice Experiment

Background: Obtaining insight into patients' preferences is important to optimize cancer care. We investigated patients' preferences for surgical management of esophageal cancer. Methods: We conducted a discrete choice experiment among adult patients who had undergone esophagectomy for adenocarcinoma or squamous cell cancer of the esophagus. Patients' preferences were quantified with regression analysis using scenarios based on five aspects: risk of in-hospital mortality, risk of persistent symptoms, chance of 5-year survival, risk of surgical and non-surgical complications, and hospital volume of esophageal cancer surgery. Results: The response rate was 68 % (104/142). All aspects proved to influence patients' preferences (p < 0.05). Persisting gastrointestinal symptoms and 5-year survival were the most important attributes, but preferences varied between patients. On average, patients were willing to trade-off 9.5 % (CI 2.4-16.6 %) 5-year survival chance to obtain a surgical treatment with 30 % lower risk of gastrointestinal symptoms, or 8.1 % (CI 4.0-12.2 %) 5-year survival chance for being treated in a high instead of a low-volume hospital. Conclusions: Patients are willing to trade-off some 5-year survival chance to achieve an improvement in early outcomes. Given the preference heterogeneity among participants, the present study underlines the importance of a patient-tailored approach when discussing prognosis and treatment