Test-Retest Reliability of Discrete Choice Experiment for Valuations of QLU-C10D Health States

Gamper, Eva‐Maria; Holzner, Bernhard; King, Madeleine; Norman, Richard; Viney, Rosalie; Nerich, Virginie; Kemmler, Georg

doi:10.1016/j.jval.2017.11.012

Cited by 26 publications

(15 citation statements)

References 33 publications

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“…The wording of the DCE tasks and different layouts have been pre-tested in general population respondents which showed that although perceived difficult the tasks were considered manageable [14]. Utility weights resulting from the DCE showed to be unbiased by the ordering of attributes in the DCE [15] and stable within respondents over time [16].…”

Section: Methodsmentioning

confidence: 99%

EORTC QLU-C10D value sets for Austria, Italy, and Poland

et al. 2020

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Objective To develop Austrian, Italian, and Polish general population value sets for the EORTC QLU-C10D, a cancer-specific utility instrument based on the EORTC QLQ-C30, and to descriptively compare their index scores for distinct health states. Methods The QLU-C10D descriptive system comprises 10 health attributes and each can take on 4 levels. A standardised and pre-tested methodology has been applied for valuations including a web-based discrete choice experiment (DCE). It was administered in 1000 general population respondents per country recruited via online panels, aiming at representativeness for core socio-demographic variables. Results In all three countries, the attributes with the largest impact on utility were physical functioning, pain, and role functioning. Cancer-specific dimensions with the largest impact were nausea and fatigue or bowel problems. Utility values of the worst health state (i.e. severe problems on all 10 dimension) were-0.111 (Austria), 0.025 (Italy), and 0.048 (Poland). Country-specific utilities differed for a selection of health states across the continuum. Austrian utilities were systematically lower for moderately and severely impaired health states. Conclusion QLU-C10D cancer-specific utilities can now be calculated in three more countries. Differences between countries indicate that careful consideration is required when using non-country-specific value sets in economic evaluations.

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Section: Methodsmentioning

confidence: 99%

EORTC QLU-C10D value sets for Austria, Italy, and Poland

et al. 2020

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“…Second, participants' preferences about SARS-CoV-2 testing may change over time. Research on other topics has demonstrated that choices stated in a DCE are generally consistent, with good testretest reliability; 16,17 however, knowledge about SARS-CoV-2 and COVID-19 is rapidly evolving and is widely disseminated in mainstream media, 18 which could plausibly impact preferences.…”

Section: Discussionmentioning

confidence: 99%

“…Second, participants’ preferences about SARS-CoV-2 testing may change over time. Research on other topics has demonstrated that choices stated in a DCE are generally consistent, with good test-retest reliability; 16,17 however, knowledge about SARS-CoV-2 and COVID-19 is rapidly evolving and is widely disseminated in mainstream media, 18 which could plausibly impact preferences. For example, reports of re-infection and the potential waning of antibodies, such as the first such report in the US in October 2020, 19 approximately one month after the completion of our DCE, might influence preferences about antibody testing, as might the availability of highly efficacious vaccines in December 2020.…”

Section: Discussionmentioning

confidence: 99%

Patterns of SARS-CoV-2 testing preferences in a national cohort in the United States

Romo

Zimba

Kulkarni

et al. 2020

Preprint

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In order to understand preferences about SARS-CoV-2 testing, we conducted a discrete choice experiment among 4793 participants in the Communities, Households, and SARS-CoV-2 Epidemiology (CHASING COVID) Cohort Study from July 30-September 8, 2020. We used latent class analysis to identify distinct patterns of preferences related to testing and conducted a simulation to predict testing uptake if additional testing scenarios were offered. Five distinct patterns of SARS-CoV-2 testing emerged. “Comprehensive testers” (18.9%) ranked specimen type as most important and favored less invasive specimen types, with saliva most preferred, and also ranked venue and result turnaround time as highly important, with preferences for home testing and fast result turnaround time. “Fast track testers” (26.0%) ranked result turnaround time as most important and favored immediate and same day turnaround time. “Dual testers” (18.5%) ranked test type as most important and preferred both antibody and viral tests. “Non-invasive dual testers” (33.0%) ranked specimen type and test type as similarly most important, preferring cheek swab specimen type and both antibody and viral tests. “Home testers” (3.6%) ranked venue as most important and favored home-based testing. By offering less invasive (saliva specimen type), dual testing (both viral and antibody tests), and at home testing scenarios in addition to standard testing scenarios, simulation models predicted that testing uptake would increase from 81.7% to 98.1%. We identified substantial differences in preferences for SARS-CoV-2 testing and found that offering additional testing options, which consider this heterogeneity, would likely increase testing uptake.SIGNIFICANCEDuring the COVID-19 pandemic, diagnostic testing has allowed for early detection of cases and implementation of measures to reduce community transmission of SARS-CoV-2 infection. Understanding individuals’ preferences about testing and the service models that deliver tests are relevant in efforts to increase and sustain uptake of SARS-CoV-2 testing, which, despite vaccine availability, will be required for the foreseeable future. We identified substantial differences in preferences for SARS-CoV-2 testing in a discrete choice experiment among a large national cohort of adults in the US. Offering additional testing options that account for or anticipate this heterogeneity in preferences (e.g., both viral and antibody tests, at home testing), would likely increase testing uptake.ClassificationBiological Sciences (major); Psychological and Cognitive Sciences (minor)

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“…For example, when researchers conduct test-retest exercises of tasks, such as TTO, SG or choice experiments, they usually find some element of variability in the responses (Feeny et al, 2004;Gamper et al, 2018;van Agt, Essink-Bot, Krabbe, & Bonsel, 1994). In a recent study, Gamper et al (2018) found that only 25% of subjects were perfectly consistent (i.e., repeated exactly the same choice between two options) in a choice experiment. The complexity of the task has two implications for subjects' responses to TTO questions.…”

Section: Contrast Effects and Preference Imprecisionmentioning

confidence: 99%

“…The second implication is that there will be an element of variability in the evaluation of health states. Some people may change their responses to the same question from one moment to the next (Feeny et al, 2004;Gamper et al, 2018;van Agt et al, 1994). This leads to the next decision model.…”

Section: Contrast Effects and Preference Imprecisionmentioning

confidence: 99%

Sequence effects in time trade‐off valuation of hypothetical health states

Prades

McHugh

Donaldson³

et al. 2019

Health Economics

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Choice‐based stated preference methods, such as time trade‐offs (TTOs), are used to establish health state utilities informing healthcare allocation. However, little is known about the presence of (position‐dependent and precedent‐dependent) sequence effects in the valuation of health states, despite techniques requiring respondents to evaluate several health states in a sequence. This paper is the first to explicitly test for the presence of sequence effects in the health domain using a new explanation based on contrast effects and preference imprecision; the implication being that randomisation cannot avoid sequence effects. Six TTO questions were designed using the EQ‐5D‐3L descriptive system. These were grouped into two blocks of three and within each block four sequences were used. In an online survey, 1,197 Spanish respondents answered one grouping of three TTO questions. Results indicate that sequence effects can affect preferences as utilities of health states are biased downwards if preceded by a better health state and biased upwards if preceded by a worse health state. This study informs our understanding of how context effects interact with preference elicitation methods, which is essential for interpreting survey results used to inform policy.

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Test-Retest Reliability of Discrete Choice Experiment for Valuations of QLU-C10D Health States

Cited by 26 publications

References 33 publications

EORTC QLU-C10D value sets for Austria, Italy, and Poland

EORTC QLU-C10D value sets for Austria, Italy, and Poland

Patterns of SARS-CoV-2 testing preferences in a national cohort in the United States

Sequence effects in time trade‐off valuation of hypothetical health states

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