Attribute level overlap (and color coding) can reduce task complexity, improve choice consistency, and decrease the dropout rate in discrete choice experiments

Jonker, Marcel F.; Donkers, Bas; Bekker‐Grob, Esther W. de; Stolk, Elly

doi:10.1002/hec.3846

Cited by 71 publications

(51 citation statements)

References 44 publications

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“…On the other hand, it has been recently published a high sample size DCE study where the participants who completed the DCE also using an online tool. The authors concluded that including overlap when presenting the choices or using different colours for each level could make more accessible for participants to identify the differences between levels and moreover it seems that combining colour editing levels plus overlap reduced the dropout rate [17]. In our study, the dropout rate and the participants who stated the DCE “was easily understood” were very low.…”

Section: Discussionmentioning

confidence: 62%

Using a stated preference discrete choice experiment to assess societal value from the perspective of patients with rare diseases in Italy

López-Bastida¹,

Ramos-Goñi²,

Aranda-Reneo³

et al. 2019

Orphanet J Rare Dis

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Background Decision makers have huge problems when attempting to attribute social value to the improvements achieved by new drugs, especially when considering the use of orphan drugs for rare diseases. We present the results of a pilot study aimed to investigate patient preferences regarding public funding for drugs used to treat rare diseases. Methods An online questionnaire was used as a discrete choice experiment (DCE) survey to explore the preferences of patients with cystic fibrosis and haemophilia in Italy. The questionnaire focused on relevant issues that were defined in a review of the literature. A conditional logistic model showed preferences for specific attributes. Results A total of 54 questionnaires (20% response rate) were completed. The issues that received the greatest attention were improvement in health, treatment cost and value for money. However, disease severity and the availability of other treatments were important social values that could not be ignored. Conclusions The findings presented here provide evidence as to what patients with cystic fibrosis or haemophilia think are the most important considerations on which to base decisions in health technology scenarios, and regarding the priorities for funding.

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Section: Discussionmentioning

confidence: 62%

Using a stated preference discrete choice experiment to assess societal value from the perspective of patients with rare diseases in Italy

López-Bastida¹,

Ramos-Goñi²,

Aranda-Reneo³

et al. 2019

Orphanet J Rare Dis

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“…As shown, respondents were able to choose between two apps and an opt out. Moreover, a small amount of attribute level overlap was used to reduce the cognitive burden of the survey and improve respondents’ attribute attendance [ 15 ]. In addition to the DCE tasks, several background, warm-up, attitudinal, and survey evaluation questions were included in the survey.…”

Section: Methodsmentioning

confidence: 99%

COVID-19 Contact Tracing Apps: Predicted Uptake in the Netherlands Based on a Discrete Choice Experiment

Jonker¹,

Bekker‐Grob²,

Veldwijk³

et al. 2020

JMIR Mhealth Uhealth

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112

129

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Background Smartphone-based contact tracing apps can contribute to reducing COVID-19 transmission rates and thereby support countries emerging from lockdowns as restrictions are gradually eased. Objective The primary objective of our study is to determine the potential uptake of a contact tracing app in the Dutch population, depending on the characteristics of the app. Methods A discrete choice experiment was conducted in a nationally representative sample of 900 Dutch respondents. Simulated maximum likelihood methods were used to estimate population average and individual-level preferences using a mixed logit model specification. Individual-level uptake probabilities were calculated based on the individual-level preference estimates and subsequently aggregated into the sample as well as subgroup-specific contact tracing app adoption rates. Results The predicted app adoption rates ranged from 59.3% to 65.7% for the worst and best possible contact tracing app, respectively. The most realistic contact tracing app had a predicted adoption of 64.1%. The predicted adoption rates strongly varied by age group. For example, the adoption rates of the most realistic app ranged from 45.6% to 79.4% for people in the oldest and youngest age groups (ie, ≥75 years vs 15-34 years), respectively. Educational attainment, the presence of serious underlying health conditions, and the respondents’ stance on COVID-19 infection risks were also correlated with the predicted adoption rates but to a lesser extent. Conclusions A secure and privacy-respecting contact tracing app with the most realistic characteristics can obtain an adoption rate as high as 64% in the Netherlands. This exceeds the target uptake of 60% that has been formulated by the Dutch government. The main challenge will be to increase the uptake among older adults, who are least inclined to install and use a COVID-19 contact tracing app.

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“…These four versions were simultaneously optimized, which improves the robustness and efficiency of the experimental design without resulting in a higher burden for respondents [13]. To keep the task complexity of the DCE manageable for respondents, which reduces the drop-out rate, increases choice consistency, and can avoid problems with attribute non-attendance, a design technique called attribute level overlap was used [14, 15]. Accordingly, in each choice task, seven of the 10 attributes were constrained to be presented at the same level.…”

Section: Methodsmentioning

confidence: 99%

Population preferences for breast cancer screening policies: Discrete choice experiment in Belarus

et al. 2019

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BackgroundReaching an acceptable participation rate in screening programs is challenging. With the objective of supporting the Belarus government to implement mammography screening as a single intervention, we analyse the main determinants of breast cancer screening participation.MethodsWe developed a discrete choice experiment using a mixed research approach, comprising a literature review, in-depth interviews with key informants (n = 23), “think aloud” pilots (n = 10) and quantitative measurement of stated preferences for a representative sample of Belarus women (n = 428, 89% response rate). The choice data were analysed using a latent class logit model with four classes selected based on statistical (consistent Akaike information criterion) and interpretational considerations.ResultsWomen in the sample were representative of all six geographic regions, mainly urban (81%), and high-education (31%) characteristics. Preferences of women in all four classes were primarily influenced by the perceived reliability of the test (sensitivity and screening method) and costs. Travel and waiting time were important components in the decision for 34% of women. Most women in Belarus preferred mammography screening to the existing clinical breast examination (90%). However, if the national screening program is restricted in capacity, this proportion of women will drop to 55%. Women in all four classes preferred combined screening (mammography with clinical breast examination) to single mammography. While this preference was stronger if lower test sensitivity was assumed, 28% of women consistently gave more importance to combined screening than to test sensitivity.ConclusionWomen in Belarus were favourable to mammography screening. Population should be informed that there are no benefits of combined screening compared to single mammography. The results of this study are directly relevant to policy makers and help them targeting the screening population.

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Attribute level overlap (and color coding) can reduce task complexity, improve choice consistency, and decrease the dropout rate in discrete choice experiments

Cited by 71 publications

References 44 publications

Using a stated preference discrete choice experiment to assess societal value from the perspective of patients with rare diseases in Italy

Using a stated preference discrete choice experiment to assess societal value from the perspective of patients with rare diseases in Italy

COVID-19 Contact Tracing Apps: Predicted Uptake in the Netherlands Based on a Discrete Choice Experiment

Population preferences for breast cancer screening policies: Discrete choice experiment in Belarus

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