The Effect of Including an Opt-Out Option in Discrete Choice Experiments

PLOS ONE, Dec 2019

Objective to determine to what extent the inclusion of an opt-out option in a DCE may have an effect on choice behaviour and therefore might influence the attribute level estimates, the relative importance of the attributes and calculated trade-offs. Methods 781 Dutch Type 2 Diabetes Mellitus patients completed a questionnaire containing nine choice tasks with an opt-out option and nice forced choice tasks. Mixed-logit models were used to estimate the relative importance of the five lifestyle program related attributes that were included. Willingness to pay (WTP) values were calculated and it was tested whether results differed between respondents who answered the choice tasks with an opt-out option in the first or second part of the questionnaire. Results 21.4% of the respondents always opted out. Respondents who were given the opt-out option in the first part of the questionnaire as well as lower educated respondents significantly more often opted out. For both the forced and unforced choice model, different attributes showed significant estimates, the relative importance of the attributes was equal. However, due to differences in relative importance weights, the WTP values for the PA schedule differed significantly between both datasets. Conclusions Results show differences in opting out based on the location of the opt-out option and respondents' educational level; this resulted in small differences between the forced and unforced choice model. Since respondents seem to learn from answering forced choice tasks, a dual response design might result in higher data quality compared to offering a direct opt-out option. Future research should empirically explore how choice sets should be presented to make them as easy and less complex as possible in order to reduce the proportion of respondents that opts-out due to choice task complexity. Moreover, future research should debrief respondents to examine the reasons for choosing the opt-out alternative.

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The Effect of Including an Opt-Out Option in Discrete Choice Experiments

de Wit GA (2014) The Effect of Including an Opt-Out Option in Discrete Choice Experiments. PLoS ONE 9(11): e111805. doi:10.1371/journal.pone.0111805 The Effect of Including an Opt-Out Option in Discrete Choice Experiments Jorien Veldwijk 0 Mattijs S. Lambooij 0 Esther W. de Bekker-Grob 0 Henrie tte A. Smit 0 G. Ardine de Wit 0 D. William Cameron, University of Ottawa, Canada 0 1 Centre for Nutrition, Prevention and Health Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands, 2 Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht , Utrecht , The Netherlands , 3 Department of Public Health, Erasmus MC, University Medical Center , Rotterdam , The Netherlands Objective: to determine to what extent the inclusion of an opt-out option in a DCE may have an effect on choice behaviour and therefore might influence the attribute level estimates, the relative importance of the attributes and calculated tradeoffs. Methods: 781 Dutch Type 2 Diabetes Mellitus patients completed a questionnaire containing nine choice tasks with an optout option and nice forced choice tasks. Mixed-logit models were used to estimate the relative importance of the five lifestyle program related attributes that were included. Willingness to pay (WTP) values were calculated and it was tested whether results differed between respondents who answered the choice tasks with an opt-out option in the first or second part of the questionnaire. Results: 21.4% of the respondents always opted out. Respondents who were given the opt-out option in the first part of the questionnaire as well as lower educated respondents significantly more often opted out. For both the forced and unforced choice model, different attributes showed significant estimates, the relative importance of the attributes was equal. However, due to differences in relative importance weights, the WTP values for the PA schedule differed significantly between both datasets. Conclusions: Results show differences in opting out based on the location of the opt-out option and respondents' educational level; this resulted in small differences between the forced and unforced choice model. Since respondents seem to learn from answering forced choice tasks, a dual response design might result in higher data quality compared to offering a direct opt-out option. Future research should empirically explore how choice sets should be presented to make them as easy and less complex as possible in order to reduce the proportion of respondents that opts-out due to choice task complexity. Moreover, future research should debrief respondents to examine the reasons for choosing the opt-out alternative. - Funding: This study was funded by the Strategic Research RIVM (SOR) of the National Institute for Public Health and the Environment (to MSL and GAW). The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Competing Interests: The authors have declared that no competing interests exist. There seems to be consensus regarding the inclusion of an optout option in Discrete Choice Experiments (DCEs) that aim to determine the potential participation in an elective program as such an option is more in accordance with the respondents choice options in real life [14]. Moreover, when estimating the potential number of participants in any program, insight into the percentage of the target population that does not wish to participate in such a program is necessary. However, if individual preferences are measured to determine which components define the most preferred program or treatment, the inclusion of an opt-out option might not be a necessity but rather a threat to efficiency. Until now, the choice to include an opt-out option is determined by the objective of the DCE in the first place. Nevertheless, very little empirical evidence exists on the issue whether, and to what extent the inclusion of opt-out options in DCEs effect choice behavior of respondents. Which may therefore influence the precision of the estimates of attributes, the relative importance of the attributes, trade-offs (e.g., willingness to pay) calculated based on these estimates and thereby the conclusions that will be drawn from a DCE. Most DCEs in health economics are rooted in the Random Utility Theory (RUT) [3,57]. This theory assumes that respondents choose rationally and will select the scenario that generates the highest personal utility, that is, respondents will only select the opt-out option if none of the presented scenarios in that specific choice task is more attractive than the opt-out option [5,8]. Additional research shows that from this perspective, forcing respondents to make a choice induces bias, as they would not always make that same choice in real life [3,9,10]. In such a forced-choice situation, people who would rather choose to optout, tend to randomly select either scena (...truncated)


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Jorien Veldwijk, Mattijs S. Lambooij, Esther W. de Bekker-Grob, Henriëtte A. Smit, G. Ardine de Wit. The Effect of Including an Opt-Out Option in Discrete Choice Experiments, PLOS ONE, 2014, 11, DOI: 10.1371/journal.pone.0111805