BackgroundPreventive measures are essential to limit the spread of new viruses; their uptake is key to their success. However, the vaccination uptake in pandemic outbreaks is often low. We aim to elicit how disease and vaccination characteristics determine preferences of the general public for new pandemic vaccinations.MethodsIn an internet-based discrete choice experiment (DCE) a representative sample of 536 participants (49% participation rate) from the Dutch population was asked for their preference for vaccination programs in hypothetical communicable disease outbreaks. We used scenarios based on two disease characteristics (susceptibility to and severity of the disease) and five vaccination program characteristics (effectiveness, safety, advice regarding vaccination, media attention, and out-of-pocket costs). The DCE design was based on a literature review, expert interviews and focus group discussions. A panel latent class logit model was used to estimate which trade-offs individuals were willing to make.ResultsAll above mentioned characteristics proved to influence respondents’ preferences for vaccination. Preference heterogeneity was substantial. Females who stated that they were never in favor of vaccination made different trade-offs than males who stated that they were (possibly) willing to get vaccinated. As expected, respondents preferred and were willing to pay more for more effective vaccines, especially if the outbreak was more serious (€6–€39 for a 10% more effective vaccine). Changes in effectiveness, out-of-pocket costs and in the body that advises the vaccine all substantially influenced the predicted uptake.ConclusionsWe conclude that various disease and vaccination program characteristics influence respondents’ preferences for pandemic vaccination programs. Agencies responsible for preventive measures during pandemics can use the knowledge that out-of-pocket costs and the way advice is given affect vaccination uptake to improve their plans for future pandemic outbreaks. The preference heterogeneity shows that information regarding vaccination needs to be targeted differently depending on gender and willingness to get vaccinated.

No abstract

Objectiveto 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.Methods781 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.Results21.4% 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.ConclusionsResults 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.

ObjectiveThe objective of this study was to assess the predictive value of a discrete choice experiment (DCE) in public health by comparing stated preferences to actual behavior.Methods780 Type 2 diabetes mellitus (T2DM) patients received a questionnaire, containing a DCE with five attributes related to T2DM patients’ willingness to participate in a combined lifestyle intervention. Panel mixed-multinomial-logit models were used to estimate the stated preferences based on 206 completed DCE questionnaires. Actual participation status was retrieved for 54 respondents based on patients’ medical records and a second questionnaire. Predicted and actual behavior data were compared at population level and at individual level.ResultsBased on the estimated utility function, 81.8 % of all answers that individual respondents provided on the choice tasks were predicted correctly. The actual participation rate at the aggregated population level was minimally underestimated (70.1 vs. 75.9 %). Of all individual choices, 74.1 % were predicted correctly with a positive predictive value of 0.80 and a negative predictive value of 0.44.ConclusionStated preferences derived from a DCE can adequately predict actual behavior in a public health setting.

BackgroundDiscrete Choice Experiments (DCEs) are increasingly used in studies in healthcare research but there is still little empirical evidence for the predictive value of these hypothetical situations in similar real life circumstances. The aim of this paper is to compare the stated preferences in a DCE and the accompanying questionnaire with the revealed preferences of young parents who have to decide whether to vaccinate their new born child against hepatitis B.MethodsA DCE asking parents to decide in which scenario they would be more inclined to vaccinate their child against hepatitis B. The stated preference was estimated by comparing the per respondent utility of the most realistic scenario in which parents could choose to vaccinate their child against hepatitis B, with the utility of the opt-out, based on the mixed logit model from the DCE. This stated preference was compared with the actual behaviour of the parents concerning the vaccination of their new born child.ResultsIn 80% of the respondents the stated and revealed preferences corresponded. The positive predictive value is 85% but the negative predictive value is 26%.ConclusionsThe predictive value of the DCE in this study is satisfactory for predicting the positive choice but not for predicting the negative choice. However, the behaviour in this study is exceptional in the sense that most people chose to vaccinate. Future studies should focus on behaviours with a larger variance in the population.Electronic supplementary materialThe online version of this article (doi:10.1186/s12874-015-0010-5) contains supplementary material, which is available to authorized users.

Risk framing affects how respondents value the presented risk. Positive risk framing led to increased dominant decision-making behavior, whereas negative risk framing led to risk-seeking behavior. Attribute framing should have a prominent part in the expert and focus group interviews, and different types of framing should be used in the pilot version of DCEs as well as in actual DCEs to estimate the magnitude of the effect of choosing different types of framing.

We find no indication that online surveys yield inferior results compared with paper-based surveys, whereas the price per respondent is lower for online surveys. Researchers might want to include fewer choice sets per respondent when collecting DCE data online. Because our findings are based on a nonrandomized DCE that covers one health domain only, research in other domains is needed to support our findings.

Future research on the use of either words or graphics is recommended in order to establish guidelines on how to develop a valid presentation method for attribute levels in the choice tasks of a DCE.