Abstract
Stated preference (SP) survey responses may not predict actual behavior, leading to hypothetical bias. We developed an approach that harnesses large-scale routine data to help SP surveys provide more accurate estimates of revealed preferences (RPs), within a study which elicited preferences for alternative changes to the blood service in England. The SP survey responses were used to predict the mean number of annual whole blood donations. Ex ante, the iterative survey design estimated hypothetical bias by contrasting pilot SP survey responses (N=1254), with individually linked data on RPs, to inform the main SP survey design (N=25,187). Ex post, the analysis recognized mediation of the relationship between SP and RP when blood donation is deferred. The pilot survey reported that donors' intended donation frequency of 3.2 (men) and 2.6 (women) times per year, exceeded their actual frequency by 41% and 30% respectively. Choice scenario attributes for the main SP survey were then modified, and over-prediction subsequently decreased to 34% for men and 16% for women. The mediating effect of deferrals explained 29% (men) and 86% (women) of the residual discrepancy between SP and RP. Future studies can use this approach to reduce hypothetical bias, and provide more accurate predictions for decision-making.
Highlights
Stated preference (SP) survey responses may not predict actual behavior, leading to hypothetical bias
Stated preference (SP) methods are widely used in health economics, for example to estimate the relative value of alternative service changes (DeBekker‐Grob, et al, 2012), and to elicit the willingness to pay for health gains
This paper develops an approach for reducing hypothetical bias when predicting revealed preferences (RPs) from SP surveys
Summary
Stated preference (SP) methods are widely used in health economics, for example to estimate the relative value of alternative service changes (DeBekker‐Grob, et al, 2012), and to elicit the willingness to pay for health gains. The HEMO (Health Economics MOdeling of blood donation) study recognized the importance of providing timely evidence on the relative preference for alternative service changes including those that had not been implemented even in the research setting, by undertaking a SP survey to estimate the effect of changes to service attributes on the predicted frequency of donation (Grieve et al, 2018). This SP survey was designed to estimate the effect of alternative future changes to the blood service on the frequency with which donors are willing to donate whole blood. The first section asked donors to think about a donation
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