Data analysis
MCI
First, we analyzed the respondents’ “a priori” monetary value for diagnostic testing in patients with MCI. This “a priori” estimate is based on their stated preference with regard to diagnostic testing and the subsequent monetary value after the video in which the MCI case was presented, but before randomization on conditions A, B, and C varying in health benefit. To identify characteristics related to the willingness to undergo additional testing in case of MCI, characteristics of respondents (demographics, caregivers status, experiences, and own health) willing to undergo diagnostic testing were compared with respondents who were not willing to undergo diagnostic testing using logit models.Second, we analyzed the maximum price for amyloid-PET, elicited via contingent valuation. To compare the difference in how much people were willing to pay for condition A with that for conditions B and C a mixed random-parameter model was used. The “a priori” willingness to pay was included as a random effect and the model was adjusted for the order in which the “a priori” answer options were shown (ascending or descending). Confidence intervals were estimated using bootstrapping with 5000 replications. In a sub-analysis, we reran the model on the highest monetary value by applying 95 percentile winsorization on extreme values identified as outliers that are 300% of the IQR (i.e., above the median).