Primary analyses
REGRESSION
The primary outcome was the BMQ-AET differential score after viewing the information leaflet. Descriptive statistics were used to summarize necessity belief, concern, and BMQ-AET differential scores overall and by component. Multiple linear regression with effect coding (−1, +1) was used to directly assess the main effects and the interaction effects of the components on the BMQ-AET differential. The model included all main effects and all interactions, and baseline BMQ-AET differential scores and age as covariates. Coefficients are reported as they originate from the model, which is half what they would traditionally be defined to be, due to the use of effect coding. Data were analyzed using R Statistical Software (R version 4.2.0, April 22, 2022) [