Box 2.

Structure of the different sets of OKS questions used to feed the models to derive the mapping algorithm for the EQ-5D-5L

1. All the 12 OKS questions as predictors 2. RFE-based important predictors are a subset of OKS questions determined by recursive feature elimination (RFE). RFE fits a random forest model with $5\times 5$-fold cross-validation to recursively eliminate predictors that were not required to build an accurate model [11] 3. Model-based important predictors are a subset of OKS questions which is most relevant to prediction as determined by a built-in algorithm within every model class 4. Pre-processed predictors:

The 12 OKS questions were scaled and centered. Then, principal components (Explaining 90% of the variance in OKS questions) were extracted using principal component analysis (PCA)