Analyses
depression, PTSD, NB, post-traumatic, Depression, DSM-5
REGRESSION
Analyses were performed according to the intention-to-treat principle, using the IBM SPSS software (version 25; IBM Corp., Armonk, NY, USA). To prevent bias from possibly selective loss to follow-up, missing data were accounted for using multiple imputations with predictive mean matching. The following predictors were included in the imputation model: treatment condition, age, sex, educational level, cultural background, severity of PTSD symptoms based on the CAPS-5 score, post-traumatic symptom severity as measured with the PTSD Checklist for DSM-5 (PCL-5), depression severity as measured with the Beck Depression Inventory, second edition (BDI-II-NL) (Beck et al., For the health-economic evaluation, incremental net–benefit regression analysis (INBRA) with adjustment for baseline imbalance in utility was used. Group differences in costs were related to group differences in QALYs using cost-effectiveness acceptability curves. Depending on the willingness to pay (WTP) per QALY, acceptability curves show the probability that each of the conditions is economically preferred over the other two conditions, i.e. the probability that the condition has the highest net benefit (NB = WTP × QALYs – Costs). Bootstrapping was used to estimate these acceptability curves (Hoch, Rockx & Krahn, In the Netherlands, the WTP ceiling for gaining one QALY ranges from €20,000 to €80,000, depending on the severity of the condition at hand (Zorginstituut Nederland, 