Statistical analysis
SECONDARY
Descriptive statistics were used to describe participants’ general characteristics. Frequencies, t tests and chi-square tests were used to explore agreement in demographics between both groups on general characteristics. The primary analyses were performed according to the intention-to-treat principle. Per-protocol analyses were performed for participants who attended all face-to-face meetings of the PARASOL intervention and for all participants in the usual care group, despite per-protocol analyses were not planned in the initial study protocol [We performed univariate and multivariate analyses to determine the effectiveness of the PARASOL intervention on mean differences in the primary and secondary outcome measures on short- and long-term. In both univariate and multivariate analyses, the baseline value was included as covariate [To determine if linear mixed model analysis with a 2-level hierarchy was necessary, heterogeneity was assessed across health care centers on quality of life as primary outcome measure by calculating the ICC. The highest ICC was found to be 0.034. Linear mixed model analyses were performed, but no variations between clusters was observed. Therefore, only univariate and multivariate intention-to-treat analyses are presented in the tables.Per-protocol analyses consisted of multivariate analyses controlling for the same variables as the primary analyses. Additional sensitivity analyses were performed by comparing the results of the main analysis of subjective symptom impact for different cut-off points to ensure the validity of the results. On short-term, we adjusted the cut-off points by defining a responder as a participant who reported adequate relief of their symptoms for at least 40% or at least 60% of the measurements. On long term, we adjusted the cut-off points by defining a responder as a participant who reported adequate relief of their symptoms for at least 40% or at least 70% of the measurements. Analyses were carried out using SPSS Statistics 25.0 (IBM SPSS, Chicago, Illinois).