Statistical Methods
SECONDARY
We conducted intention-to-treat (ITT) analyses of all participants (N=151), and no interim analyses were conducted. In line with the protocol, we also conducted per-protocol analyses, which included all control group participants and all intervention participants who marked >50% of the intervention components as complete. As the per-protocol analysis was conducted after ITT analyses, researchers were no longer blinded to the allocation.SPSS software (IBM Corp) was used to calculate demographics and mean scores on outcome measures and to compare complete cases with the cases lost, whereas R (version 4.1.1; R Foundation for Statistical Computing) was used for all subsequent analyses. For the hypotheses regarding intervention effectiveness, linear mixed models (LMMs) were used to compare changes in outcome measures across groups and time points while controlling for age and gender. LMMs allow all participants to be retained regardless of attrition and thus are appropriate for ITT analysis [An LMM was tested for each primary and secondary outcome using the lme4 package for R [We also conducted causal mediation analysis in R using the mediation package developed by Tingley et al [Descriptive statistics were used to summarize the program engagement data, and descriptive qualitative coding was used for the interview data. The descriptive coding process began with repeated readings of all data extracts. Initial coding was used to determine patterns within the data set, which were discussed by 2 of the authors, both of whom had lived experience of a chronic condition. Subsequent coding was completed independently by 1 of the authors. The coding was conducted in the context of the research question, “What are the experiences of young people completing the SCO-CMC program?” The codes aimed to capture surface-level trends in the data relating to participants’ program experiences and recommendations.