Data analysis
SE
Baseline characteristics were compared between the intervention and control groups using independent t-test, Welch’s independent t-test, and two-tailed Fisher’s exact test as appropriate. Normality was tested using the Skewness/Kurtosis test. All compared baseline variables had a normal distribution.For outcome measures, only those that completed at least one intervention or control session were analyzed given high drop-out. For participants that were included in the final analysis, 7.0% of KDQOL, PHQ-9 or self-care data was missing. For participants that had at least one study follow-up, but then subsequently did not complete the study (n = 5), the pattern of missing data was considered monotone. For participants that completed all study procedures, data was determined to be missing at random. For these participants only 0.25% of data was missing. Missing KDQOL and PHQ-9 measures were imputed using the last observation carried forward (LOCF). Missing self-care outcomes were left blank. For each QOL outcome, average changes from pre to post, were summarized via means (±SD) and 95% confidence intervals. Mean absolute differences between outcome scores pre-post intervention (week 0 and week 16) were compared within groups using paired t-tests and between groups using independent t-test or with an appropriate non-parametric test. The effect of our intervention was also estimated using a linear model for each post-treatment KDQOL score, adjusting for pre-treatment score and treatment arm (ANCOVA) and using a mixed effects sensitivity model examining the linear trend of MCS and PCS scores over week 0,8 and 16 and a group by time interaction. LOCF was used for the ANCOVA model, while missing outcomes were left blank for a mixed effects model sensitivity analysis. A 2-tailed alpha level of 0.05 was used for all analyses. All statistical analyses were conducted using Stata SE, version 15.0 (StataCorp, College Station, TX).For the semi-structured interviews, transcripts were coded independently by three team members for identification of initial themes and then checked for inter-rater agreement. Content analysis conducted by marking and categorizing key words and phrases to identify themes of relevance to study participants [