Statistical analysis
In order to achieve a reliable estimation of VBC efficacy, we decided on a sample size of one hundred. To calculate this, we performed a power calculation, following the previous VBC study on women seeking help in Afghanistan due to psychosocial stress, which produced an effect size of three for the efficacy of VBC [The study hypotheses were examined through IBM SPSS Statistics version 24 using 2x2 mixed design ANOVA, with score change as a two-level within-subject variable (pre- vs. post-test) and the study group as a two-level between-subject variable (VBC vs. waiting list) for each outcome measure. In this regard, we studied the interaction effect between score change and type of study group. Bonferroni correction was used to adjust for multiple testing. Moreover, to examine extended effects of VBC from pre-test to three-month follow-up, repeated measure ANOVA was employed. Mauchly’s Test of Sphericity was significant for resilience (Independent Samples To compare effect sizes between the two groups, we calculated the effect size r, using F-ratios and degrees of freedom for each interaction effect (score change from pretest to posttest across the two groups). Concerning the VBC group, we performed Cohen’s d for each pair of pre-test and three-month follow-up assessments. The accepted significance level (α) for two-tailed statistical analyses was 