Statistical analysis
All data analysis was performed using the IBM Statistical Package for the Social Sciences (SPSS) 22.0 (SPSS Inc., Chicago, IL, USA). Senior residents’ characteristics and outcome variables were first depicted by descriptive statistics. Categorical Chi-square tests and independent t-tests were used to compare differences in characteristics between the two groups. To evaluate the effects of the intervention, a Linear mixed model (LMM) was employed. This model accounts for both within-group changes over time (main effects) and differences in these changes between the MBEC group and control group across time (interaction effects), exhibiting robust while handling missing data. The LMM primarily examined the interaction effects between the MBEC and control groups, along with the trajectory of change in outcomes of mental health and spiritual well-being over the course of the intervention and 4-week follow-up. The interaction between group (MBEC versus control) and time (baseline, mid-intervention, post-intervention, and 4-week follow-up) offered insights into the differential impact of the MBEC program compared to the control condition over time. Additionally, effect sizes were calculated for the outcome measures as well as the statistical significance. A p-value under 0.05 was considered statistically significant.