Effect evaluation
SENSITIVITY
Descriptive statistics will be used to analyze data concerning the participants’ demographic and baseline characteristics. Baseline differences between the intervention and control group will be analyzed using an independent sample t-test or the Mann–Whitney U-test for continuous data and the Chi-square test for categorical data. The primary analysis is an evaluation of the interventional effect of the HWePS program in the intervention area as compared to the control area. We will apply mixed effects models and generalized estimating equations adjusting for sample characteristics. In case there are significant baseline differences between groups, propensity score matching methods will be used. Subgroup analyses will be performed for sociodemographic factors (e.g., age, sex, income, etc.) and health status (e.g., frailty), and two paired t-tests will be applied for those variables collected only in the intervention group. All statistical analyses will be carried out using SAS 9.4 (Cary, NC, USA) and p-values with α ≤ 0.05 will be considered significant.Effect analysis will be conducted based on the intention-to-treat (ITT) principle, in which all participants who participated in the HWePS study will be included regardless of intervention dose or protocol adherence. Imputation methods will be implemented to handle missing data to enable ITT analysis. Sensitivity analyses will be conducted to assess the effects of inclusion in various groups within the samples.