Data analysis
There were two main questions for the intended comparison across countries. First, we tested if there were any differences across the three types of aging between Mexico and Spain. For this question, we compared only the pretest scores across all six measures, for the three types of aging, using Second, we analyzed if the effects of the interventions varied across countries. For this question, we ran linear mixed-effects models with the R packages lme4 [Building separate models for each type of aging makes the interpretation easier, and it is justified if there are significant interactions with time and condition. Given that we built separate models for each country, we further tested the same models pooling all participants from both countries where we included the triple interaction between time, condition, and country as a predictor. These pooled models add further evidence of differential effects across countries where those are detectable. Finally, to further clarify the interactions in each country, we ran simple main effects analyses for the predictor time within each group condition in each country, by comparing pre- and postintervention scores with paired sample Scores were assumed robust enough to analyze them with parametric statistics, based on the assumption analyses reported by the authors [