Both descriptive and analytic statistics will be used, in order to compare groups and for analyses of changes over time. Non-parametric statistics will be used when ordinal data are analysed. Otherwise, parametric statistics will be used. Besides descriptive statistics, the chi2 and Fisher's 2-tailed exact test will be used to test differences in the proportions between the groups, and odds ratio (OR) will be used to compare outcomes between groups. A value of p < 0.05 (2-sided) will be considered significant. The analysis will be made on the basis of the intention-to-treat principle. Given the old age of the participants, a relatively high drop-out rate will be inevitable, and missing data will not be at random. Simply analyzing complete cases is not relevant and might lead to bias. Therefore, the approach of data imputation will be the replacement of missing values with a value based on the median change of deterioration between baseline and follow-up of all who participated at follow-up. The reasons for this imputation method is 1) the study sample (frail older people) is expected to deteriorate over time as a natural course of the aging process and 2) reasons for not fulfilling the follow-ups are often deteriorated health. Worst-case change will be applied for those who have died before follow-up.