Statistical analyses
The intention-to-treat principle will be followed, where all participants who completed the baseline questionnaire will be included in the analysis regardless whether they complete the whole intervention. Acknowledging there may be attrition at the follow-up, the missing values for the non-respondents will be recorded using their baseline scores. If the missing data are at random, the imputation method will be applied. This will assure no false improvement in efficacy. Data will be analysed using SPSS Version . The demographics of the participants in the intervention and control groups will be compared using the independent samples t-test or Pearson’s Chi-square test to measure differences including age, gender and country of birth. The primary outcome measures (described above) will be calculated following validated MHFA scoring methods reported in the literature. Repeated measures analysis of variance will be employed to assess continuous measures between the intervention and control group over three time points (baseline, post intervention and two months post intervention). Logistic regression will be used to assess changes in dichotomous variables. The significance level will be set at 5%.