Statistical methods for primary and secondary outcomes {20a}
depression, anxiety
REGRESSION, SECONDARY
We anticipate that the block randomization will successfully eliminate confounding by covariates, but potential confounding variables will be measured on all questionnaires, and imbalance between intervention and control groups assessed prior to the final analysis. Any imbalance in confounding variables between the groups will be controlled for as appropriate, using cox proportional hazards or logistic regression modelling. Descriptive statistics will be calculated for all participant characteristics that have the potential to act as confounding variables on the primary association between the intervention and gestational age.Time-to-event analysis will be used to assess change in our primary outcome of gestational age at delivery.Logistic regression will be used to model the association between the intervention and categorical secondary outcome of depression (scoring 13 or greater on the EPDS), post-intervention, and 6 and 12 months postpartum. Secondary outcomes of difference in continuous scores on the EPDS (depression), PROMIS (anxiety), and parenting self-efficacy scales between intervention and control groups will be modelled using linear regression.