Statistical methods
REGRESSION, SENSITIVITY, REGRESSIONS
Descriptive statistics were used to describe the sample characteristics. Continuous variables were described by means and standard deviations (SD) and categorical data as counts and percentages. Crude comparisons between pairs of variables were performed using t-test for continuous variables and chi-square for categorical variables.As the dependent variable (QoL) was assessed at two time points, all models were constructed with QoL variable assessed at T3 and adjusted for QoL variable measured at T1 to account for the design and possible statistical dependencies as the same individuals were assessed two times. All models are conducted with listwise exclusion, and the number of participants used in each model is marked in Tables A linear regression model was fitted with QoL as the dependent and intervention vs. control groups (labeled: Intervention) as the independent variable. We constructed one regression model for each of the four QoL domains at T3. All the models were adjusted for baseline differences between the intervention and control groups. Further, we constructed an interaction term to test whether the effect of the intervention on our outcome depended on the QoL level at T1, e.g., that the intervention had a larger effect on those who had lower QoL in pregnancy. This variable is labeled Intervention*QoL domain and included as an independent variable.As no differences in the outcome were found between the intervention and control groups, a two-step linear regression with a backward selection method was used to investigate the association between QoL domains, social support, and the selected possible predictive factors in the whole sample of first-time mothers. We tested four regression models, one for each of the four QoL domains assessed at T3. In the first step of each model, we entered the four subscales of the PICSS functional scale (informational, instrumental, emotional, appraisal) and PICSS structural scale (formal and informal supporters) assessed at T2, and the QoL domain assessed at T1. In the second step, we retained the variables that were statistically significant from step one and included the selected possible predictive factors (family income, pregnancy week at T1, age of the mother, and perception of sleep at T1 and T2). The criterion for removing variables from the model in the linear regression with backward selection method was set to The results of all linear regressions are presented as unstandardized regression coefficient (B), with 95% confidence interval for B (95% CI), and Sensitivity analyses were conducted to explore if answering the survey after the outbreak of COVID-19, which was on March 12Internal consistency reliability was examined by calculating Cronbach’s alpha for all WHOQOL-BREF domain scales and subscales of the PICSS functional scale.All statistical analyses were conducted in SPSS, version 28, in the secure platform of Services for Sensitive Data [