Statistical analysis
REGRESSION, SECONDARY
This study used a Bayesian adaptive design to determine the final sample size (up to a maximum of 150 participants), employing a sequential Bayesian design with maximal sample size [Frequentist analyses were completed in Stata (version 17) and used an intention-to-treat (ITT) population, defined here as all randomised participants (Frequentist statistical analyses were conducted for primary and secondary outcomes in accordance with our statistical analysis plan (osf.io/2xn5m; Descriptive Statistical Analysis Plan). Descriptive statistics were presented as frequencies and percentages (out of non-missing) for categorical variables. The mean and standard deviation and/or median and first and third quartiles (interquartile range; IQR) were presented for continuous variables. All statistical tests were two-sided with a 5% significance level. Treatment effect size estimates and corresponding 95% confidence intervals (CIs) were presented for between-group comparisons and within-group changes.Between-group comparisons were conducted to determine the effect of the intervention plus symptom monitoring for 4 weeks on primary and secondary outcomes at 4 weeks. Additionally, within-group comparisons were conducted to detect differences in number of intrusive memories before and after the intervention. Likewise, within-group comparisons were performed to determine treatment effects of the intervention on other secondary outcomes before and after the intervention in the immediate intervention and delayed access (comparator) arms.For the primary outcome analysis, a Zero Inflated Negative Binomial (ZINB) regression model was used with the baseline measure and binary arm status included as covariates, along with binary arm status as a covariate for the zero-inflated part of the model. This was chosen following a numerical model comparison (AIC, BIC) and inspection of a visual plot of difference of observed and predicted values (model fit of general Poisson, Zero Inflated Poisson, Negative Binomial, and Zero Inflated Negative Binomial were compared).Single level general Poisson regression was used to quantify within arm changes of number of intrusive memories pre- to post-intervention. For other secondary outcomes, multilevel modelling (MLM) was performed with baseline measure, binary arm status, follow-up time and arm-by-time interaction included as fixed-effect covariates, and individual participant taken as a level-two analytical unit [