Statistical analysis
REGRESSION, EVENT
Descriptive statistics were calculated for all participants and the proportion of participants with and without an event of first full RTW. The time to first full RTW during the 12-month follow-up was estimated using the Kaplan–Meier estimator. The percentages of employees reporting RTW for four consecutive weeks at each specific time point (every fourth week) were illustrated using a bar graph.To examine whether psychosocial work factors and work-home interference are associated with first full RTW, a parametric Weibull survival regression model with interval-censored outcome was conducted. Interval censoring was used because the exact date of RTW was not known. If the preceding values to the first full RTW were missing, the lower limit of the censoring interval was extended to match the period with no information. If a missing value was preceded and followed by a reported non-working period, the subject was considered not to have returned to work. Observations were censored if lost to follow-up or at the end of the study (Finkelstein A post hoc analysis was conducted using a multivariate model dividing the data into two-time intervals: 0– ≤ 6- versus > 6–12 months. Weibull survival regression was first used to investigate the association between each variable of interest and the first full RTW during the two-time intervals separately. Thereafter, we used the interaction term between the time interval and the variable of interest to investigate whether the associations between the different variables and time to first full RTW differed between the two-time intervals. All analyses were conducted in Stata, version 15 (StataCorp. 2017. 