Strengths and limitations
CMD, depression, Anxiety, anxiety
MINOR
To the authors’ knowledge, this is the first study investigating predictors of RTW in people on sick leave due to CMD (both within the CMD group as a whole and within the stress, anxiety and depression subgroups) that has applied self-reported measurement and clinical assessment, including information about health-related and psychological factors. This study includes participants on sick leave from employment and from unemployment, thus ensuring diverse representation of important demographic, social and clinical characteristics in the population. The register-based data ensured information on RTW for all participants in this study at 6 and 12 months follow-up. All these factors strengthen the study findings.However, this study has certain limitations that need to be addressed. First, the data stem from participants in two RCTs. Thus, we cannot assume that this population is representative of the general population of people on sick leave with CMD. Moreover, the fact that two-thirds of the participants received an experimental intervention may mean that results from this study cannot easily be transferred to contexts beyond the IBBIS project. We addressed this matter by adjusting for intervention group in the analysis. Another option was to only analyse data from participants included in the control group in the IBBIS project, but doing so would have resulted in markedly less power. Analyses in the subgroups were based on samples that differed in size, for instance, between 636 participants in the stress group and 222 participants in the anxiety group. These differences could have influenced the power within each subgroup to identify predictors and subsequently affect the reliability of comparing predictors across subgroups. Missing data affected a minor proportion of baseline measures. To account for this, a multiple imputation strategy was carried out. Predictable missingness structures were thus accounted for, and since no data are missing in the outcome measures, the risk of bias is small.Univariate analysis showed that many variables were significant individually, but fewer variables were found significant in the overall predictive model, probably because many of the psychometric variables are highly correlated. A correlation matrix (supplementary material) showed that most correlations to be around 0.3 and 0.7. The factors with high correlation coefficients often reflected the same underlying feature, e.g. anxiety as measured with BAI and the 4DSQ Anxiety.