Statistical analysis included descriptive statistics for the prevalence of co-occurring psychiatric diagnoses in the total sample, and according to types of SUD diagnoses. We compared the characteristics of patients with - and without COD using proportion tests and independent samples t-tests. The prevalence of types of CODs was examined for the following psychiatric disorders: anxiety (F40-F49); mood (F30-39), ADHD (F90-90.9); personality disorder (F60-69); multiple CODs. Gender differences in the prevalence of each types of CODs were examined using bivariate logistic regression analysis. Bivariate logistic regression analyses were also undertaken to investigate factors associated with relapse. Repeated-measures generalized logistic mixed modeling (GLMM) with a diagonal covariance matrix was used to assess the multivariate association of demographic (age, gender, education), psychological (motivation, mental distress) and types of SUD diagnoses with relapse at 3 month follow-up. The analysis accounted for the prospective nested nature of the data structure (i.e., the same patients nested over time). Since mental distress was measured at two time points (baseline and follow-up), this variable was entered as a time-varying covariate accounting for variation in mental distress across the study period. Variables indicating the center where the patients were treated (unit 1–5) and the length of stay (number of days) were included in the multivariate models to control for any treatment- related differences in relapse rates. We did not incorporate the treatment center variable as a random effect in the analysis due to the small number of patients at each treatment center, which made it complicated to account for the variance of treatment center as a random effect due to the substantial risk of Type II error. The variance inflation factors were < 2 for all independent variables, indicating that multicollinearity was not a concern [35 ]. We ran the GLMM analyses separately for patients with and without COD. SPSS 28 was used for statistical analyses.
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