Table 2. Simple and multiple regression models for time to relapse, chronicity, and depression scores (T2, T3) in remitted depressed patients (rMDD).
| outcome variables | shorter time to relapse after T1a (n = 57) | chronicity/ % of weeks with significant symptoms after T1b (n = 57) | composite depression score (BDI-II/MADRS) T2, T3c (n = 57) | |||
|---|---|---|---|---|---|---|
| predictors | simple | multiplef | simple | multiplef | simple | multiplef |
| B (SE) | B (SE) | B (SE) | B (SE) | B (SE) | B (SE) | |
| demographics | ||||||
| Age | 0.003 (0.019) | - | - 0.001 (0.014) | - | 0.007 (0.010) | - |
| sex (1 = m, 2 = f) | -0.518 (0.388) | - | - 0.547 (0.313) | - | 0.236 (0.239) | - |
| education level (0 = ≥10y, 1 = <10 y) | 0.238 (0.040) | - | 0.074 (0.304) | - | -0.034 (0.229) | - |
| clinical variables | ||||||
| medication use (0 = no, 1 = yes) | -0.116 (0.437) | - | -0.388 (0.337) | - | -0.366 (0.303) | - |
| residual symptoms at baseline | 0.498 (0.173)** | 0.585 (0.187)** | 0.360(0.135)** | - | 0.522(0.082)*** | 0.502(0.077)*** |
| trait repetetive negative thinking | 0.020 (0.014) | - | 0.037(0.039)*** | 0.032(0.009)*** | 0.024(0.007)*** | - |
| affective state variables (AA)d | ||||||
| valence | -0.289 (0.240) | - | -0.293 (0.160) | - | -0.386(0.113)** | - |
| energetic arousal | -0.189 (0.248) | - | -0.366(0.181)* | - | -0.436(0.128)** | - |
| calmness | -0.291 (0.242) | - | -0.202 (0.169) | - | -0.338(0.120)* | - |
| instability of valence | 0.396(0.191)* | 0.511 (0.205)* | 0.213 (0.159) | - | 0.209 (0.118) | - |
| instability of energetic arousal | 0.156 (0.147) | - | 0.165 (0.129) | - | 0.064 (0.099) | - |
| instability of calmness | 0.229 (0.131) | - | 0.214 (0.119) | - | 0.089 (0.091) | - |
| cognitive state variables (AA)d | ||||||
| rumination | 0.275 (0.162) | - | 0.185 (0.132) | - | 0.283(0.093)** | - |
| rumination*timee | - | - | - | - | 0.290(0.127)* | - |
| instability of daily-life rumination | 0.138(0.065)* | - | 0.093 (0.057) | - | 0.099(0.042)* | 0.065 (0.031)* |
a cox regression model
b linear regression model
c mixed models (hierarchical linear models)
d AA Ambulatory Assessment variable
e model includes main effects and interaction effect of predictor and time
f all multiple models included subsample status as a covariate
*** p < .001
** p < .01
* p < .05