Such detail is crucial for reliable predictions of depression-scale sedimentary architecture within and/or between individual oil fields.
LEIDS-R scores were also found to have a unique contribution to the prediction of depression, over and above trait level of depressive rumination (Moulds et al. 2008).
First, the slightly higher prediction of depression in the present study is related to a more accurate prediction of the presence of depressive disorder by AD in our sample.
Further, there was a significant Gender × Care as Self-Sacrifice subscale interaction in the prediction of depression, such that this subscale was negatively correlated to depression in men, and uncorrelated in women.
For the prediction of depression, between May and June in 2013, we collected data from 1000 participants (male: 426, female: 574).
In addition to baseline depression, the number of negative mental images significantly contributed to the prediction of depression severity two months later.
Previous findings support the evidence that age contributes significantly to the prediction of depression [ 10, 36, 37].
The number of negative images experienced during the same time frame significantly contributed to the prediction of depression severity eight weeks later, over and above baseline depression scores.
Studies by Ehring et al. (2008) and Kleim et al. (in press) demonstrated a relative specificity of theory-derived cognitive factors in the prediction of depression and PTSD.
It may be that prediction of depression provided by the 5-HTTLPR×cortisol interaction is related to prior episodes or may only occur in those with recurrent episodes.
DAS sub-scales showed differences in parameter values for the prediction of depression, both the relation between baseline levels and the relation between changes in these two factors.
